Observation Collection List
Get a list of Project objects. Projects have a 1:1 mapping with Observations.
GET /api/v3/observationcollections/?format=api&offset=500
{ "count": 948, "next": "https://api.catalogue.ceda.ac.uk/api/v3/observationcollections/?format=api&limit=100&offset=600", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/observationcollections/?format=api&limit=100&offset=400", "results": [ { "ob_id": 24366, "uuid": "da178ab717344a08adaf552151f21857", "short_code": "coll", "title": "HYPPOS: in-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft", "abstract": "In-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft for HYPPOS- HYdrodynamic control of Primary Producers in Optically Shallow fluvial lakes .", "keywords": "HYPPOS, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:50:18", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24365, "uuid": "dcf8fa7420084d8fb6d6d47d53c44b0e", "short_code": "ob", "title": "APEX EUFAR HYPPOS Flight, 2014-09-27: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the HYPPOS- HYdrodynamic control of Primary Producers in Optically Shallow fluvial lakes project (flight reference: apex_dlr-dornier_20140927_hyppos).\r\n\r\nData were collected over the Mantua, Northern Italy area.\r\n\r\n\r\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 99795, 99796, 99799, 99800, 99801, 99802, 99803, 99794, 99797, 99798 ], "onlineresource_set": [], "project_set": [ 19950 ] }, { "ob_id": 24371, "uuid": "e731614223bf470aa8510e64f2562ce1", "short_code": "coll", "title": "RAIN4DUST: in-situ airborne observations by the FA20 - SAFIRE aircraft aircraft", "abstract": "In-situ airborne observations by the FA20 - SAFIRE aircraft aircraft for RAIN4DUST - Contribution of flash floods to the variability of dust emission in the Sahara .", "keywords": "RAIN4DUST, EUFAR, aircraft, atmospheric", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:50:29", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24375, "uuid": "85119583d35e40548a8dd456f5f3e68b", "short_code": "ob", "title": "SAFIRE-FA20 FS18 EUFAR RAIN4DUST Flight, 2011-06-16: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the SAFIRE Falcon20 Core Instrument suite onboard the FA20 - SAFIRE aircraft for the RAIN4DUST - Contribution of flash floods to the variability of dust emission in the Sahara project (flight reference: fs18).\n\nData were collected over the Central Saharan mountains, Chad area.\n" }, { "ob_id": 24370, "uuid": "895db6ebb74f4b54b7081a5f9cbe2ad2", "short_code": "ob", "title": "SAFIRE-FA20 FS13 EUFAR RAIN4DUST Flight, 2011-06-11: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the SAFIRE Falcon20 Core Instrument suite onboard the FA20 - SAFIRE aircraft for the RAIN4DUST - Contribution of flash floods to the variability of dust emission in the Sahara project (flight reference: fs13).\n\nData were collected over the Central Saharan mountains, Chad area.\n" }, { "ob_id": 24379, "uuid": "1f55f8266847470585d1ad934e3ba849", "short_code": "ob", "title": "SAFIRE-FA20 FS26 EUFAR RAIN4DUST Flight, 2011-06-23: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the SAFIRE Falcon20 Core Instrument suite onboard the FA20 - SAFIRE aircraft for the RAIN4DUST - Contribution of flash floods to the variability of dust emission in the Sahara project (flight reference: fs26).\r\n\r\nData were collected over the Central Saharan mountains, Chad area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 99816, 99817, 99818, 99819, 99820, 99821, 99822, 99823 ], "onlineresource_set": [], "project_set": [ 19946 ] }, { "ob_id": 24384, "uuid": "9e8d1f472c454ceca12b59577d95049a", "short_code": "coll", "title": "UR-TIR: in-situ airborne observations by the CASA 212 RS - INTA aircraft aircraft", "abstract": "In-situ airborne observations by the CASA 212 RS - INTA aircraft aircraft for UR-TIR- Urban mapping with airborne thermal infra red imagery .", "keywords": "UR-TIR, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:51:32", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24383, "uuid": "8edd26f597de4f168c6d92b95e19aecb", "short_code": "ob", "title": "INTACASA-RS EUFAR UR-TIR Flight, 2011-07-05: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the UR-TIR- Urban mapping with airborne thermal infra red imagery project (flight reference: intacasa-rs_20110705_urtir).\r\n\r\nData were collected over the Munich and Bochum, Germany area." }, { "ob_id": 24388, "uuid": "744a336cacbf480dbc679be7de11a9e7", "short_code": "ob", "title": "INTACASA-RS EUFAR UR-TIR Flight, 2011-07-12: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the UR-TIR- Urban mapping with airborne thermal infra red imagery project (flight reference: intacasa-rs_20110712_urtir).\r\n\r\nData were collected over the Munich and Bochum, Germany area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 99861, 99862, 99863, 99865, 99866, 99867, 99868, 99869, 99864 ], "onlineresource_set": [], "project_set": [ 19939 ] }, { "ob_id": 24393, "uuid": "780e9bb79a1c4280aa3b96241bbd62d5", "short_code": "coll", "title": "REFLEX: in-situ airborne observations by the CASA 212 RS - INTA aircraft aircraft", "abstract": "In-situ airborne observations by the CASA 212 RS - INTA aircraft aircraft for REFLEX- Regional Experiments For Land-atmosphere EXchanges.", "keywords": "REFLEX, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:51:24", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24392, "uuid": "99fe854aa89f4ba388308ae6a56802c1", "short_code": "ob", "title": "INTACASA-RS EUFAR REFLEX Flight, 2012-07-04 BU: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the REFLEX- Regional Experiments For Land-atmosphere EXchanges project (flight reference: intacasa-rs_20120704_REFLEX_BU).\r\n\r\nData were collected over the Albacete, Spain area." }, { "ob_id": 24401, "uuid": "d7ccdf23e45b4d21a8bdd7b8fb20081e", "short_code": "ob", "title": "INTACASA-RS EUFAR REFLEX Flight, 2012-07-26: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the REFLEX- Regional Experiments For Land-atmosphere EXchanges project (flight reference: intacasa-rs_20120726_reflex).\r\n\r\nData were collected over the Albacete, Spain area." }, { "ob_id": 24397, "uuid": "a17a1ae8b7d74da58b59761aea965f76", "short_code": "ob", "title": "INTACASA-RS EUFAR REFLEX Flight, 2012-07-25: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the REFLEX- Regional Experiments For Land-atmosphere EXchanges project (flight reference: intacasa-rs_20120725_reflex).\r\n\r\nData were collected over the Albacete, Spain area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 99895, 99896, 99897, 99898, 99899, 99900, 99901, 99902 ], "onlineresource_set": [], "project_set": [ 19966 ] }, { "ob_id": 24406, "uuid": "5cc1d6587533461fbfaf7d9fcc5ce86c", "short_code": "coll", "title": "HYMOUNTECOS: in-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft", "abstract": "In-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft for HyMountEcos- Hyperspectral Remote Sensing for Mountain Ecosystems (HYMOUNTECOS).", "keywords": "HYMOUNTECOS, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:51:41", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24414, "uuid": "58c2847b44c1408e877858b265813ee9", "short_code": "ob", "title": "APEX EUFAR HYMOUNTECOS Flight, 2012-09-10 hyme3: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the HyMountEcos- Hyperspectral Remote Sensing for Mountain Ecosystems (HYMOUNTECOS) project (flight reference: apex_dlr-dornier_20120910_hymountecos_hyme3).\r\n\r\nData were collected over the Giant Mountains (Karkonosze/Krkonose) National Park. Border of the Czech Republic and Poland area.\r\n\r\n\r\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." }, { "ob_id": 24405, "uuid": "fc62352a78874c10b7bed5d682ead39e", "short_code": "ob", "title": "APEX EUFAR HYMOUNTECOS Flight, 2012-09-10 hyme2: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the HyMountEcos- Hyperspectral Remote Sensing for Mountain Ecosystems (HYMOUNTECOS) project (flight reference: apex_dlr-dornier_20120910_hymountecos_hyme2).\n\nData were collected over the Giant Mountains (Karkonosze/Krkonose) National Park. Border of the Czech Republic and Poland area.\n\n\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." }, { "ob_id": 24410, "uuid": "5713bc205dbc4a87b30d4a0189598260", "short_code": "ob", "title": "APEX EUFAR HYMOUNTECOS Flight, 2012-09-10 hyme1: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the HyMountEcos- Hyperspectral Remote Sensing for Mountain Ecosystems (HYMOUNTECOS) project (flight reference: apex_dlr-dornier_20120910_hymountecos_hyme1).\n\nData were collected over the Giant Mountains (Karkonosze/Krkonose) National Park. Border of the Czech Republic and Poland area.\n\n\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." }, { "ob_id": 24418, "uuid": "47107d89764b4d30843dfbe44fed3d12", "short_code": "ob", "title": "APEX EUFAR HYMOUNTECOS Flight, 2012-09-10 hymeb: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the HyMountEcos- Hyperspectral Remote Sensing for Mountain Ecosystems (HYMOUNTECOS) project (flight reference: apex_dlr-dornier_20120910_hymountecos_hymeb).\n\nData were collected over the Giant Mountains (Karkonosze/Krkonose) National Park. Border of the Czech Republic and Poland area.\n\n\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 99941, 99942, 99943, 99946, 99947, 99948, 99949, 99950, 99944, 99945 ], "onlineresource_set": [], "project_set": [ 19959 ] }, { "ob_id": 24423, "uuid": "0f98ddb81f044c9f8eb2141767076c50", "short_code": "coll", "title": "VESSAER: in-situ airborne observations by the ENDURO - KIT aircraft aircraft", "abstract": "In-situ airborne observations by the ENDURO - KIT aircraft aircraft for VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region .", "keywords": "VESSAER, EUFAR, aircraft, atmospheric", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:51:48", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24422, "uuid": "f8476979b7ff4c178701325053aa1cb2", "short_code": "ob", "title": "KIT-ENDURO EUFAR VESSAER Flight, 2012-06-30: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the KIT Enduro core instruments onboard the ENDURO - KIT aircraft for the VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region project (flight reference: 20120630).\n\nData were collected over the Corsica, France area.\n" }, { "ob_id": 24447, "uuid": "d281edaadf0245b8bb0aeafa9af4fa80", "short_code": "ob", "title": "KIT-ENDURO EUFAR VESSAER Flight, 2012-07-12: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the KIT Enduro core instruments onboard the ENDURO - KIT aircraft for the VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region project (flight reference: 20120712).\n\nData were collected over the Corsica, France area.\n" }, { "ob_id": 24443, "uuid": "35ad728e1bc04150819ac607a953656a", "short_code": "ob", "title": "KIT-ENDURO EUFAR VESSAER Flight, 2012-07-09: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the KIT Enduro core instruments onboard the ENDURO - KIT aircraft for the VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region project (flight reference: 20120709).\r\n\r\nData were collected over the Corsica, France area.\r\n" }, { "ob_id": 24435, "uuid": "8cff18fdc2a846f19ff6777ff4f56b7c", "short_code": "ob", "title": "KIT-ENDURO EUFAR VESSAER Flight, 2012-07-06: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the KIT Enduro core instruments onboard the ENDURO - KIT aircraft for the VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region project (flight reference: 20120706).\n\nData were collected over the Corsica, France area.\n" }, { "ob_id": 24451, "uuid": "3d5ad59b875b4732bbe8dd5c2143a2bd", "short_code": "ob", "title": "KIT-ENDURO EUFAR VESSAER Flight, 2012-06-27: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the KIT Enduro core instruments onboard the ENDURO - KIT aircraft for the VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region project (flight reference: 20120627).\n\nData were collected over the Corsica, France area.\n" }, { "ob_id": 24431, "uuid": "839d00480d794bad92380ed51757bdef", "short_code": "ob", "title": "KIT-ENDURO EUFAR VESSAER Flight, 2012-07-04: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the KIT Enduro core instruments onboard the ENDURO - KIT aircraft for the VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region project (flight reference: 20120704).\n\nData were collected over the Corsica, France area.\n" }, { "ob_id": 24427, "uuid": "0598d36de4a84d88bc057875910391f4", "short_code": "ob", "title": "KIT-ENDURO EUFAR VESSAER Flight, 2012-07-01: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the KIT Enduro core instruments onboard the ENDURO - KIT aircraft for the VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region project (flight reference: 20120701).\r\n\r\nData were collected over the Corsica, France area.\r\n" }, { "ob_id": 24439, "uuid": "9682f34665574b298744f814a976278d", "short_code": "ob", "title": "KIT-ENDURO EUFAR VESSAER Flight, 2012-07-08: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the KIT Enduro core instruments onboard the ENDURO - KIT aircraft for the VESSAER - VErtical Structure and Sources of AERosols in the Mediterranean Region project (flight reference: 20120708).\n\nData were collected over the Corsica, France area.\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100006, 100007, 100008, 100010, 100011, 100012, 100013, 100014, 100009 ], "onlineresource_set": [], "project_set": [ 20356 ] }, { "ob_id": 24456, "uuid": "e8e304c1449646d79f958becaab4276c", "short_code": "coll", "title": "WALITEMP: in-situ airborne observations by the ATR42 - SAFIRE aircraft aircraft", "abstract": "In-situ airborne observations by the ATR42 - SAFIRE aircraft aircraft for WaLiTemp- Inter-comparison of airborne and ground-based lidar measurements for the characterization of atmospheric water vapour and temperature profiles (WALITEMP).", "keywords": "WALITEMP, EUFAR, aircraft, atmospheric", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:50:10", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24455, "uuid": "82f3ed5c48ab4e10b79c8fbc4ce3d625", "short_code": "ob", "title": "SAFIRE-ATR42 AS38 EUFAR WALITEMP Flight, 2012-09-13: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the SAFIRE ATR42 Core Instrument suite onboard the ATR42 - SAFIRE aircraft for the WaLiTemp- Inter-comparison of airborne and ground-based lidar measurements for the characterization of atmospheric water vapour and temperature profiles (WALITEMP) project (flight reference: as38).\n\nData were collected over the Montpellier, France. Mediterranean Basin area.\n" }, { "ob_id": 24468, "uuid": "0c0bb573d2d64633b508e4c7d0cb4563", "short_code": "ob", "title": "SAFIRE-ATR42 AS62 EUFAR WALITEMP Flight, 2012-11-05: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the SAFIRE ATR42 Core Instrument suite onboard the ATR42 - SAFIRE aircraft for the WaLiTemp- Inter-comparison of airborne and ground-based lidar measurements for the characterization of atmospheric water vapour and temperature profiles (WALITEMP) project (flight reference: as62).\r\n\r\nData were collected over the Montpellier, France. Mediterranean Basin area." }, { "ob_id": 24460, "uuid": "bdd1b37c49e04923bef3df7e912f5cd8", "short_code": "ob", "title": "SAFIRE-ATR42 AS42 EUFAR WALITEMP Flight, 2012-10-02: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the SAFIRE ATR42 Core Instrument suite onboard the ATR42 - SAFIRE aircraft for the WaLiTemp- Inter-comparison of airborne and ground-based lidar measurements for the characterization of atmospheric water vapour and temperature profiles (WALITEMP) project (flight reference: as42).\r\n\r\nData were collected over the Montpellier, France. Mediterranean Basin area.\r\n" }, { "ob_id": 24464, "uuid": "9201cb35b4874da4b276524d84733226", "short_code": "ob", "title": "SAFIRE-ATR42 AS57 EUFAR WALITEMP Flight, 2012-10-29: in situ atmospheric measurements", "abstract": "In situ atmospheric measurements using the SAFIRE ATR42 Core Instrument suite onboard the ATR42 - SAFIRE aircraft for the WaLiTemp- Inter-comparison of airborne and ground-based lidar measurements for the characterization of atmospheric water vapour and temperature profiles (WALITEMP) project (flight reference: as57).\r\n\r\nData were collected over the Montpellier, France. Mediterranean Basin area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100119, 100120, 100121, 100123, 100124, 100125, 100126, 100127, 100122 ], "onlineresource_set": [], "project_set": [ 19935 ] }, { "ob_id": 24473, "uuid": "29b566562d0c4a9b969c65874091e74a", "short_code": "coll", "title": "DEHESHYRE: in-situ airborne observations by the CASA 212 RS - INTA aircraft aircraft", "abstract": "In-situ airborne observations by the CASA 212 RS - INTA aircraft aircraft for DEHESHyrE- Monitoring mass and energy fluxes in a manipulated Mediterranean tree-grass \"Dehesa\" ecosystem through the integration of ground and satellite data with airborne hyperspectral imagery (DEHESHYRE).", "keywords": "DEHESHYRE, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:46:58", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24472, "uuid": "016adea2d1804c9b99f18ca0d0e052b8", "short_code": "ob", "title": "INTACASA-RS EUFAR DEHESHYRE Flight, 2015-04-23: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the DEHESHyrE- Monitoring mass and energy fluxes in a manipulated Mediterranean tree-grass \"Dehesa\" ecosystem through the integration of ground and satellite data with airborne hyperspectral imagery (DEHESHYRE) project (flight reference: intacasa-rs_20150423_deheshyre2015).\n\nData were collected over the Las Majadas del Tieta, Spain area.\n" }, { "ob_id": 24477, "uuid": "2fff4ae492e245c6a46bad07ae2c6e15", "short_code": "ob", "title": "INTACASA-RS EUFAR DEHESHYRE Flight, 2015-07-03: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Compact Airborne Spectrographic Imager 1500i and INTA Airborne Hyperspectral Scanner instruments onboard the CASA 212 RS - INTA aircraft for the DEHESHyrE- Monitoring mass and energy fluxes in a manipulated Mediterranean tree-grass \"Dehesa\" ecosystem through the integration of ground and satellite data with airborne hyperspectral imagery (DEHESHYRE) project (flight reference: intacasa-rs_20150703_deheshyre2015).\r\n\r\nData were collected over the Las Majadas del Tieta, Spain area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100180, 100181, 100182, 100184, 100185, 100186, 100187, 100188, 100183 ], "onlineresource_set": [], "project_set": [ 19953 ] }, { "ob_id": 24482, "uuid": "1fe8654675a3453cab4a8d698d8ada48", "short_code": "coll", "title": "HILBILLY: in-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft", "abstract": "In-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft for HiLBilly- Hyperspectral imaging of lake biogeochemical properties in optically-complex systems (HILBILLY).", "keywords": "HILBILLY, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:46:46", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24486, "uuid": "92db4bc800364593b6976f202be8e3c3", "short_code": "ob", "title": "APEX EUFAR HILBILLY Flight, 2015-07-10 LakeGeneve: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the HiLBilly- Hyperspectral imaging of lake biogeochemical properties in optically-complex systems (HILBILLY) project (flight reference: apex_dlr-dornier_20150710_LakeGeneve).\r\n\r\nData were collected over the Lake Biel and Lake Geneva, Switzerland area.\r\n\r\n\r\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." }, { "ob_id": 24490, "uuid": "f397245723e346d5b1f932cb617f0ddd", "short_code": "ob", "title": "APEX EUFAR HILBILLY Flight, 2015-07-11 LakeGeneve: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the HiLBilly- Hyperspectral imaging of lake biogeochemical properties in optically-complex systems (HILBILLY) project (flight reference: apex_dlr-dornier_20150711_LakeGeneve).\r\n\r\nData were collected over the Lake Biel and Lake Geneva, Switzerland area.\r\n\r\n\r\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." }, { "ob_id": 24481, "uuid": "96e9424b5db6482085a2ab31a8401743", "short_code": "ob", "title": "APEX EUFAR HILBILLY Flight, 2015-07-10 LakeBiel: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the HiLBilly- Hyperspectral imaging of lake biogeochemical properties in optically-complex systems (HILBILLY) project (flight reference: apex_dlr-dornier_20150710_LakeBiel).\r\n\r\nData were collected over the Lake Biel and Lake Geneva, Switzerland area.\r\n\r\n\r\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100216, 100217, 100218, 100221, 100222, 100223, 100224, 100225, 100219, 100220 ], "onlineresource_set": [], "project_set": [ 19971 ] }, { "ob_id": 24495, "uuid": "191b6a219b6f450b839abe58ee30ad6c", "short_code": "coll", "title": "URBSENSE: in-situ airborne observations by the CASA 212 RS - INTA aircraft aircraft", "abstract": "In-situ airborne observations by the CASA 212 RS - INTA aircraft aircraft for UrbSense- Multi-sensor monitoring of the urban environment. (URBSENSE).", "keywords": "URBSENSE, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:52:04", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24499, "uuid": "1a751302459b4e56a76c63bcab6344c8", "short_code": "ob", "title": "INTACASA-RS EUFAR URBSENSE Flight, 2015-07-10 Ghent: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the UrbSense- Multi-sensor monitoring of the urban environment (URBSENSE) project (flight reference: intacasa-rs_20150710_hilbilly_Ghent).\r\n\r\nData were collected over the Brussels, Ghent, Leuven, Belgium area." }, { "ob_id": 24494, "uuid": "769c10fea82e4f1fb81f594dae95c117", "short_code": "ob", "title": "INTACASA-RS EUFAR URBSENSE Flight, 2015-07-10 Leuven: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the UrbSense- Multi-sensor monitoring of the urban environment (URBSENSE) project (flight reference: intacasa-rs_20150710_hilbilly_Leuven).\r\n\r\nData were collected over the Brussels, Ghent, Leuven, Belgium area." }, { "ob_id": 24503, "uuid": "ced4c4e9288d4c2d8c3ae019bae6cc4b", "short_code": "ob", "title": "INTACASA-RS EUFAR URBSENSE Flight, 2015-07-10 Brussels: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the INTA Airborne Hyperspectral Scanner and INTA Compact Airborne Spectrographic Imager 1500i instruments onboard the CASA 212 RS - INTA aircraft for the UrbSense- Multi-sensor monitoring of the urban environment (URBSENSE) project (flight reference: intacasa-rs_20150710_hilbilly_Brussels).\r\n\r\nData were collected over the Brussels, Ghent, Leuven, Belgium area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100267, 100268, 100269, 100271, 100272, 100273, 100274, 100275, 100270 ], "onlineresource_set": [], "project_set": [ 19970 ] }, { "ob_id": 24508, "uuid": "4e854c6f0c704a7bb4e5a48f547242f0", "short_code": "coll", "title": "SWAMP: in-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft", "abstract": "In-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft for SWAMP- Spectrometry of a Wetland And Modelling of Photosynthesis with Hyperspectral Airborne Reflectance and Fluorescence.", "keywords": "SWAMP, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:52:13", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24507, "uuid": "58aa3d2037b04e32a28e2a8f29f6232b", "short_code": "ob", "title": "APEX EUFAR SWAMP Flight, 2015-07-15: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the SWAMP- Spectrometry of a Wetland And Modelling of Photosynthesis with Hyperspectral Airborne Reflectance and Fluorescence project (flight reference: apex_dlr-dornier_20150715_swamp).\r\n\r\nData were collected over the Rzecin peatland site (PolWet) Site, western Poland area.\r\n\r\n\r\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100315, 100316, 100317, 100319, 100320, 100321, 100322, 100323, 100318 ], "onlineresource_set": [], "project_set": [ 19968 ] }, { "ob_id": 24513, "uuid": "7f85573628774e1bb9cd88d46d74b8c7", "short_code": "coll", "title": "AROMAPEX: in-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft", "abstract": "In-situ airborne observations by the DO228-212 /D-CFFU - DLR aircraft aircraft for AROMAPEX- APEX flights for the AROMAT-2 activity.", "keywords": "AROMAPEX, EUFAR, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2018-01-22T09:51:56", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24517, "uuid": "062b508677d549b18abe029ba504eb50", "short_code": "ob", "title": "APEX EUFAR AROMAPEX Flight, 2016-04-21 M0153-Berlin-PM: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the AROMAPEX- APEX flights for the AROMAT-2 activity project (flight reference: apex_dlr-dornier_20160421_M0153-Berlin-PM).\n\nData were collected over the Berlin, Germany area.\n\n\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." }, { "ob_id": 24512, "uuid": "4495ff6ec545436f936be43930df0546", "short_code": "ob", "title": "APEX EUFAR AROMAPEX Flight, 2016-04-21 M0152-Berlin-AM: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the Airborne Prism Experiment (APEX) instrument onboard the DO228-212 /D-CFFU - DLR aircraft for the AROMAPEX- APEX flights for the AROMAT-2 activity project (flight reference: apex_dlr-dornier_20160421_M0152-Berlin-AM).\r\n\r\nData were collected over the Berlin, Germany area.\r\n\r\n\r\nThe APEX (Airborne Prism EXperiment) instrument is an imaging spectrometer developed by a Swiss-Belgian consortium on behalf of ESA. It is operated jointly by VITO (Belgium) and RSL (Switzerland). Please see the link to the APEX website from this record for further details." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100338, 100339, 100340, 100343, 100344, 100345, 100346, 100347, 100341, 100342 ], "onlineresource_set": [], "project_set": [ 19973 ] }, { "ob_id": 24522, "uuid": "dd96551bfbaa4c19b0b1399f8131f1ff", "short_code": "coll", "title": "EUFAR10_01: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for AIMWETLAB - Aerial imaging of the wetlands of Lake Balaton and the Kis-Balaton (EUFAR10_01).", "keywords": "EUFAR10_01, AIMWETLAB, aircraft, hyperspectral, remote sensing", "publicationState": "published", "dataPublishedTime": "2021-09-29T13:41:05", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24534, "uuid": "d3bfdcd848944aafa23d6a0a99ba88a3", "short_code": "ob", "title": "ARSF 2010_238b - EUFAR AIMWETLAB/EUFAR10_01 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AIMWETLAB - Aerial imaging of the wetlands of Lake Balaton and the Kis-Balaton (EUFAR10_01) project (flight reference: 2010_238b).\r\n\r\nData were collected over the Balaton Peninsula, Hungary area." }, { "ob_id": 24526, "uuid": "7328c2d3a0bb4d0b98c3eb6f68cbc446", "short_code": "ob", "title": "ARSF 2010_234e - EUFAR AIMWETLAB/EUFAR10_01 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AIMWETLAB - Aerial imaging of the wetlands of Lake Balaton and the Kis-Balaton (EUFAR10_01) project (flight reference: 2010_234e).\r\n\r\nData were collected over the Balaton Peninsula, Hungary area.\r\n" }, { "ob_id": 24521, "uuid": "5260dbdda8824113a308ad22c9c0dc43", "short_code": "ob", "title": "ARSF 2010_233b - EUFAR AIMWETLAB/EUFAR10_01 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AIMWETLAB - Aerial imaging of the wetlands of Lake Balaton and the Kis-Balaton (EUFAR10_01) project (flight reference: 2010_233b).\r\n\r\nData were collected over the Balaton Peninsula, Hungary area." }, { "ob_id": 24530, "uuid": "28fe2b9848d54e7e83aa91b569e76344", "short_code": "ob", "title": "ARSF 2010_235b - EUFAR AIMWETLAB/EUFAR10_01 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AIMWETLAB - Aerial imaging of the wetlands of Lake Balaton and the Kis-Balaton (EUFAR10_01) project (flight reference: 2010_235b).\r\n\r\nData were collected over the Balaton Peninsula, Hungary area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100376, 100377, 100378, 100381, 100382, 100383, 100384, 100385, 100379 ], "onlineresource_set": [], "project_set": [ 19560 ] }, { "ob_id": 24539, "uuid": "caf71db90f0c44abaf332b139e31d3f2", "short_code": "coll", "title": "EUFAR10_02: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for AIRES-CZM - USING AIRBORNE REMOTE SENSING FOR IMPROVED COASTAL ZONE MANAGEMENT (EUFAR10_02).", "keywords": "EUFAR10_02, AIRES-CZM, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24543, "uuid": "66c3d2f8203449cbbef46b6d648c3f0d", "short_code": "ob", "title": "ARSF 2010_199b - EUFAR AIRES-CZM/EUFAR10_02 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AIRES-CZM - Using AIRborne REmote Sensing for improved Coastal Zone Management (EUFAR10_02) project (flight reference: 2010_199b).\r\n\r\nData were collected over the Santander, Spain area." }, { "ob_id": 24538, "uuid": "900e56bc92d3407b98a32a536641c889", "short_code": "ob", "title": "ARSF 2010_199a - EUFAR AIRES-CZM/EUFAR10_02 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AIRES-CZM - Using AIRborne REmote Sensing for improved Coastal Zone Management (EUFAR10_02) project (flight reference: 2010_199a).\r\n\r\nData were collected over the Santander, Spain area." }, { "ob_id": 24547, "uuid": "81c79c4f27d34ce78383aceaa27530c9", "short_code": "ob", "title": "ARSF 2010_200 - EUFAR AIRES-CZM/EUFAR10_02 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AIRES-CZM - Using AIRborne REmote Sensing for improved Coastal Zone Management (EUFAR10_02) project (flight reference: 2010_200).\r\n\r\nData were collected over the Santander, Spain area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100442, 100443, 100444, 100447, 100448, 100449, 100450, 100451, 100445 ], "onlineresource_set": [], "project_set": [ 19562 ] }, { "ob_id": 24552, "uuid": "7cf9d9f7868643919373052972dfad44", "short_code": "coll", "title": "EUFAR10_06: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for ARMSRACE - Archaeological and Relief Modeling of the Sárvíz valley for Reconstruction of Ancient Climate Events (EUFAR10_06).", "keywords": "EUFAR10_06, ARMSRACE, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24551, "uuid": "f6dd7b66df5f4825b067c760ac9b0cea", "short_code": "ob", "title": "ARSF 2010_231a - EUFAR ARMSRACE/EUFAR10_06 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ARMSRACE - Archaeological and Relief Modeling of the Sárvíz valley for Reconstruction of Ancient Climate Events (EUFAR10_06) project (flight reference: 2010_231a).\r\n\r\nData were collected over the Sarviz Valley, Hungary area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100494, 100495, 100496, 100499, 100500, 100501, 100502, 100503, 100497 ], "onlineresource_set": [], "project_set": [ 19599 ] }, { "ob_id": 24557, "uuid": "471c649d365b4bc496eeb8002964ac24", "short_code": "coll", "title": "EUFAR10_03: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for A.NEW - Airborne observations of Nonlinear Evolution of internal Waves generated by internal (tidal) beams (EUFAR10_03).", "keywords": "EUFAR10_03, A-NEW, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24556, "uuid": "37cb1bc255494592971918286e8a2d2b", "short_code": "ob", "title": "ARSF 2010_196 - EUFAR A-NEW/EUFAR10_03 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the A.NEW - Airborne observations of Nonlinear Evolution of internal Waves generated by internal (tidal) beams (EUFAR10_03) project (flight reference: 2010_196).\r\n\r\nData were collected over the Lisbon, Portugal area." }, { "ob_id": 24561, "uuid": "d2483ed13aa54ef1981b381b09cd7a8d", "short_code": "ob", "title": "ARSF 2010_197 - EUFAR A-NEW/EUFAR10_03 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the A.NEW - Airborne observations of Nonlinear Evolution of internal Waves generated by internal (tidal) beams (EUFAR10_03) project (flight reference: 2010_197).\r\n\r\nData were collected over the Lisbon, Portugal area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100518, 100519, 100520, 100523, 100524, 100525, 100526, 100527, 100521 ], "onlineresource_set": [], "project_set": [ 19557 ] }, { "ob_id": 24566, "uuid": "18d4617dbd724f68a51edb6f9a291bb8", "short_code": "coll", "title": "EUFAR10_07: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for ADDRESSS - ADvanced Digital REmote sensing in Ecology and earth Sciences Summer School (EUFAR10_07).", "keywords": "EUFAR10_07, ADDRESSS, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24565, "uuid": "f7df3a0869b94e728aa4dc39f8ca2d26", "short_code": "ob", "title": "ARSF 2010_234b - EUFAR ADDRESSS/EUFAR10_07 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ADDRESSS - ADvanced Digital REmote sensing in Ecology and earth Sciences Summer School (EUFAR10_07) and ADDRESSS - ADvanced Digital REmote sensing in Ecology and earth Sciences Summer School projects (flight reference: 2010_234b).\n\nData were collected over the Tihany, Hungary area.\n" }, { "ob_id": 24570, "uuid": "435ad4ddc6d447349589270060b07ab2", "short_code": "ob", "title": "ARSF 2010_234d - EUFAR ADDRESSS/EUFAR10_07 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Rollei Digital Camera, ARSF Specim AISA Eagle and ARSF Specim AISA Hawk instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ADDRESSS - ADvanced Digital REmote sensing in Ecology and earth Sciences Summer School (EUFAR10_07) (flight reference: 2010_234d).\r\n\r\nData were collected over the Tihany, Hungary area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100556, 100557, 100558, 100561, 100562, 100563, 100564, 100565, 100559 ], "onlineresource_set": [], "project_set": [ 19558 ] }, { "ob_id": 24579, "uuid": "b50ff2b787334af7b0b84df288c74683", "short_code": "coll", "title": "EUFAR11_03: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for HYMEDECOS-Erosion- HYperspectral monitoring of MEDiterranean ECOSystems: Soil erosion and water/suspended sediment transport monitoring and modelling in the Isábena catchment (NE Spain) (EUFAR11_03).", "keywords": "EUFAR11_03, HYMEDECOS-EROSION, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24578, "uuid": "b7a04f2e96464fa3997e01b4abddd55c", "short_code": "ob", "title": "ARSF 2011_092 - EUFAR HYMEDECOS-EROSION/EUFAR11_03 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the HYMEDECOS-Erosion- HYperspectral monitoring of MEDiterranean ECOSystems: Soil erosion and water/suspended sediment transport monitoring and modelling in the Isábena catchment (NE Spain) (EUFAR11_03) project (flight reference: 2011_092).\r\n\r\nData were collected over the North East Spain area.\r\n" }, { "ob_id": 24583, "uuid": "7c11501b3aa94d4eab1841504e4c5646", "short_code": "ob", "title": "ARSF 2011_095 - EUFAR HYMEDECOS-EROSION/EUFAR11_03 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instrument onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the HYMEDECOS-Erosion- HYperspectral monitoring of MEDiterranean ECOSystems: Soil erosion and water/suspended sediment transport monitoring and modelling in the Isábena catchment (NE Spain) (EUFAR11_03) project (flight reference: 2011_095).\r\n\r\nData were collected over the North East Spain area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100608, 100609, 100610, 100613, 100614, 100615, 100616, 100617, 100611 ], "onlineresource_set": [], "project_set": [ 19957 ] }, { "ob_id": 24588, "uuid": "03931bfa701444f3b7d36c619cb6a76b", "short_code": "coll", "title": "EUFAR11_04: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for HyMedEcos-Gradients - Hyperspectral monitoring of Mediterranean ecosystems: gradients of land degradation (EUFAR11_04).", "keywords": "EUFAR11_04, HYMEDECOS-GRADIENTS, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24587, "uuid": "ee52c35f235f401d8da28848084f2f2f", "short_code": "ob", "title": "ARSF 2011_097 - EUFAR HYMEDECOS-GRADIENTS/EUFAR11_04 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the HyMedEcos-Gradients - Hyperspectral monitoring of Mediterranean ecosystems: gradients of land degradation (EUFAR11_04) project (flight reference: 2011_097).\r\n\r\nData were collected over the Alentejo region, southern Portugal area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100646, 100647, 100648, 100651, 100652, 100653, 100654, 100655, 100649 ], "onlineresource_set": [], "project_set": [ 19615 ] }, { "ob_id": 24593, "uuid": "dd8369235f7c445194ad199162c5fac1", "short_code": "coll", "title": "EUFAR11_07: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for SEDMEDHY- Soil Erosion Detection within MEDiterranean agricultural areas using HYperspectral data (EUFAR11_07).", "keywords": "EUFAR11_07, SEDMEDHY, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24597, "uuid": "2afff4a60459413caef57177f2eb7b95", "short_code": "ob", "title": "ARSF 2011_222 - EUFAR SEDMEDHY/EUFAR11_07 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Hawk and ARSF Specim AISA Eagle instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the SEDMEDHY- Soil Erosion Detection within MEDiterranean agricultural areas using HYperspectral data (EUFAR11_07) project (flight reference: 2011_222).\r\n\r\nData were collected over the Toledo, Spain area." }, { "ob_id": 24592, "uuid": "76e3b9f7d61d4357b7444233607e270c", "short_code": "ob", "title": "ARSF 2011_220 - EUFAR SEDMEDHY/EUFAR11_07 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Specim AISA Eagle, ARSF Specim AISA Hawk, ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the SEDMEDHY- Soil Erosion Detection within MEDiterranean agricultural areas using HYperspectral data (EUFAR11_07) project (flight reference: 2011_220).\r\n\r\nData were collected over the Toledo, Spain area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100670, 100671, 100672, 100675, 100676, 100677, 100678, 100679, 100673 ], "onlineresource_set": [], "project_set": [ 19945 ] }, { "ob_id": 24602, "uuid": "f34f78bb1bdf44eb8b9c83f0fb6a897f", "short_code": "coll", "title": "EUFAR11_02: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for SVALBD_PGLACIAL2- Influence of climate change on paraglacial and glacial landscape evolution in Svalbard (EUFAR11_02).", "keywords": "EUFAR11_02, SVALBD-PGLACIAL2, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24601, "uuid": "965dc3424bd24c58b2f66aff57aac876", "short_code": "ob", "title": "ARSF 2011_187 - EUFAR SVALBD-PGLACIAL2/EUFAR11_02 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the SVALBD_PGLACIAL2- Influence of climate change on paraglacial and glacial landscape evolution in Svalbard (EUFAR11_02) project (flight reference: 2011_187).\r\n\r\nData were collected over the Ny-Alesund, Svalbard, Norway area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100708, 100709, 100710, 100713, 100714, 100715, 100716, 100717, 100711 ], "onlineresource_set": [], "project_set": [ 19941 ] }, { "ob_id": 24607, "uuid": "4185925e0b214c9ead505bb2ebaaaedf", "short_code": "coll", "title": "EUFAR11_06: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for DeInVader - Tracing the invasion of an exotic tree species in protected West-Mediterranean dune ecosystems (EUFAR11_06).", "keywords": "EUFAR11_06, DEINVADER, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24606, "uuid": "9d24dc80e25d4912a01fd98b2dddd6c6", "short_code": "ob", "title": "ARSF 2011_098 - EUFAR DEINVADER/EUFAR11_06 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the DeInVader - Tracing the invasion of an exotic tree species in protected West-Mediterranean dune ecosystems (EUFAR11_06) project (flight reference: 2011_098).\r\n\r\nData were collected over the Southwest Portugal area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100732, 100733, 100734, 100737, 100738, 100739, 100740, 100741, 100735 ], "onlineresource_set": [], "project_set": [ 19602 ] }, { "ob_id": 24612, "uuid": "0a46e5f36b8641e7a724fec67cb2d155", "short_code": "coll", "title": "EUFAR12_02: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for ICELAND_DEBRISFLOWS- A Study of the Hazard and Geomorphic Change Caused by Debris Flows in Iceland (EUFAR12_02).", "keywords": "EUFAR12_02, ICELAND_DEBRISFLOWS, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24616, "uuid": "d64f8597b3e04cceaebfad02ed20c729", "short_code": "ob", "title": "ARSF 2012_240b - EUFAR ICELAND_DEBRISFLOWS/EUFAR12_02 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ICELAND_DEBRISFLOWS- A Study of the Hazard and Geomorphic Change Caused by Debris Flows in Iceland (EUFAR12_02) project (flight reference: 2012_240b).\r\n\r\nData were collected over the Sugandafjorour and Skutulsfjorour in the Westfjords, Iceland area." }, { "ob_id": 24611, "uuid": "96d3dfecea96409781322479a7144636", "short_code": "ob", "title": "ARSF 2012_240a - EUFAR ICELAND_DEBRISFLOWS/EUFAR12_02 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ICELAND_DEBRISFLOWS- A Study of the Hazard and Geomorphic Change Caused by Debris Flows in Iceland (EUFAR12_02) project (flight reference: 2012_240a).\r\n\r\nData were collected over the Sugandafjorour and Skutulsfjorour in the Westfjords, Iceland area." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100756, 100757, 100758, 100761, 100762, 100763, 100764, 100765, 100759 ], "onlineresource_set": [], "project_set": [ 19961 ] }, { "ob_id": 24621, "uuid": "81607c4e67f7497483b9aa872e21da4b", "short_code": "coll", "title": "EUFAR15_68: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for HYMOSENS2: rivers HYdroMOrphological characterization by high-resolution remote SENSing data (EUFAR15_68).", "keywords": "EUFAR15_68, HYMOSENS2, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24620, "uuid": "f3330dadae7b4cf7963632791f3e24ce", "short_code": "ob", "title": "ARSF 2015_270 - EUFAR HYMOSENS2/EUFAR15_68 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the HYMOSENS2: rivers HYdroMOrphological characterization by high-resolution remote SENSing data (EUFAR15_68) project (flight reference: 2015_270).\r\n\r\nData were collected over the Ain, France area.\r\n" }, { "ob_id": 24625, "uuid": "767aa51a545047a587995a2a6078337d", "short_code": "ob", "title": "ARSF 2015_272 - EUFAR HYMOSENS2/EUFAR15_68 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera, ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the HYMOSENS2: rivers HYdroMOrphological characterization by high-resolution remote SENSing data (EUFAR15_68) project (flight reference: 2015_272).\r\n\r\nData were collected over the Ain, France area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100794, 100795, 100796, 100799, 100800, 100801, 100802, 100803, 100797 ], "onlineresource_set": [], "project_set": [ 19958 ] }, { "ob_id": 24630, "uuid": "1c3bc4fb7afe4afaa38e52ceff87712c", "short_code": "coll", "title": "EUFAR15_58: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for HOLUHRAUN_HAZ- Assessing the hazard and testing our understanding of environmental and geophysical responses from emplacement of a large volume lava flow field (EUFAR15_58).", "keywords": "EUFAR15_58, HOLUHRAUN_HAZ, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24634, "uuid": "22eb1240c2224d2aadd97e83859329bb", "short_code": "ob", "title": "ARSF 2015_247a - EUFAR HOLUHRAUN_HAZ/EUFAR15_58 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera, ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the HOLUHRAUN_HAZ- Assessing the hazard and testing our understanding of environmental and geophysical responses from emplacement of a large volume lava flow field (EUFAR15_58) project (flight reference: 2015_247a).\r\n\r\nData were collected over the Central Iceland area.\r\n" }, { "ob_id": 24629, "uuid": "e99d744614eb4edc8e1c100d0746ea34", "short_code": "ob", "title": "ARSF 2015_244b - EUFAR HOLUHRAUN_HAZ/EUFAR15_58 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera, ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the HOLUHRAUN_HAZ- Assessing the hazard and testing our understanding of environmental and geophysical responses from emplacement of a large volume lava flow field (EUFAR15_58) project (flight reference: 2015_244b).\r\n\r\nData were collected over the Central Iceland area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100832, 100833, 100834, 100837, 100838, 100839, 100840, 100841, 100835 ], "onlineresource_set": [], "project_set": [ 19956 ] }, { "ob_id": 24639, "uuid": "fa5e7e1f29f54581bcc2beedebde3a87", "short_code": "coll", "title": "EUFAR15_48: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for HIDHAZ_N_ICELAND- The hidden hazard of melting ground-ice in Northern Iceland (EUFAR15_48).", "keywords": "EUFAR15_48, HIDHAZ_N_ICELAND, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24638, "uuid": "d4595317e1ea42eea4a1653d989d5173", "short_code": "ob", "title": "ARSF 2015_249 - EUFAR HIDHAZ_N_ICELAND/EUFAR15_48 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera, ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the HIDHAZ_N_ICELAND- The hidden hazard of melting ground-ice in Northern Iceland (EUFAR15_48) project (flight reference: 2015_249).\r\n\r\nData were collected over the Mafellshyrna, Iceland area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100870, 100871, 100872, 100875, 100876, 100877, 100878, 100879, 100873 ], "onlineresource_set": [], "project_set": [ 19955 ] }, { "ob_id": 24644, "uuid": "375b9ab3f8324cabaa910c94681aa380", "short_code": "coll", "title": "EUFAR15_38: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for MEDhy^2CON- MEDiterranean HYdrological and HYperspectral monitoring of landscape CONnectivity in contrasting Mediterranean insular catchments (Mallorca, Spain) (EUFAR15_38).", "keywords": "EUFAR15_38, MEDHY2CON, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24643, "uuid": "708d98ac4b3d4784bd38521a4993b5b7", "short_code": "ob", "title": "ARSF 2015_169a - EUFAR MEDHY2CON/EUFAR15_38 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the MEDhy^2CON- MEDiterranean HYdrological and HYperspectral monitoring of landscape CONnectivity in contrasting Mediterranean insular catchments (Mallorca, Spain) (EUFAR15_38) project (flight reference: 2015_169a).\r\n\r\nData were collected over the Mallorca, Spain area.\r\n" }, { "ob_id": 24648, "uuid": "a7796c76e77347c590a79b104212f987", "short_code": "ob", "title": "ARSF 2015_169b - EUFAR MEDHY2CON/EUFAR15_38 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the MEDhy^2CON- MEDiterranean HYdrological and HYperspectral monitoring of landscape CONnectivity in contrasting Mediterranean insular catchments (Mallorca, Spain) (EUFAR15_38) project (flight reference: 2015_169b).\r\n\r\nData were collected over the Mallorca, Spain area.\r\n" }, { "ob_id": 24652, "uuid": "1810bd2581b04625908a89e3a74ba374", "short_code": "ob", "title": "ARSF 2015_170 - EUFAR MEDHY2CON/EUFAR15_38 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the MEDhy^2CON- MEDiterranean HYdrological and HYperspectral monitoring of landscape CONnectivity in contrasting Mediterranean insular catchments (Mallorca, Spain) (EUFAR15_38) project (flight reference: 2015_170).\r\n\r\nData were collected over the Mallorca, Spain area.\r\n" }, { "ob_id": 24656, "uuid": "c8e1df01bb96433089c983dfd514d703", "short_code": "ob", "title": "ARSF 2015_268 - EUFAR MEDHY2CON/EUFAR15_38 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera, ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the MEDhy^2CON- MEDiterranean HYdrological and HYperspectral monitoring of landscape CONnectivity in contrasting Mediterranean insular catchments (Mallorca, Spain) (EUFAR15_38) project (flight reference: 2015_268).\r\n\r\nData were collected over the Mallorca, Spain area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100894, 100895, 100896, 100899, 100900, 100901, 100902, 100903, 100897 ], "onlineresource_set": [], "project_set": [ 19965 ] }, { "ob_id": 24661, "uuid": "1ee932fff5ab458c8613b3e4cece6fa1", "short_code": "coll", "title": "EUFAR15_18: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for AHSPECT- Agriculture-Health-SPECTrometry (EUFAR15_18).", "keywords": "EUFAR15_18, AHSPECT, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24665, "uuid": "df5a2408710049398224d3208be173ba", "short_code": "ob", "title": "ARSF 2015_274 - EUFAR AHSPECT/EUFAR15_18 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera, ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AHSPECT- Agriculture-Health-SPECTrometry (EUFAR15_18) project (flight reference: 2015_274).\r\n\r\nData were collected over the Toulouse, France area.\r\n" }, { "ob_id": 24660, "uuid": "78fec6aeb25d407fb5a8bc8723370545", "short_code": "ob", "title": "ARSF 2015_174 - EUFAR AHSPECT/EUFAR15_18 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR and ARSF AsiaFENIX hyperspectral imager instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the AHSPECT- Agriculture-Health-SPECTrometry (EUFAR15_18) project (flight reference: 2015_174).\r\n\r\nData were collected over the Toulouse, France area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100960, 100961, 100962, 100965, 100966, 100967, 100968, 100969, 100963 ], "onlineresource_set": [], "project_set": [ 19951 ] }, { "ob_id": 24670, "uuid": "17c292712074479ea313b00e848d13d9", "short_code": "coll", "title": "EUFAR15_28: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for ISOTHERM- Ice SnOw vegetation HypERspecTral Measurements (EUFAR15_28).", "keywords": "EUFAR15_28, ISOTHERM, aircraft, hyperspectral, remote sensing", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [ { "ob_id": 24669, "uuid": "6be1cb63a6c7416593829ec273f97b10", "short_code": "ob", "title": "ARSF 2015_175a - EUFAR ISOTHERM/EUFAR15_28 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ISOTHERM- Ice SnOw vegetation HypERspecTral Measurements (EUFAR15_28) project (flight reference: 2015_175a).\r\n\r\nData were collected over the Mont Blanc, France area.\r\n" }, { "ob_id": 24682, "uuid": "70c1e4b1fbf1407b8b745a3d5b239cfa", "short_code": "ob", "title": "ARSF 2015_271b - EUFAR ISOTHERM/EUFAR15_28 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera, ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR and ARSF AsiaFENIX hyperspectral imager instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ISOTHERM- Ice SnOw vegetation HypERspecTral Measurements (EUFAR15_28) project (flight reference: 2015_271b).\r\n\r\nData were collected over the Mont Blanc, France area.\r\n" }, { "ob_id": 24674, "uuid": "2fd4455f4c2d4bf5a067992fbf1e1aee", "short_code": "ob", "title": "ARSF 2015_175b - EUFAR ISOTHERM/EUFAR15_28 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF AsiaFENIX hyperspectral imager and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ISOTHERM- Ice SnOw vegetation HypERspecTral Measurements (EUFAR15_28) project (flight reference: 2015_175b).\r\n\r\nData were collected over the Mont Blanc, France area.\r\n" }, { "ob_id": 24678, "uuid": "8ae877e98d47461391fb48ae4ea856f7", "short_code": "ob", "title": "ARSF 2015_271a - EUFAR ISOTHERM/EUFAR15_28 Flight: hyperspectral remote sensing measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Rollei Digital Camera and ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ISOTHERM- Ice SnOw vegetation HypERspecTral Measurements (EUFAR15_28) project (flight reference: 2015_271a).\r\n\r\nData were collected over the Mont Blanc, France area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 100998, 100999, 101000, 101003, 101004, 101005, 101006, 101007, 101001 ], "onlineresource_set": [], "project_set": [ 19963 ] }, { "ob_id": 24699, "uuid": "81fb84c4b00640b7a3acb58346497977", "short_code": "coll", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci) Dataset Collection", "abstract": "Collection of datasets from the European Space Agency's (ESA) Antarctic Ice Sheets Climate Change Initiative (CCI) project. This is producing long term and reliable climate data records from satellite data for a number of Essential Climate Variables (ECV's) for Antarctica. \r\n\r\nCurrent data products relate to Ice Velocities, Gravimetric Mass Balance, Grounding Line Locations and Surface Elevation Changes.", "keywords": "Antarctic, CCI, Ice Sheet", "publicationState": "published", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 32692, "uuid": "36dae49c76f845a18062fa96599be719", "short_code": "ob", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly Gravimetric Mass Balance gridded product, v3.0, 2002 - 2020", "abstract": "This dataset contains the Gravimetric Mass Balance (GMB) gridded product for the Antarctic Ice Sheet (AIS), generated by TU Dresden as part of the ESA Antarctic Ice Sheet Climate Change Initiatve (Antarctic_Ice_Sheet_cci). \r\n\r\nThe Gravimetric Mass Balance (GMB) product for the Antarctic Ice Sheet (AIS) is based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through July 2020. The GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 187 monthly solutions. The mass change estimation is based on the tailored sensitivity kernel approach developed at TU Dresden. (Groh & Horwath, 2021)\r\n\r\nThe GMB gridded product comprises time series of ice mass changes for cells of polar-stereographic grid with a sampling of 50x50 km² covering the entire AIS. A GMB basin product is also available as a separate dataset.\r\n\r\nGroh, A. & Horwath, M. (2021). Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels. Remote Sens., 13(9), 1736. doi:10.3390/rs13091736" }, { "ob_id": 24695, "uuid": "200ff3bf37d744a48b48cb2e3565cace", "short_code": "ob", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Gravimetric Mass Balance Basin products, v1.1", "abstract": "This dataset provides Gravimetric Mass Balance Basin data for the Antarctic Ice Sheet. It has been produced in the framework of the Antarctic Ice Sheets Climate Change Initiative (CCI) project, under the lead of TU Dresden. \r\n\r\nThe ice sheet mass balance, i.e. the change in ice mass over time, is determined using the US-German satellite gravimetry mission GRACE (Gravity Recovery and Climate Experiment). The Antarctic Ice Sheet CCI GMB products are based on the monthly GRACE solutions ITSG-Grace2016 by Technische Universität Graz, and comprises a time series of mass change grids covering the entire ice sheet (GMB Gridded product), along side mass change time series for different drainage basins (GMB Basin Product). \r\n\r\nThe dataset described here covers version 1.1 of the Basin product. Mass change time series are provided for a number of drainage basins. They describe the evolution of ice mass relative to a modelled reference value, defined to be the GRACE-derived mass as of 2009-01-01. Respective time series are also derived for the total areas of the West Antarctic Ice Sheet, the East Antarctic Ice Sheet, the Antarctic Peninsula and the Antarctic Ice Sheet as a whole.\r\n\r\nIf publishing results based on this dataset, please cite the following: Groh, A., & Horwath, M. (2016). The method of tailored sensitivity kernels for GRACE mass change estimates. Geophysical Research Abstracts, 18, EGU2016-12065.\r\n\r\nInteractive data visualisation is available at: https://data1.geo.tu-dresden.de/ais_gmb/" }, { "ob_id": 19879, "uuid": "2d0422ea3c4047d5829d5fbdabe0c156", "short_code": "ob", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Gravimetric Mass Balance Gridded product, v1.1", "abstract": "This dataset provides gridded Gravimetric Mass Balance data for the Antarctic Ice Sheet. It has been produced in the framework of the Antarctic Ice Sheets Climate Change Initiative (CCI) project, under the lead of TU Dresden. \r\n\r\nThe ice sheet mass balance, i.e. the change in ice mass over time, is determined using the US-German satellite gravimetry mission GRACE (Gravity Recovery and Climate Experiment). The Antarctic Ice Sheet CCI GMB products are based on the monthly GRACE solutions ITSG-Grace2016 by Technische Universität Graz, and comprises a time series of mass change grids covering the entire ice sheet (GMB Gridded product), along side mass change time series for different drainage basins (GMB Basin Product). \r\n\r\nThe dataset described here covers version 1.1 of the Gridded product. Time series of gridded mass changes are provided in a polar-stereographic projection (EPSG:3031) with a grid resolution of 50 km x 50 km. The gridded changes are given in millimetre of equivalent water height (mm w.eq., or kg/m2). \r\n\r\nIf publishing results based on this dataset, please cite the following: Groh, A., & Horwath, M. (2016). The method of tailored sensitivity kernels for GRACE mass change estimates. Geophysical Research Abstracts, 18, EGU2016-12065\r\n\r\nInteractive data visualisation is available at: https://data1.geo.tu-dresden.de/ais_gmb/" }, { "ob_id": 26543, "uuid": "bdf2cf5a78554a73bf5e57a853e3bbc0", "short_code": "ob", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Grounding Line Locations for the Ferringo, Pine Island, Thwaites, Smith, Kohler and Pope Glaciers, Antarctica, 1995-2017, v2.0 (CCI subset)", "abstract": "Grounding line locations (GLL) data for the Ferringo, Pine Island, Thwaites, Smith, Kohler and Pope Glaciers in Antarctica, produced by the ESA Antarctic Ice Sheet Climate Change Initiative (CCI) project. The grounding lines have been derived from satellite observations from the ERS-1/2 and Copernicus Sentinel-1 instruments, acquired in the period from 1995-2017.\r\n\r\nAn extended dataset of Grounding line locations for these Glaciers is available on the ENVEO CryoPortal (http://cryoportal.enveo.at/data/)" }, { "ob_id": 32600, "uuid": "7b3bddd5af4945c2ac508a6d25537f0a", "short_code": "ob", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Grounding line location for key glaciers, Antarctica, 1994-2020, v2.0", "abstract": "This dataset contains grounding line locations (GLL) for key glaciers in Antarctica, produced as part of the ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci) project. The data have been derived from satellite observations from the ERS-1/2, TerraSAR-X and Copernicus Sentinel-1 satellites, acquired between 1994 and 2020." }, { "ob_id": 32601, "uuid": "00fe090efc58446e8980992a617f632f", "short_code": "ob", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly velocity from 2017 to 2020, derived from Sentinel-1, v1", "abstract": "This dataset contains monthly gridded ice velocity maps of the Antarctic Ice Sheet derived from Sentin\r\nel-1 data acquired between 2017-01-01 and 2020-08-31. It was generated by ENVEO, as part of the ESA Antarctic Ice Sheet Climate Change Initiative project (Antarctic_Ice_Sheet_cci).\r\n\r\nThe surface velocity is derived by applying feature tracking techniques using Sentinel-1 synthetic aperture radar (SAR) data acquired in the Interferometric Wide (IW) swath mode. Ice velocity is provided at 200m grid spacing in Polar Stereographic projection (EPSG: 3031). The horizontal velocity components are provided in true meters per day, towards easting and northing direction of the grid. The vertical displacement is derived from a digital elevation model. Provided is a NetCDF file with the velocity components: vx, vy, vz, along with maps showing the magnitude of the horizontal components, the valid pixel count and uncertainty. The product combines all ice velocity maps, based on 6- and 12-day repeats, acquired within a single month in a monthly averaged product." }, { "ob_id": 24694, "uuid": "5fef473b97cf47f6a5b410f7acf2dbbe", "short_code": "ob", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Ice velocity time series for Pine Island Glacier, Antarctica, 2014-2016, v1.0", "abstract": "This dataset constists of an ice velocity time series for Pine Island Glacier, Antarctica, derived from Copernicus Sentinel-1 satellite data acquired from 2014 to 2016. It has been produced by the ESA Antarctic Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data format is 3-layer GeoTiff: the first two layers represent the horizontal displacement component easting and northing respectively in output map coordinates and converted to meters per day [m/d]. The third layer represents the vertical velocity and is derived from the height difference along the displacement vector taken from a Digital Elevation Model (DEM).\r\n\r\nThe method employed to produce this dataset was presented in: Nagler, T., Rott, H., Hetzenecker, M., Wuite, J., Potin, P. (2015). The Sentinel-1 Mission: New Opportunities for Ice Sheet Observations. Remote Sensing, 2015, 7, 9371-9389, doi:10.3390/rs70709371." }, { "ob_id": 32602, "uuid": "e1dfd0ee655944b8a82ce0479c518747", "short_code": "ob", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly Gravimetric Mass Balance basin product, v3.0, 2002-2020", "abstract": "This dataset contains the Gravimetric Mass Balance (GMB) basin product for the Antarctic Ice Sheet (AIS), generated by TU Dresden as part of the ESA Antarctic Ice Sheet Climate Change Initiatve (Antarctic_Ice_Sheet_cci). \r\n\r\nThe Gravimetric Mass Balance (GMB) product for the Antarctic Ice Sheet (AIS) is based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through July 2020. The GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 187 monthly solutions. The mass change estimation is based on the tailored sensitivity kernel approach developed at TU Dresden. (Groh & Horwath, 2021)\r\n\r\nThe GMB basin product provides time series of integrated mass changes for 26 drainage basins and the aggregations of the Antarctic Peninsula, East Antarctica, West Antarctica and the entire AIS. Based on the GMB basin product, ice mass balance estimates, i.e. linear trend in the change in ice mass, were derived for all drainage basins and aggregations. A gridded GMB product is also available as a separate dataset.\r\n\r\nGroh, A. & Horwath, M. (2021). Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels. Remote Sens., 13(9), 1736. doi:10.3390/rs13091736" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 101130, 101131, 101132, 105406, 105411, 105436, 105460, 101129 ], "onlineresource_set": [ 23274, 23275, 23273 ], "project_set": [ 24700 ] }, { "ob_id": 24737, "uuid": "31ae96f9cfc54ef9a38638f8723a1d17", "short_code": "coll", "title": "ACSIS: Data collected during the The North Atlantic Climate System Integrated Study.", "abstract": "This data collection includes a range of data collected for The North Atlantic Climate System Integrated Study: ACSIS, including: In-situ airborne observations by the FAAM BAE-146 aircraft, groundbased air composition measurements from Penlee Observatory, and Atlantic Ocean Sea Surface Temperature (SST) studies.", "keywords": "NCAS, NCEO, ACSIS, FAAM, airborne, SST, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2017-05-18T12:09:24", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8, 13 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 27859, "uuid": "7876d0c706544eee877b2bbb786f3c2e", "short_code": "ob", "title": "FAAM C211 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 37474, "uuid": "7b16d480d42248ccbf2e144456de38db", "short_code": "ob", "title": "FAAM C288 ACSIS Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 24741, "uuid": "1072c94a044646f5b0f5b6168f78e8d8", "short_code": "ob", "title": "FAAM B997 ACSIS Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 25502, "uuid": "5b937be3db27419197336ccac0f087ee", "short_code": "ob", "title": "FAAM C067 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 24736, "uuid": "85023a32f2ed467695275ba90bf3dee9", "short_code": "ob", "title": "FAAM B996 ACSIS Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 24749, "uuid": "d60cd1eb5883409d9f5ccffc70701120", "short_code": "ob", "title": "FAAM B999 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 37498, "uuid": "e525619875834d63a2a6ce84288cb130", "short_code": "ob", "title": "FAAM C294 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 41413, "uuid": "e74491c96ef24df29a9342a3d57b5939", "short_code": "ob", "title": "ACSIS: Sunphotometer aerosol measurements at Plymouth Marine Laboratory - Version 1. 2001-2023", "abstract": "Measurements of spectral aerosol optical thickness (tau), single scattering albedo (SSA), refractive index (RI), and size distribution of aerosols for preset aerosol diameters (um - microns) made using sunphotometers between June 2001 - December 2023 located on the roof of Plymouth Marine Laboratory (PML), Devon, UK, for the Western Channel Observatory (https://www.westernchannelobservatory.org.uk) and The North Atlantic Climate System Integrated Study (ACSIS). \r\n\r\nThis version 1 dataset contains measurements for 2001 to 2023. Two Kipp and Zonen (UK) PREDE POM01-L sunphotometers were used: June 2001 - March 2008 (Unknown serial number) and August 2009 - December 2023 (Serial Number PS08015). \r\n\r\nThe instruments operated at 7 wavelengths (315, 400, 500, 670, 870, 940 and 1020nm) and scanned at pre-set angles away from the solar disk to determine, using the inversion code of Nakajima et al. (1996), various optical properties of tiny particles called aerosols within the atmospheric column." }, { "ob_id": 26415, "uuid": "c0e1aab5fd604255895d200b2c4f9673", "short_code": "ob", "title": "FAAM C104 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 26290, "uuid": "130637c33a27475093552bf76c088150", "short_code": "ob", "title": "FAAM C106 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27901, "uuid": "4360e79a20a1478c91894945fa37db46", "short_code": "ob", "title": "FAAM C145 ACSIS-4 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-4) project." }, { "ob_id": 27810, "uuid": "8978b4819b4e4991bd06f5c867022d15", "short_code": "ob", "title": "FAAM C201 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 30169, "uuid": "d9d91c40bcbb46468db8de7da6e55bb4", "short_code": "ob", "title": "FAAM C228 ACSIS-6 Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ACSIS-6 FAAM Aircraft Project project." }, { "ob_id": 25493, "uuid": "8434b678f8844f14adbb6e7cba3501c9", "short_code": "ob", "title": "FAAM C066 ACSIS Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 30142, "uuid": "27e4308e50804532b14c9bc9bb054100", "short_code": "ob", "title": "FAAM C215 ACSIS-6 Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ACSIS-6 FAAM Aircraft Project project." }, { "ob_id": 30145, "uuid": "8a22902dfc554230b6cca7c89cf68043", "short_code": "ob", "title": "FAAM C216 ACSIS-6 Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ACSIS-6 FAAM Aircraft Project project." }, { "ob_id": 27861, "uuid": "0eb3a6ce574044d29733830d9fd4fb45", "short_code": "ob", "title": "FAAM C212 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 27857, "uuid": "eea5327c3aad484cb1343bec3157cd79", "short_code": "ob", "title": "FAAM C210 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 37490, "uuid": "834f5a562aac4a97ba8d84d8cf2d571f", "short_code": "ob", "title": "FAAM C292 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 25285, "uuid": "8f1ff8ea77534e08b03983685990a9b0", "short_code": "ob", "title": "Penlee Point Atmospheric Observatory: Meteorological and chemical observations 2014- present", "abstract": "The Penlee Point Atmospheric Observatory (PPAO) was established by the Plymouth Marine Laboratory in May 2014 for long term observations of ocean-atmosphere interaction. The observatory is only a few tens of metres away from the water edge and 11m above mean sea level.\r\n\r\nThis dataset contains air temperature, dew point, wind speed and direction, rainfall, sulphur dioxide, ozone, carbon dioxide and methane measurements from Penlee Point Atmospheric Observatory from 2014-2017.\r\n\r\nAt the mouth of the Plymouth Sound, the site (50° 19.08' N, 4° 11.35' W) is exposed to marine air when the wind comes from 110° - 240°. Typical southwesterly winds tend to bring relatively clean background Atlantic air. In contrast, winds from the southeast are often contaminated by exhaust plumes from passing ships. The PPAO is in close proximity to marine sampling stations that form the Western Channel Observatory, enabling better understanding of the ocean-atmosphere coupling." }, { "ob_id": 27808, "uuid": "8363ce5efc4e49d788fb98e4bf3812a7", "short_code": "ob", "title": "FAAM C200 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 27895, "uuid": "366fdf27ac7b4678a4447a52d8544ae5", "short_code": "ob", "title": "FAAM C142 ACSIS-4 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-4) project." }, { "ob_id": 24753, "uuid": "81902dc06146452e98a7db0d2b876855", "short_code": "ob", "title": "FAAM C001 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27814, "uuid": "0eafddba5d314b729271438b25133047", "short_code": "ob", "title": "FAAM C199 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 30167, "uuid": "1015965e30bf4c1f8eb7f02bedcd865a", "short_code": "ob", "title": "FAAM C226 ACSIS-6 Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ACSIS-6 FAAM Aircraft Project project." }, { "ob_id": 27893, "uuid": "735dd23c7bbc40d59ee568d1363a03e4", "short_code": "ob", "title": "FAAM C141 ACSIS-4 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-4) project." }, { "ob_id": 30492, "uuid": "83b0cd7e7cc6495a90b4cb967ead3577", "short_code": "ob", "title": "North Atlantic Climate System Integrated Study (ACSIS) Atlantic Ocean medium resolution SST dataset: Reconstructed 5-day, ½ degree, Atlantic Ocean SST (1950-2014)", "abstract": "The North Atlantic Climate System Integrated Study (ACSIS) Atlantic Ocean medium resolution SST dataset is a 5-day field of Sea Surface Temperature (SST) on a ½ degree by ½ degree grid from 1950 to 2014 and covers the Atlantic Ocean.\r\n\r\nThe dataset is based on in situ ship and buoy SST observations from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Revision 3. Measurements which fail initial quality control checks are rejected and for each grid box where there is data a trimmed mean and sample standard deviation are calculated to produce super-observations. These are then expressed as anomalies from the 1981-2014 Climatology (mean, annual, semi-annual and tri-annual) from the European Space Agency (ESA) Climate Change Initiative (CCI) SST dataset (version 2.0) derived from satellite observations. The measurements are then interpolated using Kriging to infill gaps and estimate uncertainties. The spatial covariance used in the Kriging was derived from the CCI SST analysis residuals (CCI SST analysis minus the CCI SST climatology). After interpolation, bias corrections derived from the HadSST.4.0.0.0 dataset are applied.\r\n\r\nThe dataset is available as annual CF complaint NetCDF files, with a total of 65 annual files available. Each file contains: the 5 day mean sea surface temperature; the corresponding climatological value, the sea surface temperature anomaly and the uncertainty in the sea surface temperature. \r\n\r\nThe new dataset has been developed as part of the UK North Atlantic Climate System Integrated Study (ACSIS) for use in validation and comparison with regional climate models. Other potential uses include boundary forcing for regional reanalyses, monitoring and assessment of regional climate change and other studies requiring SST at a resolution higher than typical for the in situ products (i.e. < 1 month, < 1°) and spanning the satellite and pre-satellite era." }, { "ob_id": 27842, "uuid": "3fa55ea0513c4111a2f79ad5004d0a48", "short_code": "ob", "title": "FAAM C203 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 30147, "uuid": "4687d2a5199246e38383469ac65d47b3", "short_code": "ob", "title": "FAAM C217 ACSIS-6 Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ACSIS-6 FAAM Aircraft Project project." }, { "ob_id": 37482, "uuid": "fb6891a046e448bf87661c7297052a38", "short_code": "ob", "title": "FAAM C290 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27846, "uuid": "a354aa616629419badb5b52ae0cb9313", "short_code": "ob", "title": "FAAM C205 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 37494, "uuid": "ae5cd3a3914541a592ce1f9ccba00959", "short_code": "ob", "title": "FAAM C293 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 26294, "uuid": "f22c74b77ea34adea7628dd088a4f767", "short_code": "ob", "title": "FAAM C105 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27844, "uuid": "c9fcaa2e7ee845e5bb1163863b845153", "short_code": "ob", "title": "FAAM C204 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 25518, "uuid": "677ca252ac8d44468bb473316c578ec7", "short_code": "ob", "title": "FAAM C071 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 25498, "uuid": "3450271614774081bb538de48618bb9e", "short_code": "ob", "title": "FAAM C068 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 26375, "uuid": "aed4c763415947b8bed5687d47ff4df0", "short_code": "ob", "title": "FAAM C096 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27891, "uuid": "04459aa62d5f4e7ebe2172518a842fcb", "short_code": "ob", "title": "FAAM C140 ACSIS-4 Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-4) project." }, { "ob_id": 37486, "uuid": "7ab38af8367b4c84acf8f9472f097b98", "short_code": "ob", "title": "FAAM C291 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27897, "uuid": "7ae42edd3d854ca98424c7bd3824805d", "short_code": "ob", "title": "FAAM C143 ACSIS-4 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-4) project." }, { "ob_id": 26411, "uuid": "9a586aea2b59413599b4b3d5e7b98711", "short_code": "ob", "title": "FAAM C103 ACSIS Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27889, "uuid": "23cab2d457844f8c85c2f98e91a7d496", "short_code": "ob", "title": "FAAM C139 ACSIS-4 Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-4) project." }, { "ob_id": 41414, "uuid": "88b969c2540e4d558c2896fb5b8ef613", "short_code": "ob", "title": "ACSIS: UKESM1 simulations for the North Atlantic Climate System Integrated Study", "abstract": "Three UK Earth Sysyem Model (UKESM1) hindcasts have been performed in support of the North Atlantic Climate System Integrated Study (ACSIS). \r\n\r\nData is provided as raw model output in Met Office PP (32-bit) format that can be read by the Iris (https://scitools-iris.readthedocs.io/en/stable/) or cf-python (https://ncas-cms.github.io/cf-python/) libraries.\r\n\r\nThis is global data at N96eL85 resolution (1.875 x 1.25, 85 model levels up to 85km). Simulations were performed on the Monsoon2 High Performance Computer (HPC).\r\n\r\nThe following fields are contained in the dataset: O3, NO, NO2, CO, CH4, 4x Stratospheric O3 tracers, and 30x idealised tracers emitted from various locations (15 with a 5-day e-folding lifetime, and 15 with a 30-day e-folding lifetime). Data is provided in mass mixing ratio (kg species/kg air)." }, { "ob_id": 24757, "uuid": "1d75255b335b497684c7e30506119715", "short_code": "ob", "title": "FAAM C002 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 30173, "uuid": "e8c2a0e24726480fb65b34d03a8b7d06", "short_code": "ob", "title": "FAAM C229 ACSIS-6 Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ACSIS-6 FAAM Aircraft Project project." }, { "ob_id": 37454, "uuid": "9d8303ca10fd4c9b8fdb5e718daf6b26", "short_code": "ob", "title": "FAAM C283 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 24745, "uuid": "27a478b5cc35406e84dd630b0f2fd1cc", "short_code": "ob", "title": "FAAM B998 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27840, "uuid": "62906b15a7ae44e4a11ce77c76537f58", "short_code": "ob", "title": "FAAM C202 ACSIS-5 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-5) project." }, { "ob_id": 30171, "uuid": "2fad8124836b44b7860598397f29c132", "short_code": "ob", "title": "FAAM C227 ACSIS-6 Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ACSIS-6 FAAM Aircraft Project project." }, { "ob_id": 25510, "uuid": "b95acf1fbc014892a4e5e7189b929c56", "short_code": "ob", "title": "FAAM C069 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 27899, "uuid": "157cf7e581344a6a9148fc9c540e63de", "short_code": "ob", "title": "FAAM C144 ACSIS-4 flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS (ACSIS-4) project." }, { "ob_id": 37478, "uuid": "65494ea159d847a3bfcf38ddc1e476f6", "short_code": "ob", "title": "FAAM C289 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." }, { "ob_id": 25514, "uuid": "eb136b5006a34b2693187e5e5d7aceaf", "short_code": "ob", "title": "FAAM C070 ACSIS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 101290, 101285, 101286, 101287, 101291, 101292, 101293, 101294, 101288, 101289, 131956, 131957, 131958, 131959 ], "onlineresource_set": [], "project_set": [ 24717 ] }, { "ob_id": 24762, "uuid": "d309a5ab60b04b6c82eca6d006350ae6", "short_code": "coll", "title": "MOYA: ground station and in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "This dataset collection contains ground observations and in-situ airborne observations by the FAAM BAE-146 aircraft for Methane Observations and Yearly Assessments: MOYA.\r\n\r\nThis data was collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1).", "keywords": "MOYA, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2017-05-18T12:30:08", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 28004, "uuid": "66ec51c92db7422f8ff5bf2b2d6bcd62", "short_code": "ob", "title": "FAAM C196 MOYA-Arctic flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) (MOYA-Arctic) project." }, { "ob_id": 27875, "uuid": "24374fde16cc4316afbca0b18fbe1d79", "short_code": "ob", "title": "FAAM C133 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 26920, "uuid": "dfabd91ff8034897b101d2c31e2301c7", "short_code": "ob", "title": "FAAM C125 MOYA Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 26719, "uuid": "88d1bbf6110e42abb29fc6b16eda42a0", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Zeppelin Observatory", "abstract": "This dataset contains air sample measurements of the ratio between carbon 12: carbon 13 in atmospheric methane (d13C). The air samples measured were taken from an inlet on the Zeppelin Observatory into either flasks, tedlar bags or flexfoil bags. The samples were analysed for the carbon ratio in methane at Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThis data was collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 28128, "uuid": "893b8a270f924d67af8541011f407b29", "short_code": "ob", "title": "Weybourne Atmospheric Observatory: Fourier Transform Infra-Red (FTIR) measurements", "abstract": "This dataset contains measurements taken from the Fourier Transform Infra-Red (FTIR instrument location at the Weybourne Atmospheric Observatory. The instrument measures CH4, N2O, CO and CO2.\r\n\r\nThe Weybourne Atmospheric Observatory (WAO) is a Regional station in the Global Atmosphere Watch (GAW) programme of the World Meteorological Organization (WMO). It is situated on the North Norfolk coast (52°57’02’’N, 1°07’19’’E, 15 m asl)." }, { "ob_id": 26615, "uuid": "b36ed14d0a204f4fa6b1d884a516b26e", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Methane measurements by the British Antarctic Survey from the Halley Research Station in Antarctica", "abstract": "This dataset contains methane concentration measurements from the British Antarctic Survey's Halley Research Station in Antarctica. The Picarro G2301 analyser was used for the measurement of Methane and located at the Clean Air Sector Laboratory (CASLab). Data times were averaged from the 1 minute data to provide hourly data sets. The UK participation of the Methane Observations and Yearly Assessments (MOYA) project was funded by the Natural Environment Research Council (NERC, grant: NE/N015584/1)" }, { "ob_id": 24766, "uuid": "f6431d263801473d8a2901f3a0808004", "short_code": "ob", "title": "FAAM C004 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments: MOYA project." }, { "ob_id": 27834, "uuid": "42a4a202612c4ed4810384fb25130685", "short_code": "ob", "title": "FAAM C128 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 30552, "uuid": "4d403b47cae546ca9b749c0ac932e37c", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Hong Kong 2017-2019", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples around Hong Kong Island. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 28000, "uuid": "8c64fb4a88f4413b901f2c76297df763", "short_code": "ob", "title": "FAAM C194 MOYA-Arctic flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) (MOYA-Arctic) project." }, { "ob_id": 30266, "uuid": "4c5a7badd17a4b10a00ce0327aa073d6", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Jersey Radar Station, UK 2013 to 2015", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples at Jersey Radar Station, UK. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 30540, "uuid": "dbb96efc262c44f6bc7406c3dbb890b0", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Chacaltya Observatory Station, Bolivia 2014 to 2019", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples at Chacaltya Observatory Station, Bolivia. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 32176, "uuid": "905032bf592d46cba7effe558b79145d", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): lower troposphere greenhouse gas data taken over Pantanal, Mato Grosso do Sul, Brazil", "abstract": "This dataset contains CH4, CO2, CO, N2O and SF6 dry air molar fraction vertical profiles over the Pantanal, Mato Grosso do Sul, Brazil with air sampled using small aircraft and analysed at Laboratório de Gases de Efeito Estufa (LAGEE), Sao Jose dos Campos, Brazil.\r\n\r\nThe air was sampled during ascent of small airplane from 4.4 km above surface down to close to the ground. A series of flasks (17 flasks) were filled sequentially. The flasks were contained in a suitcase. Valves of the flasks were opened and closed by a programmable microcontroller. After sampling the suitcase were sent by mail to the high precision gas analytics laboratory LAGEE at Instituto Nacional de Pesquisas Espaciais (INPE), Sao Jose dos Campos, Brazil where the dry air molar fractions of the air of each flask were measured.\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 30544, "uuid": "eeb37252d6924fcda01bbd6f66566055", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Cape Point Observatory Station, South Africa 2011 to 2016", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples at Cape Point, South Africa. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 32182, "uuid": "8c0db6a995214523a38d4e2ef2124781", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Llanos de Moxos, Bolivia", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples at Llanos de Moxos, Bolivia. The samples were analysed by Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nDate of campaign:\r\n-31 Mar 2017, location: -15.024 -64.811, Low to medium forest, with heights up to 7-8 meters, seasonally flooded\r\n-26 May 2017, location: -14.572 -64.869, Open savanah, ocassionally flooded, with palms and scattered trees\r\n-13 July 2017, location: -14.49 -64.86, Open savanah covered by grasses and herbs\r\n-20 Aug 2017, location: -14.49 -64.86, Open savanah covered by grasses and herbs\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 25285, "uuid": "8f1ff8ea77534e08b03983685990a9b0", "short_code": "ob", "title": "Penlee Point Atmospheric Observatory: Meteorological and chemical observations 2014- present", "abstract": "The Penlee Point Atmospheric Observatory (PPAO) was established by the Plymouth Marine Laboratory in May 2014 for long term observations of ocean-atmosphere interaction. The observatory is only a few tens of metres away from the water edge and 11m above mean sea level.\r\n\r\nThis dataset contains air temperature, dew point, wind speed and direction, rainfall, sulphur dioxide, ozone, carbon dioxide and methane measurements from Penlee Point Atmospheric Observatory from 2014-2017.\r\n\r\nAt the mouth of the Plymouth Sound, the site (50° 19.08' N, 4° 11.35' W) is exposed to marine air when the wind comes from 110° - 240°. Typical southwesterly winds tend to bring relatively clean background Atlantic air. In contrast, winds from the southeast are often contaminated by exhaust plumes from passing ships. The PPAO is in close proximity to marine sampling stations that form the Western Channel Observatory, enabling better understanding of the ocean-atmosphere coupling." }, { "ob_id": 30548, "uuid": "79adaf540c7346e8b7b70b66bddeebe6", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Royal Holloway Earth Sciences Monitoring Station, Egham, UK, 2015 to 2020", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples at Royal Holloway Earth Sciences Monitoring Station, UK at Royal Holloway University of London. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 27873, "uuid": "c3b2eb9cc55646539dc9b80c05e897a3", "short_code": "ob", "title": "FAAM C132 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 27832, "uuid": "cb2b7189549149ac9ab7a1a5f282c702", "short_code": "ob", "title": "FAAM C127 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 24778, "uuid": "d308ab44d03749e2a3eea1886d25af90", "short_code": "ob", "title": "FAAM C007 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments: MOYA project." }, { "ob_id": 28006, "uuid": "53ad1a8179e64bb9a2f0da38ad83d2f1", "short_code": "ob", "title": "FAAM C197 MOYA-Arctic flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) (MOYA-Arctic) project." }, { "ob_id": 27877, "uuid": "f87077b2d4004ecaa7ad7c5342ee8297", "short_code": "ob", "title": "FAAM C134 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 30536, "uuid": "c3387fb33fa845f783bfcb5dc3a8d982", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Llanos de Moxos, Bolivia 2019", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples on the Llanos de Moxos wetland near Trinidad, Bolivia. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 28182, "uuid": "1328bfce79de47bca0d9dc90f90ad7c3", "short_code": "ob", "title": "Kjølnes Atmospheric Observatory (KJN): High-precision long-term atmospheric measurements of greenhouse gases (CO, CO2, N2O and CH4) using Off-Axis Integrated-Cavity Output Spectroscopy (OA-ICOS).", "abstract": "This dataset contains high-precision long-term atmospheric measurements of greenhouse gases (CO, CO2, N2O and CH4 ) using Off-Axis Integrated-Cavity Output Spectroscopy (OA-ICOS). The measurements were taken at Kjølnes Atmospheric Observatory (KJN).\r\n\r\nThe Kjølnes Atmospheric Observatory (70°51'07.9\\\"N 29°13'56.3\\\"E) has been operational since August 2013. Two OA-ICOS devices, connected in series and sharing a suite of calibration and reference gases, have been employed to make continuous measurements of atmospheric CO2, CH4, N2O and CO concentrations. The data are calibrated by performing a linear regression upon the weekly measurements of three calibration (tied to the latest NOAA calibration scales) cylinders. The quality control procedure incorporates regular measurements of a dedicated reference cylinder (Target Tank), carefully calibrated at Max-Planck Institute for Biogeochemistry (Germany)." }, { "ob_id": 26916, "uuid": "efa3a90efb5e4a4e961a2f4ddd5dd663", "short_code": "ob", "title": "FAAM C124 MOYA Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 26721, "uuid": "418208c3a0874a4aa2e49bdbc0a32d36", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Alert, Canada", "abstract": "This dataset contains air sample measurements of the ratio between carbon 12: carbon 13 in atmospheric methane (d13C). The air samples measured were taken at Alert, Canada on a regular basis using glass flasks. The samples were analysed for the carbon ratio in methane at Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS). \r\n\r\nThis data was collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 24774, "uuid": "0686929375c846f191e3eeb74f077b60", "short_code": "ob", "title": "FAAM C006 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments: MOYA project." }, { "ob_id": 26720, "uuid": "4ec1af9b0d0845e7b654ff9ca5694113", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Ascension Observatory", "abstract": "This dataset contains air sample measurements of the ratio between carbon 12: carbon 13 in atmospheric methane (d13C). The air samples measured were taken at the Ascension Islands on a regular basis using glass flasks. The samples were analysed for the carbon ratio in methane at Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS). MS). \r\n\r\nThis data was collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 24770, "uuid": "a84e2b504e4e489881321e4838081e5e", "short_code": "ob", "title": "FAAM C005 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments: MOYA project." }, { "ob_id": 27865, "uuid": "880eb12084544affb7d62405a45da7a7", "short_code": "ob", "title": "FAAM C129 MOYA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 32185, "uuid": "371695923931472b8cf415725b12f449", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from Pantanal research station Universidade Federal de Mato Grosso do Sul (UFMS)", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples at Pantanal research station Universidade Federal de Mato Grosso do Sul (UFMS). The samples were analysed by Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 28008, "uuid": "4a33f2d72336498eaa1c977e2a766208", "short_code": "ob", "title": "FAAM C198 MOYA-Arctic flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) (MOYA-Arctic) project." }, { "ob_id": 27998, "uuid": "aa912f341f0c4e4389bcb47d9b9aca26", "short_code": "ob", "title": "FAAM C193 MOYA-Arctic flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) (MOYA-Arctic) project." }, { "ob_id": 27996, "uuid": "aace74ffb762485ca446c6339c626e4d", "short_code": "ob", "title": "FAAM C192 MOYA-Arctic flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) (MOYA-Arctic) project." }, { "ob_id": 30269, "uuid": "7438d170fda7451285742e76900ca0f0", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Isotopic d13C methane measurements taken from at Akrotiri, Cyprus since 2018", "abstract": "This dataset contains air sample measurements of isotopic d13C methane. The measurements were collected using regular flask samples at Akrotiri, Cyprus. The samples were analysed Royal Holloway University of London using continuous flow gas chromatography/isotope ratio mass spectrometry (CF-GC/IRMS).\r\n\r\nThese data were collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 26478, "uuid": "b8ca8754a54845b2959124b48578343e", "short_code": "ob", "title": "FAAM C111 MOYA and SaddleworthMoor flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) and SADDLEWORTHMOOR FAAM Aircraft Project projects." }, { "ob_id": 26969, "uuid": "95857f7d529c4daf97e925289648ce04", "short_code": "ob", "title": "FAAM C126 MOYA flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) project." }, { "ob_id": 28002, "uuid": "23a95403c08c497a9d14b9613345d024", "short_code": "ob", "title": "FAAM C195 MOYA-Arctic flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) (MOYA-Arctic) project." }, { "ob_id": 27548, "uuid": "96a6ad89375a4f9ca68489758f9259da", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Hourly averaged methane measurements taken from Sapper Hill, Falkland Islands Atmospheric Observatory, 2010-2018", "abstract": "This dataset contains hourly averaged methane measurements taken from Sapper Hill, Falkland Islands Atmospheric Observatory from 2010-2018. Sapper Hill, Falkland Islands Atmospheric Observatory was established by the Royal Holloway Greenhouse Gas Research Group in October 2010 and handed to the British Antarctic Survey AIC group in September 2016 for long term observations of atmospheric mixing ratios. The observatory is located on Sapper Hill overlooking Stanley.\r\n\r\nThis data was collected as part of the Methane Observations and Yearly Assessments (MOYA) project funded by the Natural Environment Research Council (NERC) (NE/N016211/1)." }, { "ob_id": 24761, "uuid": "2f3fc65ee69640a79bd1efd6136936ba", "short_code": "ob", "title": "FAAM C003 MOYA Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments: MOYA project." }, { "ob_id": 27994, "uuid": "ccbdc006a543410d883c8dac7264fe34", "short_code": "ob", "title": "FAAM C191 MOYA-Arctic flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) (MOYA-Arctic) project." }, { "ob_id": 27751, "uuid": "e9aee1f49d2d49edbbfa948c32bfd457", "short_code": "ob", "title": "Methane Observations and Yearly Assessments (MOYA): Atmospheric carbon dioxide and methane measurements taken from Bachok Marine Research Station, Malaysia", "abstract": "This dataset contains atmospheric carbon dioxide and methane measurements taken from Bachok Marine Research Station, Malaysia using Los Gatos Research (LGR) Fast Greenhouse Gas Analyser (FGGA) from 2015 to present. LGR FGGA measures trace concentrations of methane (CH4), carbon dioxide (CO2) and water vapor (H2O) simultaneously in flowing gaseous samples (usually air) at rates up to ≥10 Hz.\r\n\r\nBackok Research Station is located on the east coast of Malaysia, within 100 m of the waters' edge of the South China Sea. This facility is part of the Institute of Ocean and Earth Sciences (IOES) at the University of Malaya (UM). An atmospheric observation tower has been built on the windward side of the main building, for the specific purpose of studying long range transported pollution, air sea exchange, and coastal meteorology. \r\n\r\nThe UK participation of the Methane Observations and Yearly Assessments (MOYA) project was funded by the Natural Environment Research Council (NERC, grant: NE/N015584/1)." }, { "ob_id": 12974, "uuid": "e9c9e975601f4ba4ac1756a3c112a8d1", "short_code": "ob", "title": "Weybourne Atmospheric Observatory: Longterm Methane measurements", "abstract": "Longterm Methane(CH4) measurements at the Weybourne Atmospheric Observatory (WAO) using Clarus 500 Greenhouse Gas GC (Perkin Elmer) instrument operated by the NCAS (National Centre for Atmospheric Science) AMF (Atmospheric Measurement Facility). WAO, situated on the north Norfolk coast, is part of the School of Environmental Sciences at the University of East Anglia (UEA) and is a world class facility for fundemental research, background atmospheric monitoring and teaching purposes. WAO operates a range of instruments in its measurement programme - the data from which is archived at the BADC. The atmospheric methane measurements are every 10 minutes. " }, { "ob_id": 24782, "uuid": "ced4bf7ada334db9abf115972d25ecc6", "short_code": "ob", "title": "FAAM C008 MOYA Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments: MOYA project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 101379, 101380, 101381, 101384, 101385, 101386, 101387, 101388, 101382, 101383 ], "onlineresource_set": [], "project_set": [ 24718 ] }, { "ob_id": 24806, "uuid": "d7bb874c638c40e797c3aaa6baffc65f", "short_code": "coll", "title": "Amazonian peatlands: in-situ ground based soil-atmosphere flux measurements", "abstract": "'Amazonian peatlands - A potentially important but poorly characterised source of atmospheric methane and nitrous oxide' was a NERC (Natural Environment Research Council) funded project from 2013-2014 with the following grant reference: NE/I015469/2. \r\n\r\nThis dataset collection contains measurements from field sampling of soil-atmosphere fluxes concentrated on 4 dominant vegetation types in the lowland tropical peatland forests of the Pastaza-Marañón foreland basin. Vegetation types included; forested vegetation, forested [short pole] vegetation, Mauritia flexuosa-dominated palm swamp, and mixed palm swamp. \r\n\r\nGreenhouse gas (GHG) fluxes were captured from both floodplain systems and nutrient-poor bogs in order to account for underlying differences in biogeochemistry that may arise from variations in hydrology. Sampling was conducted during four field campaigns (two wet season, two dry season) over a 27-month period, extending from February 2012 to May 2014.\r\n\r\n", "keywords": "methane, nitrous oxide, peat, tropical peatland, Pastaza-Marañón foreland basin, Amazonia, Peru", "publicationState": "published", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24807, "uuid": "a3614fb00ff74999a5187d3a3767d96d", "short_code": "ob", "title": "Soil-atmosphere flux measurements calculated from concentration of methane and nitrous oxide taken from the Pastaza-Marañón foreland basin, Peru", "abstract": "The research team collected data on soil-atmosphere exchange of trace gases and environmental variables during four field campaigns (two wet seasons, two dry seasons) the lowland tropical peatland forests of the Pastaza-Marañón foreland basin in Peru. The campaigns took place over a 27 month period, extending from February 2012 to May 2014. \r\n\r\nThis dataset contains measurements from field sampling of soil-atmosphere fluxes concentrated on 4 dominant vegetation types in the lowland tropical peatland forests of the Pastaza-Marañón foreland basin. Vegetation types included; forested vegetation, forested [short pole] vegetation, Mauritia flexuosa-dominated palm swamp, and mixed palm swamp. They were measured at 5 different sites in Peru including; Buena Vista, Miraflores, San Jorge, Quistococha, and Charo. \r\n\r\nGreenhouse gas (GHG) fluxes were captured from both floodplain systems and nutrient-poor bogs in order to account for underlying differences in biogeochemistry that may arise from variations in hydrology.\r\n\r\nParameters include methane and nitrous oxide fluxes, air/soil temperatures, soil pH, soil electrical conductivity, soil dissolved oxygen content, and water table depth. \r\n\r\nSee documentation and data lineage for data quality. \r\n\r\nThese data were collected in support of the NERC project: Amazonian peatlands - A potentially important but poorly characterised source of atmospheric methane and nitrous oxide (NE/I015469/2)" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 101541, 101546, 101547, 101548, 101549, 101551, 101552, 101550, 101542, 101543, 101544, 101545 ], "onlineresource_set": [ 23395 ], "project_set": [ 24805 ] }, { "ob_id": 24817, "uuid": "648246d2bdc7460b8159a8f9daee7844", "short_code": "coll", "title": "APHH: Atmospheric measurements and model results for the Atmospheric Pollution & Human Health in a Chinese Megacity", "abstract": "The Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) Programme includes several projects making groundbased observations of meteorology, atmospheric chemical species and particulates in and around the city of Beijing. Due to the close working and exchange between the projects and overlap of instruments, this dataset collection contains measurements and related modelling study output produced by all these projects.", "keywords": "APHH, AIRPRO, INHANCE, AIRPOLL, Beijing, pollution", "publicationState": "published", "dataPublishedTime": "2017-10-18T09:11:32", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 30042, "uuid": "680ebdcb83c244fdb9d069e2f8952812", "short_code": "ob", "title": "APHH: Direct infusion ultra-high resolution mass spectrometry measurements made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains direct infusion ultra-high resolution mass spectrometry measurements made at the Institute of Atmospheric Physics land station, Beijing (IAP-Beijing) site during the summer and winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme.\r\n\r\nDaily quartz microfiber filters were collected with a Tisch high volume sampler. The extracted organic fraction of the collected PM2.5 particles was analysed using an LTQ Orbitrap Velos mass spectrometer with electrospray ionisation to obtain high resolution mass spectra which enable the assignment of molecular formulae to the detected masses.\r\n\r\nFor both seasons, 10 filters were analysed, containing the 5 filters with the highest and lowest mass loadings for each season. The files names are labeled according to the ID of the analysed filter. All dates and times are given in Beijing local time." }, { "ob_id": 24974, "uuid": "0beb36f0313e4d5aa6f8c36aa12cd594", "short_code": "ob", "title": "APHH: O3, CO, NO, NO2, NOy and SO2 measurements made at the IAP-Beijing site during the summer and winter", "abstract": "This dataset contains O3, CO, NO, NO2, NOy and SO2 measurements made at the IAP-Beijing site during the summer and winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme." }, { "ob_id": 26890, "uuid": "33f3b3defe4d4e3194be68b61c2a3b2f", "short_code": "ob", "title": "APHH: Atmospheric dispersion model footprint plots made at the Delhi site during the 2018 campaign", "abstract": "The Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) was used at the University of Leicester to produce atmospheric dispersion footprints centred on Delhi for use by the projects under the Atmospheric Pollution & Human Health in a Developing Megacity (APHH) programme. These footprints are created by model runs in which thousands of particles are released from the chosen location and are tracked backwards in time." }, { "ob_id": 27613, "uuid": "4a1d547929d44698b91e0d75d417220b", "short_code": "ob", "title": "APHH: Simulated photolysis rates using the Fast-JX model at the IAP-Beijing site during the winter and summer campaigns", "abstract": "This dataset contains Simulated Photolysis rates using the Fast-JX model at the IAP-Beijing site during the winter and summer APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme.\r\n\r\nFast-JX column photolysis model was used at Lancaster University to simulate column profiles of photolysis rates (JO3 and JNO2) centred on the Institute of Atmospheric Physics (IAP) tower site in Beijing. The photolysis rate profiles are simulated under different aerosol loadings to represent the optical effects of individual species and cloud cover on photochemistry." }, { "ob_id": 26002, "uuid": "4c2aaf6a80864d70b105e62e3ddbe797", "short_code": "ob", "title": "APHH: Particle number size distribution measurements made at the IAP-Beijing site during the summer campaign", "abstract": "This dataset contains particle number size distribution (PNSD) measurements made at the Institute of Atmospheric Physics land station, Beijing (IAP-Beijing) site during the summer APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. A University of Birmingham Particle Size Magnifier (PSM) and 2 Scanning Mobility Particle Size Spectrometer (SMPS) systems were deployed to measure PNSD from 1.5 to 615 nm.\r\n\r\nThis dataset contains two files. The number file shows the concentration of particles in each size bin, whilst the dN/dlogDp file shows the data as a lognormal function of diameter." }, { "ob_id": 25293, "uuid": "af3ccea589f9439e9e1f88c85d130965", "short_code": "ob", "title": "APHH: Single Particle Soot Photometer measurements made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains single particle soot photometer measurements made at the IAP-Beijing site during the summer and winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme." }, { "ob_id": 27166, "uuid": "df8261bae435459fb1643da0d3da90f0", "short_code": "ob", "title": "APHH: Atmospheric ion concentrations in PM2.5 made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains atmospheric ion concentrations in PM2.5 particles made at the Institute of Atmospheric Physics land station, IAP-Beijing, site using a High Volume Sampler (Ecotech 3000, Australia) and a Dionex ICS-1100 Ion Chromatography System, during the summer and winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme." }, { "ob_id": 25428, "uuid": "22241af0eb934cd7bfb1ae7418ad7c9e", "short_code": "ob", "title": "APHH: Atmospheric nitrous acid (HONO) measurements made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains atmospheric nitrous acid (HONO) measurements made at the IAP-Beijing site during the summer and winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme.\r\n\r\nHONO data was obtained using a commercial (QUMA) Long Path Absorption Photometer (LOPAP) instrument and calibrated using liquid nitrite standards. Data are averaged over 5 mins, the time stamp represents the start time of each averaging period. Missing data are either due to baseline measurements, calibrations or instrument malfunction. They are not retrievable." }, { "ob_id": 25425, "uuid": "de37c54e59a548ccb9f168ee724f3769", "short_code": "ob", "title": "APHH: Volatile organic compound (VOC) mixing ratios made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains volatile organic compound (VOC) mixing ratios recorded during two intensive field campaigns in Beijing (winter: 12/11/2016 - 10/12/2016; and summer: 15/05/2017 - 24/06/2017) as part of the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe species recorded include methanol, acetonitrile, acetaldehyde, acrolein, acetone, isoprene, methyl vinyl ketone and methacrolein, methyl ethyl ketone, benzene, toluene, C2-benzenes, C3-benzenes and monoterpenes. The data were recorded using a proton transfer reaction-time of flight-mass spectrometer (PTR-ToF-MS) from a sampling height of 100m." }, { "ob_id": 26174, "uuid": "bb339ff791814fc6a8b9a93d339f5bc1", "short_code": "ob", "title": "APHH: Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the IAP-Beijing site during the winter and summer campaigns.", "abstract": "This dataset contains Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe measurements were taken using the FAGE (Fluorescence Assay by Gas Expansion) technique which is a LIF (laser induced fluorescence) that measures on-resonance fluorescence at 308 nm. HO2 and RO2 are converted to OH via reaction with NO and NO + CO respectively. \r\n\r\nThe instrument is calibrated by photolysis of known concentration of water vapour at 185 nm to generate know concentrations of OH and HO2, same method used for HO2 but NO is injected into the flow to convert HO2 to OH. RO2 is calibrated by photolysing water vapur at 185 nm to generate OH but CH4 is added to convert OH to CH3O2, then CH3O2 is converted to OH using CO and NO. The calibration was preform every three days on campaign, and from this we can convert counts measured into concentration. The units for OH, HO2 and RO2 and there associated errors is molecules cm-3. The data has been filtered for instabilities in data collection including unstable pressure, unstable online, low laser power and not going online correctly. The data has been flagged for when the values were below limit of detection." }, { "ob_id": 27509, "uuid": "77e44e0d5df14e89ab35c0af1f7cb726", "short_code": "ob", "title": "APHH:Volatile Organic Compound Measurements (VOCs) made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains Volatile Organic Compound (VOCs) measurements made at the Institute of Atmospheric Physics land station, IAP-Beijing, site using the York Gas Chromatograph with Flame Ionisation Detectors (GC-FID) System, during the summer and winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme." }, { "ob_id": 26181, "uuid": "8ed84f3c770544c49329df9b068ab662", "short_code": "ob", "title": "APHH: Laser induced fluorescence (LIF) OH reactivity measurements made at the IAP-Beijing site during the winter and summer campaigns", "abstract": "This dataset contains Laser induced fluorescence (LIF) OH reactivity measurements made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe Leeds OH reactivity instrument measures OH reactivity by photolysing ozone at 266 nm to produce OH, decay of OH with ambient air is measured with LIF (laser induced fluorescence) at 308 nm. The results generate a bi-exponential curve and a line of best fit can be used to calculate OH lifetime. The instrument is calibrated by flowing air zero through the instrument. The units for OH reactivity is in s-1. The data has been filtered for instrument instabilities such as pressure, laser power, high background (laser scatter) and laser alignment" }, { "ob_id": 26183, "uuid": "7b9c3b7d3f554f48b9082bc4dcc9607c", "short_code": "ob", "title": "APHH: Formaldehyde (HCHO) measurements made at the IAP-Beijing site during the winter and summer campaigns", "abstract": "This dataset contains measurements of formaldehyde using laser induced fluorescence (LIF) made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nFormaldehyde concentration measurements in pptv were made using the Leeds Formaldehyde instrument which uses off-resonance laser induced fluorescence at 353 nm to detect ambient formaldehyde. The instrument was calibrated at regular intervals during the campaign using a commercial permatube containing paraformaldehyde." }, { "ob_id": 26923, "uuid": "71229b203b874d79b95b4d0ed0eae931", "short_code": "ob", "title": "APHH: Atmospheric nitrous acid (HONO) combined measurements made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains atmospheric nitrous acid (HONO) combined measurements made at the Institute of Atmospheric Physics land station (IAP-Beijing) site, during the summer and winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme.\r\n\r\nThis combined dataset consists of a single mean time series of HONO mixing ratio (ppb), and associated min/max values determined from the datasets of 4 instruments that measured HONO at IAP at ground level. The data are averaged over 1 hour, the time stamp represents the start time of each averaging period.\r\n\r\nThe instruments included in the combined dataset are the University of Birmingham commercial wet-chemical LOPAP instrument (Heland et al. 2001), Institute of Chemistry, Chinese Academy of Sciences custom built wet-chemical instrument (Tong et al. 2016), and two custom built Broadband Cavity Enhanced Spectrophotmeters (BBCEAS) from the University of Cambridge (Kennedy et al. 2011) and Anhui Institute of Optics and Fine Mechanics (Duan et al. 2018)." }, { "ob_id": 41480, "uuid": "9458b2aea1cf4dd48a7ff810a4197304", "short_code": "ob", "title": "Chamber reaction products identified from toluene/m-xylene oxidation using GCxGC TOFMS at the University of Birmingham", "abstract": "A list of reaction products from the photo-oxidation of m-xylene and toluene in chamber experiments for the Quantitative Attribution of Secondary Organic Aerosol in Beijing to its Precursors project which was part of the Air Pollution and Human Health in Developing Megacities programme.\r\n\r\nA potential aerosol mass (PAM) chamber was used to investigate the oxidised products from the photo-oxidation of m-xylene and toluene. The chamber experiments were carried out with hydroxyl (OH) radical as oxidant in both high- and low-NOx conditions and the resultant aerosol samples were collected using quartz filters and analysed by the two dimensional Gas Chromatography Time-Of-Flight Mass Spectrometry (GC×GC-TOFMS) at the University of Birmingham." }, { "ob_id": 24809, "uuid": "88f3a3de77354692aeada98c5dad599b", "short_code": "ob", "title": "APHH: Atmospheric dispersion model footprint plots made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "The Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) was used at the University of Leicester to produce atmospheric dispersion footprints centred on Beijing for use by the projects under the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. These footprints are created by model runs in which thousands of particles are released from the chosen location and are tracked backwards in time." }, { "ob_id": 26177, "uuid": "76b4ad364d71465d8f8b61e302eb2c4c", "short_code": "ob", "title": "APHH: Solar actinic UV flux photolysis rates made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains direct measurement of solar actinic UV flux from which photolysis frequencies are calculated made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the summer and winter APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nPhotolysis rates were derived from the product of absorption cross-section of the precursor molecule, the quantum yield of the photo-product and the actinic flux density (cm-2s-1nm-1). The actinic flux is measured between 280 - 650 nm (<1 nm resolution) using a spectral radiometer attached to a quartz receiver optic. Absorption cross sections and quantum yields are taken from the latest IUPAC recommendations. The instrument was calibrated between 250 - 750 nm using a spectral Irradiance of Standard Tungsten-Halogen lamp before and after the campaign." }, { "ob_id": 27299, "uuid": "60d5d5e095024831a6f45e4febe4a95e", "short_code": "ob", "title": "APHH: Meteorology and atmospheric chemistry measurements made at the Xibaidian, Beijing site during the summer and winter campaigns.", "abstract": "This dataset contains wind speed and direction, air temperature, relative humidity, barometric pressure, nitric oxide, nitric dioxide, nitric oxides, sulphur dioxide, carbon dioxide, ozone and pm2.5 based on a newly built-up rural site at Xibaidian, Pinggu district, Beijing in winter 2016 and summer 2017. The data were taken for the APHH-Beijing campaign for the Effects of air pollutions on cardiopulmonary disease in urban and peri-urban residents in Beijing (AIRLESS) project as part of the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme.\r\n\r\nInstruments were deployed on the roof of a one-story building in the far north end of a village, where most of the subjects resided nearby. Northern winds tend to bring relatively clean background air. In contrast, winds from the south are often contaminated by emissions from traffic and industries. \r\n\r\nThe following instruments were used:\r\n1. Meteorological parameter: TH16A meteorological station\r\n2. NOx: TEI 42 trace level chemiluminescence NOx Analyzer;\r\n3. SO2: Ecotech EC9850 Sulfur Dioxide Analyzer\r\n4. CO: Ecotech EC9830 Carbon Monoxide Analyzer\r\n5. O3: Ecotech EC9810 Ozone Analyzer\r\n6. PM2.5: Met One BAM 1020\r\n\r\nThe dataset was collected in Xibaidian, Pinggu district, Beijing for the Effects of air pollutions on cardiopulmonary disease in urban and peri-urban residents in Beijing (AIRLESS) project can provide ambient level of air pollutant in rural Beijing, enabling better understanding of the exposure level for local residents and potential examination for the related health effects." }, { "ob_id": 30250, "uuid": "9e11d5cb819a45068921db5ae296fb57", "short_code": "ob", "title": "APHH: Volatile organic compound (VOC) flux measurements made during the APHH-Beijing field campaigns 11-12/2016 and 05-06/2017", "abstract": "This dataset contains volatile organic compound (VOC) fluxes recorded during two intensive field campaigns in Beijing (winter: 12/11/2016 - 10/12/2016; and summer: 15/05/2017 - 24/06/2017) as part of the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme.\r\n\r\nVOC concentrations were recorded using the GIG: Proton Transfer Reaction-Time of Flight- Mass Spectrometer (PTR-ToF-MS). Measurements were made at 102 m on the Institute of Atmospheric Physics (IAP) meteorological mast. Fluxes were processed by Lancaster University." }, { "ob_id": 25984, "uuid": "b9d6fc06b827470783e518e65799384c", "short_code": "ob", "title": "APHH: Chemical composition measurements of PM2.5 particles made at the IAP-Beijing site during the winter campaign", "abstract": "This dataset contains chemical composition measurements of PM2.5 particles made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nDaily fine particles were collected on the PTFE (Polytetrafluoroethylene) filters using the Partisol samplers. The filters were then analysed for metals using X-ray fluorescence (XRF) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and for ion species using Ion Chromatography. Quartz filters were collected by Tisch high vol, samplers and then were analysed for organic and elemental carbons using the DRI Model 2015 Multiwavelength Thermal/Optical Carbon Analyser, and organic tracers using Gas chromatography–mass spectrometry (GC-MS)." } ], "identifier_set": [ 9306 ], "responsiblepartyinfo_set": [ 102254, 102256, 102257, 102258, 102260, 102261, 102262, 102259, 102255, 103624, 105669, 105670, 105671, 105672, 105685, 105686, 109530, 109531, 109568, 109569 ], "onlineresource_set": [ 23700 ], "project_set": [ 24808, 41476 ] }, { "ob_id": 24918, "uuid": "2d0118fccc86444f9bdb87d2dfce4a52", "short_code": "coll", "title": "Poles Apart: Why has Antarctic sea ice increased and why don't coupled climate models reproduce observations", "abstract": "Datasets collected as part of the NERC project Poles Apart Why has Antarctic sea ice increased and why don't coupled climate models reproduce observations? (NE/K012150/1, NE/K011561/1). \r\n\r\nThe aim of this project was to model atmospheric drivers of changes in surface wind forcing. The project began in June 2014 and completed at the end of June 2017.", "keywords": "Climate, Ozone, GHG, Aerosol, HadGEM3, UKCA", "publicationState": "published", "dataPublishedTime": "2017-08-07T09:22:11", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24914, "uuid": "acf1f55cd92a41fa9a97949b2066ad07", "short_code": "ob", "title": "Poles Apart: Why has Antarctic sea ice increased and why don't coupled climate models reproduce observations, climate model data", "abstract": "Data produced in support of the NERC project Poles Apart (2014 - 2017) that investigated the atmospheric drivers of changes in surface wind forcing using the UK Chemistry and Aerosols (UKCA) model. \r\n\r\nTen HadGEM3 model simulations were undertaken. Monthly model data was taken from the final 30 years of each simulation and a number of variables of interest, e.g. temperature and precipitation were extracted and analysed. \r\n\r\nThe temporal range for the perturbed simulations is 1980-2013, and the control simulations are valid between 1841-1900.\r\n\r\nSee the detailed experiment documentation for the Unified Model experiment ids and their corresponding description (these have been used to organise the data)." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 101977, 101975, 101974, 101973, 101972, 101971, 105385, 101976, 101979, 101978, 169542 ], "onlineresource_set": [ 23605 ], "project_set": [ 24917 ] }, { "ob_id": 24950, "uuid": "39cc5db2889348f888b824520316e9d2", "short_code": "coll", "title": "Measurements of N2O5, ClNO2, HCOOH, HNO3 and HCN at the Weybourne Atmospheric Observatory", "abstract": "Chemical ionisation mass spectrometer (CIMS) measurements of N2O5, ClNO2 and other halogenated species to understand the overall oxidation budget at the Weybourne Atmospheric Observatory rural marine site.\r\n", "keywords": "CIMS, BBCEAS, Weybourne, N2O5, ClNO2, HCOOH, HNO3, HCN", "publicationState": "published", "dataPublishedTime": "2017-09-12T10:42:58", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 15442, "uuid": "931c93034f4f4384865a377d6c2cd50d", "short_code": "ob", "title": "FAAM B822 Instrument Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument)." }, { "ob_id": 24947, "uuid": "8b965a24e74e46dcadb63611327f1e29", "short_code": "ob", "title": "Measurements of N2O5, ClNO2, HCOOH, HNO3 and HCN at the Weybourne Atmospheric Observatory", "abstract": "Chemical ionisation mass spectrometer (CIMS) measurements of N2O5, ClNO2 and other halogenated species to understand the overall oxidation budget at the Weybourne Atmospheric Observatory rural marine site.\r\n\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 102134, 102135, 102136, 102138, 102139, 102140, 102141, 105437, 102137, 102142, 102143, 102144 ], "onlineresource_set": [], "project_set": [ 24949 ] }, { "ob_id": 24959, "uuid": "b1f266c25cf2445f8b87d874f6ac830a", "short_code": "coll", "title": "BITMAP: Tracks of western disturbances (1979-2015)", "abstract": "Western disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This collection contains a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) produced from various model outputs. This work was undertaken as part of the NERC funded BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon and Poles) project. \r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award: NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. \r\n\r\nTracks of these WDs were generated using a bespoke tracking algorithm within the project applied to data from the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-Interim reanalysis data and model output from various experiments of the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (WCRP CMIP5). The algorithm, described in Hunt et al, 2017, QJRMS (see linked documentation), identified and linked upper-tropospheric vortices from the data and are available within this dataset collection. Additional details of the CMIP5 tracking algorithm are available in the Hunt et al. paper 'Representation of western disturbances in CMIP5 models' paper (see linked documentation). The principal difference between the algorithm used for the ERA-Interim data and the CMIP5 data is the choice of pressure levels on which the algorithm was run: 500 hPa for the ERA-Interim data and 450-300 hPa layer for the CMIP5 data.", "keywords": "BITMAP, India, Western disturbances, Vortices", "publicationState": "published", "dataPublishedTime": "2019-02-05T12:21:35", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24958, "uuid": "233cf64c54e946e0bb691a07970ec245", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting over Pakistan and north India in ERA-Interim reanalysis data (1979-2015)", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation), using data derived from the ERA-Interim reanalysis data. Similar datasets were produced using various model output from the WCRP CMIP5 programme, available within the parent dataset collection.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 450-300 hPa. This differs from those tracks from the CMIP5 data which were carried out on the 500 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, { "ob_id": 27182, "uuid": "f2ab8c5fb8da40cf96d32ac3739149ca", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 Historical experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). This utilised data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'Historical' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, { "ob_id": 27673, "uuid": "3a49f746dcdb4ff98e17919c84acbd20", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 midHolocene experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). The dataset was produced utilising data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'mid-Holocene' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical', 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nThe mid-Holocene period were designed to simulate the climate 6000 years ago, thus the representative date range for these data is circa 4025-4000 BC. Not all available CMIP5 mid-Holocene experiments were chosen for this dataset as the algorithm required 6-hourly output fields which were not available for all runs.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, { "ob_id": 27399, "uuid": "08ad495a1cf048d3b2fc3ffa376de47c", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 RCP85 experiment", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). This utilised data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'RCP85' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical' and 'RCP45' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, { "ob_id": 27397, "uuid": "2703d5a46d22430d887043b2715dae5a", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 RCP45 experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). This utilised data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'RCP45' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 102195, 102196, 102197, 102199, 102200, 102201, 102202, 102203, 102198, 102204, 111520, 111521 ], "onlineresource_set": [ 25423, 26521 ], "project_set": [ 24956 ] }, { "ob_id": 24981, "uuid": "bffd0262439a4ecb8fadf0134c4a4a41", "short_code": "coll", "title": "GloCAEM: Atmospheric electric potential gradient measurements", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset collection contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill.", "keywords": "GloCAEM, GEC, electric potential, electric field", "publicationState": "published", "dataPublishedTime": "2017-09-08T10:38:38", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25018, "uuid": "70f822f9d1734418a9ced14715c7bc8d", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Bristol Langford", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Bristol Langford." }, { "ob_id": 24992, "uuid": "942bc9cb12f04e1d8bfee06c9dae7d39", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Alentejo Evora, Portugal", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Alentejo Evora." }, { "ob_id": 24988, "uuid": "1df9c15fb1c14ef28ee99d5195e1c388", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Graciosa Azores, Portugal", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Graciosa Azores." }, { "ob_id": 25003, "uuid": "2ce214dd45b94730861593757ad80912", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Negev Mitzpe_Ramon, Israel", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Negev Mitzpe_Ramon." }, { "ob_id": 25039, "uuid": "d17164eb534846dcb00c3b76e8156246", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Syowa Station (10m pole), East Ongul Island, Antarctica", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek EFM 100 Instrument mounted on a 10m pole and operated by the National Institute of Polar Research and Japan Meteorological Agency at Syowa Station, East Ongul Island, Antarctica." }, { "ob_id": 25852, "uuid": "3c62cd14b63d468582e8fc00ee446595", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Halley Station, Brunt Ice Shelf, Antarctica", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a JCI Chilworth 131 at Halley Station, Brunt Ice Shelf, Antarctica." }, { "ob_id": 20072, "uuid": "3451b0d7a2f2439d8f1926041ddf8b4c", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at University of Reading", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at the University of Reading." }, { "ob_id": 25842, "uuid": "934690a393a34c6f92f3a31143713f3e", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Complejo Astronómico El Leoncito, San Juan, Argentina", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek field meter at Complejo Astronómico El Leoncito, San Juan, Argentina." }, { "ob_id": 25009, "uuid": "7a897f7dbdd547beb2ebe4a1564b036e", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Mazowieckie Otwock Swider, Poland", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Mazowieckie Otwock Swider." }, { "ob_id": 26493, "uuid": "7b55fe21e239471595057f7711e02b3b", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Nor-Amberd Research Station", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek EFM-100 Electric Field Monitor at Nor-Amberd Research Station." }, { "ob_id": 39784, "uuid": "360cf83cf2354ae88c45ad8e37a2766b", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Kakioka Magnetic Observatory, Japan (low sensitivity)", "abstract": "This dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek EFM 100 Instrument mounted at 0.6 m height on a metal pole and operated by the University of Shizuoka and Japan Meteorological Agency at Kakioka Magnetic Observatory, Ishioka-shi, Ibaraki-ken, Japan\r\n\r\nThe provided data were calibrated using long-term observation of water dropper data (Nagamachi et al, Geosci. Data J., 2021).The low sensitivity instrument dataset provided through GLOCAEM have a resolution of 65.9 V/m and the measurement range is from -131.8 kV/m to +131.8 kV /m. GPS-synchronized data with higher resolution (6.59 V/m) and with high sampling (10 Hz), all-sky camera images (10 min. sampling), animal camera images (motion detection) and are also available through on-demand request (kamogawa@u-shizuoka-ken.ac.jp).\r\n\r\nGlobal Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1." }, { "ob_id": 24982, "uuid": "809c75d66e5f47f7b55c5542bf26dad9", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Aragats Research Station, Armenia", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Aragats Research Station, Armenia." }, { "ob_id": 25419, "uuid": "072418297ba548b58a710f3d2692b23c", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Tripura University, India", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a EFM-100 Atmospheric Electric Field Monitor at Tripura University, India." }, { "ob_id": 39552, "uuid": "338774c1a9f34ce287f4cef9eb7bcdee", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Universidad Nacional San Luis Gonzaga, Ica, Peru", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek field meter at Universidad Nacional San Luis Gonzaga, Ica, Peru." }, { "ob_id": 25006, "uuid": "42fc3caa6d74469ab63c063558ff7a14", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Karlovy Vary Studenec, Czech Republic", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Karlovy Vary Studenec." }, { "ob_id": 24996, "uuid": "5db074ddfc7945e9813b4308f8a03420", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Nagycenk MTA CSFK GGI Szechenyi Istvan Geophysical Observatory, Hungary", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Nagycenk MTA CSFK GGI Szechenyi Istvan Geophysical Observatory." }, { "ob_id": 24026, "uuid": "5ddcbed44a0748b0bc84c03fbfb10a91", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Mt Hermon, Israel", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Mt Hermon." }, { "ob_id": 39786, "uuid": "5e5b96c9d37344f9850d874378927065", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Kakioka Magnetic Observatory, Japan (high sensitivity)", "abstract": "This dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek EFM 100 Instrument mounted at 0.6 m height on a metal pole and operated by the University of Shizuoka and Japan Meteorological Agency at Kakioka Magnetic Observatory, Ishioka-shi, Ibaraki-ken, Japan\r\n\r\nThe provided data was calibrated using long-term observation of water dropper data (Nagamachi et al, Geosci. Data J., 2021). The resolution of the high sensitivity data provided through GLOCAEM is 1.9 V/m and the measurement range is from -3.8 kV/m to +3.8 kV/m. GPS-synchronized data with higher resolution (0.19 V/m) and with high sampling (10 Hz), all-sky camera images (10 min. sampling), animal camera images (motion detection) and are also available through on-demand request (kamogawa@u-shizuoka-ken.ac.jp).\r\n\r\nGlobal Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1." }, { "ob_id": 24999, "uuid": "60781584324e472a81f52b8b244cbf66", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Liberec Duba Panska Ves, Czech Republic", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Liberec Duba Panska Ves." }, { "ob_id": 25015, "uuid": "9b9f646f43ae430e9f4a5d2ef1a13bd0", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Bristol Science Centre", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Bristol." }, { "ob_id": 39234, "uuid": "a1166f1c71b4402a8948daa5c3bd8aa4", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Syowa Station (1.4m pole), East Ongul Island, Antarctica", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek EFM 100 Instrument mounted at 1.4 m height on a metal pole and operated by the National Institute of Polar Research and Japan Meteorological Agency at Syowa Station, East Ongul Island, Antarctica." }, { "ob_id": 25012, "uuid": "63b6800e62e64233a487c018a346e08e", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Thrace Xanthi, Greece", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at Thrace Xanthi." }, { "ob_id": 25847, "uuid": "b998d216b95b40828d18b754da46532b", "short_code": "ob", "title": "GloCAEM: Atmospheric electricity measurements at Paraíba State University, Campina Grande, Paraiba, Brazil", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek field meter at Paraíba State University, Campina Grande, Paraiba, Brazil." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 102278, 102280, 102281, 102282, 102284, 102285, 102286, 102283, 102279, 102287, 102319, 102366, 102367, 102379, 102415, 102416, 102430, 102442, 108000, 108001, 108002, 108003, 193811, 193810, 108004 ], "onlineresource_set": [ 24396 ], "project_set": [ 20068 ] }, { "ob_id": 25021, "uuid": "18c737a986094b1abd19cfebc9d0c374", "short_code": "coll", "title": "The Organization of Tropical Rainfall: MetUM model data and observed convective aggregation data for the Tropics", "abstract": "This project was funded by the Natural Environment Research Council (NERC) with the grant reference - NE/I021012/1 - and was led by Dr Christopher Holloway (University of Reading). \r\n\r\nThis dataset collection contains MetUM model data and observed convective aggregation data for the Tropics.\r\n\r\nThis project aimed to clearly identify processes important for self-aggregation of convection in idealized models and then to test whether these processes, or different processes, are active in convective organization in nature. The second part of this goal was an open question in the field, and this fellowship has the potential to connect a rapidly expanding theoretical research area with ongoing efforts to improve the understanding and prediction of tropical variability. The focus on the Unified Model benefited weather and climate prediction in the UK by exchanging ideas with Met Office scientists who were directly involved in testing and improving the model. \r\n", "keywords": "Tropical, rainfall, clouds, MJO", "publicationState": "published", "dataPublishedTime": "2018-06-14T13:30:49", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25022, "uuid": "f3f8337c838c4602876d43f56d878515", "short_code": "ob", "title": "The Organization of Tropical Rainfall: Observed convective aggregation data across the Tropics", "abstract": "This dataset contains about 5 years of analysed observations regarding the degree of convective aggregation, or clumping, across the tropics - these are averaged onto a large-scale grid. There are also additional variables which represent environmental fields (e.g. sea surface temperature from satellite data, or humidity profiles averaged from reanalysis data) averaged onto the same large-scale grid. The main aggregation index is the Simple Convective Aggregation Index (SCAI) originally defined in Tobin et al. 2012, Journal of Climate. The data were created during the main years of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data so that they could be compared with vertical cloud profiles from this satellite data, and the results of this analysis appear in Stein et al. 2017, Journal of Climate.\r\n\r\nEach file is one year of data (although the year may not be complete).\r\n\r\nEach variable is an array: var(nlon, nlat, [nlev], ntime)\r\nlongitude, latitude, pressure, time are variables in each file\r\nunits are attributes of each variable (except non-dimensional ones)\r\nmissing_value is 3.0E20 and is an attribute of each variable\r\n\r\nTime is in days since 19790101:00Z and is every 3hours at 00z, 03z, ... \r\nThe actual temporal frequency of the data is described for each variable below.\r\n\r\nThe data is for each 10deg X 10deg lat/lon box, 30S-30N (at outer edges of box domain), with each box defined by its centre coordinates and with boxes overlapping each other by 5deg in each direction.\r\n\r\nIn general, each variable is a spatial average over each box, with the value set to missing if more than 15% of the box is missing data.\r\nExceptions to this are given below.\r\nThe most important exception is for the brightness temperature data, used in aggregation statistics, which is filled in using neighborhood averaging if no more than 5% of the pixels are missing, but otherwise is considered to be all missing data. The percentage of missing pixels is recorded in 'bt_miss_frac'.\r\n\r\n" }, { "ob_id": 25031, "uuid": "7838d170275d460887b3043de0c71679", "short_code": "ob", "title": "The Organization of Tropical Rainfall: Realistic MetUM model output for convective aggregation studies", "abstract": "This dataset comprises of model output from 25 runs (5 case studies, with 5 runs in each case study) of the Met Office Unified Model (MetUM) in realistic limited-area one-way nesting mode. The output data include values for model fields (e.g. temperature, humidity, winds, pressure) at model grid points over regularly spaced time intervals. These runs were used in a paper on convective aggregation: Holloway (2017, Journal of Advances in Modeling Earth Systems). \r\n\r\nAll runs use the \"\"New Dynamics\"\" dynamical core, MetUM version 7.5, as described in Holloway (2017). The simulations are run with 4-km horizontal grid spacing. They all have a horizontal domain size of 20 degrees latitude X 20 degrees longitude (or 574 X 574 grid points, although the grid points in the outer 8 points on all sides, the \"\"rim\"\", should be discarded before analysis), with 70 vertical levels. All runs are initialised from operational analyses from the European Centre for Medium-Range Weather Forecasting (ECMWF) taken from actual cases. Lateral boundary conditions are comprised of 6-hourly ECMWF analyses, and the model is relaxed to these conditions in and near the outer rim as described in Holloway (2017). Sea surface temperatures (SST) are taken from the initial ECMWF analysis and are held constant in time for the 15 days (but are not constant in space). There are small land regions in four of the case studies which include an interactive land surface model.\r\n\r\nEach simulation was run for 15 days. The model output includes hourly model-level prognostic variables (temperature, specific humidity, pressure, wind components, liquid water, ice water) as well as some model-level increments to temperature and specific humidity. There are also many fields containing surface variables and fluxes (averaged over each hour or every 15 minutes). Note that the \"\"control\"\" simulations have slightly more available data than the other four runs in each of the five case studies.\r\n\r\nThe five case studies are centred on the equator and occur between 2008 and 2010. See Holloway (2017) for further details:\r\nhttp://onlinelibrary.wiley.com/doi/10.1002/2017MS000980/full \r\n\r\n\r\nFor each case, there are five runs:\r\n1) control (interactive radiation, interactive surface fluxes)\r\n2) constant radiative cooling run (radiative cooling over sea points is prescribed from domain-time mean of control run)\r\n3) constant surface flux run (surface latent and sensible heat fluxes over sea points are prescribed from domain-time mean of control run)\r\n4) constant radiative cooling and constant surface flux run (combination of 2 and 3 above)\r\n5) no rain evaporation run (rain is prevented from evaporating in the atmosphere)\"\r\n" }, { "ob_id": 25029, "uuid": "2499ca660bc448f281ff1a1de1d20970", "short_code": "ob", "title": "The Organization of Tropical Rainfall: Idealised MetUM model output for convective aggregation studies", "abstract": "This dataset comprises of model output from 11 runs of the Met Office Unified Model (MetUM) in idealised radiative-convective equilibrium mode. All runs have fixed constant sea surface temperature (SST) and doubly-periodic lateral boundary conditions. These runs were used in several papers on convective self-aggregation: principally in Holloway and Woolnough (2016, Journal of Advances in Modeling Earth Systems) but also in Holloway (2017, Journal of Advances in Modeling Earth Systems).\r\n\r\nAll runs use the \"New Dynamics\" dynamical core, MetUM version 7.5, as described in Holloway and Woolnough (2016). The simulations are run with 4-km horizontal grid spacing. They all have a horizontal domain size of 576 km X 576 km (or 144 X 144 grid points), with 70 vertical levels. They were all run for 40 days except for the two runs with lower Sea Surface Temperatures, SSTs (295 K and 290 K) which were run for only 20 days.\r\n\r\nThe model output includes hourly model-level prognostic variables (temperature, specific humidity, pressure, wind components, liquid water, ice water) as well as some model-level increments to temperature and specific humidity. There are also many fields containing surface variables and fluxes (averaged over each hour or every 15 minutes).\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 102459, 102460, 102461, 102462, 102463, 102465, 102466, 102467, 102464 ], "onlineresource_set": [], "project_set": [ 12144 ] }, { "ob_id": 25033, "uuid": "53e6cf2cbb52457987466f049c734f43", "short_code": "coll", "title": "ACID-PRUF: Measurements of freezing fraction of water solution droplets solute and suspended matter during the immersion freezing of pollen extracts", "abstract": "ACID-PRUF was a three year NERC directed programme that investigated the complex interaction of aerosols and clouds. The overall aims of ACID-PRUF were to reduce the uncertainty in the radiative forcing associated with the aerosol indirect effects though a targeted laboratory and modelling programme. \r\n\r\nThis dataset collection contains measurements of freezing fraction of water solution droplets-solute and suspended matter during the immersion freezing of pollen extracts (birch pollen, Betula fontinalis occidentalis, Sigma-Aldrich, P6895-1G), with a new cold electrodynamic balance (CEDB). ", "keywords": "ACID-PRUF, pollen, aerosols, clouds", "publicationState": "published", "dataPublishedTime": "2017-09-06T12:46:21", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25036, "uuid": "131174cdad804dd1a51e79d7dbd1d2b0", "short_code": "ob", "title": "ACID-PRUF: Measurements of freezing fraction of water solution droplets solute and suspended matter during the immersion freezing of pollen extracts", "abstract": "ACID-PRUF was a three year NERC directed programme that investigated the complex interaction of aerosols and clouds. The overall aims of ACID-PRUF were to reduce the uncertainty in the radiative forcing associated with the aerosol indirect effects though a targeted laboratory and modelling programme. \r\n\r\nThis dataset collection contains measurements of freezing fraction of water solution droplets-solute and suspended matter during the immersion freezing of pollen extracts (birch pollen, Betula fontinalis occidentalis, Sigma-Aldrich, P6895-1G), with a new cold electrodynamic balance (CEDB)." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 102509, 102513, 102514, 102515, 102516, 102518, 102519, 102520, 102517, 102510, 102511, 102512 ], "onlineresource_set": [ 23722 ], "project_set": [ 11986 ] }, { "ob_id": 25062, "uuid": "dafbd838e4cc4c68a5ccdd90690ea57f", "short_code": "coll", "title": "SPARC Reanalysis Intercomparison Project (S-RIP): Zonal-mean global atmospheric reanalyses on pressure levels", "abstract": "SPARC (Stratosphere–troposphere Processes And their Role in Climate) is an international activity started in 2013 (under the World Climate Research Programme, WCRP) to compare and evaluate all available global atmospheric reanalyses in the middle atmosphere; publish several journal papers and the WCRP/SPARC reports.\r\n\r\nThis dataset collection provides zonal-mean diagnostics computed from reanalysis data sets on pressure levels. It is divided into two components. The first provides dynamical variables like temperature, geopotential height, and wind field and derived diagnostics such as eddy fluxes and a complete budget of zonal momentum. The second provides heating rates. In both components, data is provided on two grids. The first provides the diagnostics on the same grid on which reanalysis data was obtained. The second provides, using horizontal interpolation, the diagnostics on a common grid for all data sets. All diagnostics are provided as a function of latitude and pressure from 1958 to present, depending on each reanalysis' availability.\r\n\r\nThis data set was produced to facilitate the comparison of reanalysis data sets for the collaborators of the SPARC-Reanalysis Intercomparison Project (S-RIP). The data set is substantially smaller in size compared to the full three-dimensional reanalysis fields and uses standardized numerical methods. The data set includes all global reanalyses available at the time of its development and will be extended to include new reanalysis products in the future.", "keywords": "SPARC, S-RIP, WCRP", "publicationState": "published", "dataPublishedTime": "2017-11-28T16:33:26", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 208 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25384, "uuid": "70146c789eda4296a3c3ab6706931d56", "short_code": "ob", "title": "S-RIP: Zonal-mean heating rates of global atmospheric reanalyses on pressure levels", "abstract": "This dataset contains zonal-mean model-generated and diagnosed heating rates as potential temperature tendencies on pressure levels. The model-generated heating rates consist of total heating rates due to parameterized physics along with heating rates due to long-wave and short-wave radiative transfer, as generated during the model forecast step. The diagnosed heating rates are calculated from the zonal-mean atmospheric diagnostics (Zonal-mean reanalyses on pressure levels dataset) according to the zonal-mean thermodynamic equation. All heating rates are provided 6-hourly on identical horizontal and vertical grids as the dynamical variables included in Zonal-mean reanalyses on pressure levels dataset. However, the time axis of this dataset lags that of Zonal-mean reanalyses on pressure levels dataset by three hours.\r\n\r\nThis dataset was produced to facilitate the comparison of reanalysis datasets for the collaborators of the SPARC- Reanalysis Intercomparison Project (S-RIP). The dataset is substantially smaller in size compared to the full three dimensional reanalysis fields and uses unified numerical methods. The dataset includes all global reanalyses available at the time of its development and will be extended to new reanalysis products in the future." }, { "ob_id": 25059, "uuid": "b241a7f536a244749662360bd7839312", "short_code": "ob", "title": "S-RIP: Zonal-mean dynamical variables of global atmospheric reanalyses on pressure levels", "abstract": "This dataset contains zonal-mean atmospheric diagnostics computed from reanalysis datasets on pressure levels. Primary variables include temperature, geopotential height, and the three-dimensional wind field. Advanced diagnostics include zonal covariance terms that can be used to compute, for instance, eddy kinetic energy and eddy fluxes. Terms from the primitive zonal-mean momentum equation and the transformed Eulerian momentum equation are also provided.\r\n\r\nThis dataset was produced to facilitate the comparison of reanalysis datasets for the collaborators of the SPARC- Reanalysis Intercomparison Project (S-RIP) project. The dataset is substantially smaller in size compared to the full three dimensional reanalysis fields and uses unified numerical methods. The dataset includes all global reanalyses available at the time of its development and will be extended to new reanalysis products in the future." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 102668, 102669, 102670, 102671, 102672, 102674, 102675, 102676, 102673, 104763 ], "onlineresource_set": [ 23775, 24423 ], "project_set": [ 25061 ] }, { "ob_id": 25087, "uuid": "55c74c02ec8e4afea309043d110a93e7", "short_code": "coll", "title": "Auchencorth Moss Atmospheric Observatory (AU) and associated field sites: Meteorological observations", "abstract": "The Auchencorth Moss Atmospheric Observatory was setup in 1995 to measure meteorology, trace gases, aerosols and their fluxes. It is (55ᵒ47’36” N, 3°14’41” W) an ombrotrophic peatland with an extensive fetch at an elevation of 270 m, lying 18 km SSW of Edinburgh, UK, and can be categorised as a transitional lowland raised bog. The site is grazed with < 1 sheep ha^-1.\r\n\r\nDuring 2000s the site activity has increased and was established in 2006 as EMEP (European Monitoring and Evaluation Program, Level 2/3) supersite for the UK. Long term monitoring is led by NERC CEH with contributions from other organisations/research institutes including Ricardo AEA, BureauVeritas, NPL, the University of Birmingham and University of Edinburgh. In April 2014 the site was awarded WMO GAW regional station (World Meteorological Orgamisation Global Atmospheric Watch). In 2017 the site joined the ICOS network (Integrated Carbon Observation System).\r\nSimilar measurements are also made at nearby Easter Bush Field site by the same team.\r\n\r\nThe meteorological measurements were initially made to assist with interpretation of the fluxes and as such weren't installed with the intention of providing WMO standard measurements.", "keywords": "Auchencorth Moss, Meteorology, Temperature, Rainfall, Wind Speed", "publicationState": "published", "dataPublishedTime": "2020-01-21T16:10:10", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 132 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25086, "uuid": "8e6cbb111cfd41a19c92aadcb2d040fd", "short_code": "ob", "title": "Auchencorth Moss Atmospheric Observatory (AU): Annual half-hourly meteorology since 1995, Near Edinburgh, UK - Version 1", "abstract": "The site was setup in 1995 to measure meteorology, trace gases, aerosols and their fluxes. It is (55ᵒ47’36” N, 3°14’41” W) an ombrotrophic peatland with an extensive fetch at an elevation of 270 m, lying 18 km SSW of Edinburgh, and can be categorised as a transitional lowland raised bog. The site is grazed with < 1 sheep ha^-1.\r\n\r\nDuring 2000s the site activity has increased and was established in 2006 as EMEP (European Monitoring and Evaluation Program, Level 2/3) supersite for the UK. Long term monitoring is led by NERC CEH with contributions from other organisations/research institutes including Ricardo AEA, BureauVeritas, NPL, the University of Birmingham and University of Edinburgh. In April 2014 the site was awarded WMO GAW regional station (World Meteorological Orgamisation Global Atmospheric Watch). In 2017 the site joined the ICOS network (Integrated Carbon Observation System).\r\n\r\nThe meteorological measurements were initially made to assist with interpretation of the fluxes and as such weren't installed with the intention of providing WMO standard measurements but since 2014 we have been moving towards these standards as well as enhancing instrumentation.\r\n\r\nThe dataset includes the following parameters at half hourly intervals, although not every variable is available from 1995 to 2016:\r\n-T_upper_Avg - initially used to estimate senisble heat fluxes, fine wire type-E thermocouple.\r\n-T_lower_Avg - initially used to estimate senisble heat fluxes, fine wire type-E thermocouple.\r\n-T_RHT_Avg - Temperature measured by a Vailsala relative humidity and temperature probe.\r\n-RH_RHT_Avg - Relative humidity measured by a Vailsala relative humidity and temperature probe.\r\n-P_Avg - atmospheric pressure at the sites elevation.\r\n-Tot_Solar_Avg - Total solar radiation measured by a Skye SKS1110.\r\n-PAR_Avg - Photosynthetically Averaged Radiation measured by a Skye SKP215.\r\n-NetRad_Avg - Net radiation, Kipp & Zonen NrLite.\r\n-Rainfall - tipping bucket rainfall.\r\n-SoilTavg - Average soil temperature from four type-E thermocouple probes.\r\n-Soil Heat Flux - calculated from two measurements of soil heat flux with Hukseflux HFP01 plates, corrected to surface flux using the standard formula.\r\n-Cs = Bd(Cd+fSWC.Cw)\r\n-SC = DTs.Cs.d/Dtime\r\n-SHF = Plate Average + SC\r\n-DTs = change in average soil temperature from start to end of measurement period (first and last two minutes); d = plate depth 0.2 m; Bd = soil bulk density, 100 kg m-3; cd = Specific Heat Dry Soil, 840J kg-1 K-1; fSWC = fractional soil water content, measured or 0.9; cw = Specific Capacilty Heat of Water, 4190 J kg-1 K-1; Dtime = measurement period, 1800 s\r\n-Soil Moisture - soil water content measured with TDR probes, campbell CS616\r\n-WindSpd (measured) - measured by a Gill R3 then Windmaster sonic anemometer at 3.6 m\r\n-WindSpd 10 m - for most of the time period this is estimated from the turbulence measurements and 3.6 m windspeed but from 22/06/2016 a Gill Windsonic 2D anemeometer measures at 10 m\r\n-Wind Dir - measured by the sonic anemometer at 3.6 m\r\n-snow_depth_Avg - Campbell Scientific SR50A-L Sonic Ranging Sensor\r\n-Present Weather - Vaisala FD12P Present Weather Sensor\r\n-1 hr Past Weather - Vaisala FD12P Present Weather Sensor\r\n-Visibility - Vaisala FD12P Present Weather Sensor\r\n-Evaporation - to be estimated from the water-vapout flux measurements\r\n\r\nFor modelling purposes gapfilled (variables with _gf suffixes) times series will be included, they are created by linearly initially interpolating across upto an hours missing data, filling with colocated measurements (adjusted by linear interpolation with the core data), filling with measurements from nearby sites (adjusted by linear interpolation with the core data).\r\nTa_gf\r\nP_gf\r\nRH_gf\r\nTotal_Solar_gf\r\nRainfall_gf\r\nWindspd 10m_gf\r\nWind Dir_gf" }, { "ob_id": 30611, "uuid": "f9a0eaf6cfb8479f89a62ecbc091ec7d", "short_code": "ob", "title": "Auchencorth Moss Atmospheric Observatory (AU): Hourly averaged 4-pi filter radiometer measurements (21/11/2018 - 20/11/2019) near Edinburgh (UK)", "abstract": "This dataset contains hourly averaged 4-pi filter radiometer measurements of the rate constant of NO2 photolysis, j(JNO2) from both downwelling radiation (direct and diffuse radiation from the above atmosphere) and upwelling (diffuse radiation from the atmosphere below). Data are reported in s^-1.\r\n\r\nMeasurements made at Auchencorth Moss (55ᵒ47’36” N, 3°14’41” W), for more information see http://www.auchencorth.ceh.ac.uk/. The instrument was situated in a clear section of the site, 3 m above ground level. The surface cover consisted of long grasses (~15 cm), often covered by frost/snow in the winter months (December - February). Data were collected between 2018/11/21 12:00 - 2019/11/20 23:00, using a j(NO2) 4-pi filter radiometer manufactured by Meteorologie Consult GmbH (MetCon) measuring broadband actinic flux between ~310-420 nm. The instrument was operated and data were collected by staff at the UK Centre for Ecology & Hydrology. Most of the missing data are between 2019/06/13-25, due to the instrument being relocated for calibration. Other incidences of missing data occur due to power cuts at the site and problems with the data collection. This data comprises the start of a long-term time series of filter radiometer measurements at Auchencorth Moss, in order to provide data access to evaluate j-values in current radiation models and parameterisations.\r\n\r\nThe ongoing operation of the j(NO2) filter radiometer is supported by the UK Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability." }, { "ob_id": 38735, "uuid": "bbacc355f70343739e61c6675ac60c22", "short_code": "ob", "title": "Easter Bush field site - Annual half-hourly meteorology measurements since 2001, near Edinburgh, UK", "abstract": "Annual half-hourly meteorology observations from a compilation of main sonic anemometer (Gill Windmaster), secondary sonic (Metek USA-1) and wind vane sensors (Vector Instruments) made at the CEH (Centre for Ecology and Hydrology) Easter Bush field site near Edinburgh, UK since 2001.\r\n\r\nEaster Bush is located in South East Scotland, 10 km south of Edinburgh (03deg02W, 55deg52N, 190 m above sea level). The fields have been under permanent grassland management for more than 20 years with a species composition of >99% perennial ryegrass (Lolium perenne) and < 0.5% clover (Trifolium repens). The soil type is an imperfectly drained Eutric Cambisol (FAO classification) with a pH of 5.1 (in H2O), a clay fraction of 20-26% (Clayey Loam to Sandy Loam) and a soil organic carbon content of 4% (0-10 cm depth). The grassland is grazed by cows, ewes and lambs at different stocking densities and has been cut for silage in some years. The instrumentation sits on the boundary between two fields, labelled north and south, although the fenceline runs down from the NW to SE." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 102789, 102794, 102795, 102796, 102797, 102800, 102801, 102802, 102798, 102790, 102791, 102792, 102793 ], "onlineresource_set": [ 23784 ], "project_set": [ 25088 ] }, { "ob_id": 25092, "uuid": "4b873c1918854f55b11ac0e5398aaa63", "short_code": "coll", "title": "Model data described in the 2013 IPCC Fifth Assessment Report (AR5), 20 and 30 year climatologies", "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013). The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013). Twenty- and thirty-year climatologies and climatological anomalies are calculated for experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85 produced by 39 models from 22 modelling centres. The monthly climatology data covers the period from 1850-2100. The climatologies are of global scope and are provided on latitude-longitude grids.", "keywords": "IPCC, DDC, AR5, CMIP5, Climatologies, piControl, 1pctCO2, historical, scenarios, rcp26, rcp45, rcp60, rcp85", "publicationState": "published", "dataPublishedTime": "2018-05-22T13:02:35", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 195 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25099, "uuid": "d269d748cafe40ec8601125caf5cb2fa", "short_code": "ob", "title": "CMIP5 20-Year AR5 Climatology Data for the IPCC DDC", "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013). The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013). Twenty-year AR5 climatologies and climatological anomalies are calculated for the averaging periods 2016-2035, 2046-2065, 2081-2100 for the CMIP5 scenario experiments rcp26, rcp45, rcp60 and rcp85. The climatologies are of global scope and are provided on latitude-longitude grids." }, { "ob_id": 25102, "uuid": "ed9a2b24c8944d2f8f2d6c1e86bbe130", "short_code": "ob", "title": "CMIP5 30-Year Climatology Data for the IPCC DDC", "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013). The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013). Thirty-year climatologies and climatological anomalies are calculated for the CMIP5 experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85. The monthly climatology data covers the period from 1850-2100. The climatologies are of global scope and are provided on latitude-longitude grids." }, { "ob_id": 25101, "uuid": "6cf411099aa743ef81de0f96dd80bac0", "short_code": "ob", "title": "CMIP5 20-Year Climatology Data for the IPCC DDC", "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013). The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013). Twenty-year climatologies and climatological anomalies are calculated for the CMIP5 experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85. The monthly climatology data covers the period from 1850-2100. The climatologies are of global scope and are provided on latitude-longitude grids." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 102807, 102808, 102809, 102810, 102811, 102813, 102814, 102815, 102812, 111733, 111734 ], "onlineresource_set": [ 23786, 25467 ], "project_set": [ 26579 ] }, { "ob_id": 25095, "uuid": "f37c34b82fc545c39e0c8a77d51c7688", "short_code": "coll", "title": "CMIP5 20-Year Climatology Data for the IPCC DDC", "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections, have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013). The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013). Twenty-year climatologies and climatological anomalies are calculated for experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85 produced by 39 models from 22 modelling centres.", "keywords": "IPCC, AR5, CMIP5, Climatologies, piControl, 1pctCO2, historical, scenarios, rcp26, rcp45, rcp60, rcp85", "publicationState": "working", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 196 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 102824, 102825, 102826, 102828, 102829, 102830, 102831, 102832, 102827 ], "onlineresource_set": [ 23788 ], "project_set": [] }, { "ob_id": 25096, "uuid": "6ca383b092004b89b6a0efce730f77db", "short_code": "coll", "title": "CMIP5 30-Year Climatology Data for the IPCC DDC", "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections, have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013). The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013). Thirty-year climatologies and climatological anomalies are calculated for experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85 produced by 39 models from 22 modelling centres.", "keywords": "IPCC, AR5, CMIP5, Climatologies, piControl, 1pctCO2, historical, scenarios, rcp26, rcp45, rcp60, rcp85", "publicationState": "working", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 196 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 102833, 102834, 102835, 102836, 102837, 102839, 102840, 102841, 102838 ], "onlineresource_set": [ 23789 ], "project_set": [] }, { "ob_id": 25097, "uuid": "ba82ae756c304bc396fc42439cca9608", "short_code": "coll", "title": "CMIP5 20-Year AR5 Climatology Data for the IPCC DDC", "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections, have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013). The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013). Twenty-year AR5 climatologies and climatological anomalies are calculated for experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85 produced by 39 models from 22 modelling centres.", "keywords": "IPCC, AR5, CMIP5, Climatologies, piControl, 1pctCO2, historical, scenarios, rcp26, rcp45, rcp60, rcp85", "publicationState": "working", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 196 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 102842, 102843, 102844, 102846, 102847, 102848, 102849, 102850, 102845 ], "onlineresource_set": [ 23790 ], "project_set": [] }, { "ob_id": 25119, "uuid": "38ab7089781a4560b067dd6c20af3769", "short_code": "coll", "title": "CLARIFY: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for CLouds and Aerosol Radiative Impacts and Forcing: CLARIFY", "keywords": "CLARIFY, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2017-08-03T12:15:43", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25197, "uuid": "84733df1c77146bfa1960f62784cc7fb", "short_code": "ob", "title": "FAAM C044 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25201, "uuid": "c69bc12637d749c5829964c47e11de7c", "short_code": "ob", "title": "FAAM C043 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite 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data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25261, "uuid": "90d6674e656a4d5e9c0e26b980238d17", "short_code": "ob", "title": "FAAM C054 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25157, "uuid": "748c2522980545e98173f8698bc1638a", "short_code": "ob", "title": "FAAM C027 CLARIFY Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25213, "uuid": "e462461ee82348f5a5e76bfee481baed", "short_code": "ob", "title": "FAAM C039 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25118, "uuid": "82461824b52f4c42a8e2cf09cdd9902e", "short_code": "ob", "title": "FAAM C026 CLARIFY Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25185, "uuid": "6e3feb82b8ec4462ad0fd575352935b4", "short_code": "ob", "title": "FAAM C047 CLARIFY flight: Airborne atmospheric 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data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25233, "uuid": "b2c463fd4bbd492fb7fac4e15a40e2ac", "short_code": "ob", "title": "FAAM C034 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25165, "uuid": "694b36760cc64f359b1fa73640797321", "short_code": "ob", "title": "FAAM C052 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25205, "uuid": "8920cc7e28d84326809cffadaf6adce7", "short_code": "ob", "title": "FAAM C055 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25193, "uuid": "446dcc005a284cce9e9bcd417f3708bd", "short_code": "ob", "title": "FAAM C045 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25173, "uuid": "fbe8796145f74102bcb98351c763b46a", "short_code": "ob", "title": "FAAM C050 CLARIFY flight: Airborne atmospheric 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"ob_id": 25453, "uuid": "9d0141ea84bd45efa6139c85cb76bab1", "short_code": "ob", "title": "FAAM C040 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25245, "uuid": "a070273597ab45619bbc4241d722bf61", "short_code": "ob", "title": "FAAM C031 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25217, "uuid": "63f693dea2f347e095dd27c12dfd0e8f", "short_code": "ob", "title": "FAAM C038 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25457, "uuid": "c777576b9a314f34998bfe96c106f8e1", "short_code": "ob", "title": "FAAM C041 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25257, "uuid": "172a5a6f29ac4b4e85470e7a7f6e3287", "short_code": "ob", "title": "FAAM C028 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." }, { "ob_id": 25169, "uuid": "665ba5cb2a064126890c8a0094a9547b", "short_code": "ob", "title": "FAAM C051 CLARIFY flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for CLouds and Aerosol Radiative Impacts and Forcing: Year 2016 (CLARIFY-2016) project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 103006, 103007, 103008, 103011, 103012, 103013, 103014, 103015, 103009, 103010 ], "onlineresource_set": [], "project_set": [ 12132 ] }, { "ob_id": 25287, "uuid": "61409a5455cc4913a43da496768d0f67", "short_code": "coll", "title": "Penlee Point Atmospheric Observatory: Meteorological and chemical observations 2014-2017", "abstract": "The Penlee Point Atmospheric Observatory (PPAO) was established by the Plymouth Marine Laboratory in May 2014 for long term observations of ocean-atmosphere interaction. The observatory is only a few tens of metres away from the water edge and 11m above mean sea level.\r\n\r\nThis dataset collection contains air temperature, dew point, wind speed and direction, rainfall, sulphur dioxide, ozone, carbon dioxide and methane measurements from Penlee Point Atmospheric Observatory from 2014-2017.\r\n\r\nAt the mouth of the Plymouth Sound, the site (50° 19.08' N, 4° 11.35' W) is exposed to marine air when the wind comes from 110° - 240°. Typical southwesterly winds tend to bring relatively clean background Atlantic air. In contrast, winds from the southeast are often contaminated by exhaust plumes from passing ships. The PPAO is in close proximity to marine sampling stations that form the Western Channel Observatory, enabling better understanding of the ocean-atmosphere coupling.", "keywords": "Penlee, Atmospheric, Meteorology, Pollution, Chemistry, Ozone, Sulphur Dioxide, Carbon Dioxide, Rainfall, Wind, Methane", "publicationState": "published", "dataPublishedTime": "2017-10-18T09:41:30", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25285, "uuid": "8f1ff8ea77534e08b03983685990a9b0", "short_code": "ob", "title": "Penlee Point Atmospheric Observatory: Meteorological and chemical observations 2014- present", "abstract": "The Penlee Point Atmospheric Observatory (PPAO) was established by the Plymouth Marine Laboratory in May 2014 for long term observations of ocean-atmosphere interaction. The observatory is only a few tens of metres away from the water edge and 11m above mean sea level.\r\n\r\nThis dataset contains air temperature, dew point, wind speed and direction, rainfall, sulphur dioxide, ozone, carbon dioxide and methane measurements from Penlee Point Atmospheric Observatory from 2014-2017.\r\n\r\nAt the mouth of the Plymouth Sound, the site (50° 19.08' N, 4° 11.35' W) is exposed to marine air when the wind comes from 110° - 240°. Typical southwesterly winds tend to bring relatively clean background Atlantic air. In contrast, winds from the southeast are often contaminated by exhaust plumes from passing ships. The PPAO is in close proximity to marine sampling stations that form the Western Channel Observatory, enabling better understanding of the ocean-atmosphere coupling." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 103597, 103598, 103599, 103600, 103601, 103603, 103604, 103605, 103602, 103614 ], "onlineresource_set": [ 23926, 23927 ], "project_set": [ 25288 ] }, { "ob_id": 25297, "uuid": "0eaca59831bf411f8334afc0a0b64bda", "short_code": "coll", "title": "WCRP CCMI-1: The CNRM-CERFACS team MOCAGE model output", "abstract": "WCRP CCMI-1: The CNRM-CERFACS team MOCAGE model output.\r\n\r\nThe WCRP Chemistry Climate Model Initiative phase 1 (CCMI-1), is a global chemistry climate model intercomparison project, coordinated by the University of Reading on behalf of the World Climate Research Program (WCRP).\r\n\r\nThe CNRM-CERFACS team consisted of the following agencies: Centre National de Recherches Meteorologiques (CNRM) and Centre Européen de Recherche et Formation Avancées en Calcul Scientifique (CERFACS).", "keywords": "CCMI-1, WCRP, climate change, chemistry, CNRM-CERFACS, MOCAGE", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 171 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 103634, 103635, 103636, 103637, 103638, 103640, 103641, 103639, 103642, 103643, 103644 ], "onlineresource_set": [], "project_set": [ 25296 ] }, { "ob_id": 25298, "uuid": "f677360cd9714323a58ee2efa2f14b33", "short_code": "coll", "title": "WCRP CCMI-1: The CNRM-CERFACS team CNRM-CM5-3 model output", "abstract": "WCRP CCMI-1: The CNRM-CERFACS team CNRM-CM5-3 model output.\r\n\r\nThe WCRP Chemistry Climate Model Initiative phase 1 (CCMI-1), is a global chemistry climate model intercomparison project, coordinated by the University of Reading on behalf of the World Climate Research Program (WCRP).\r\n\r\nThe CNRM-CERFACS team consisted of the following agencies: Centre National de Recherches Meteorologiques (CNRM) and Centre Européen de Recherche et Formation Avancées en Calcul Scientifique (CERFACS).", "keywords": "CCMI-1, WCRP, climate change, chemistry, CNRM-CERFACS, CNRM-CM5-3", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 171 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 103647, 103645, 103646, 103648, 103649, 103650, 103652, 103651, 103653, 103654, 103655 ], "onlineresource_set": [], "project_set": [ 25296 ] }, { "ob_id": 25327, "uuid": "a8ef5ff945f14205b1716fedae239b0e", "short_code": "coll", "title": "WCRP CCMI-1: Goddard Space Flight Center (GSFC) GEOSCCM model output", "abstract": "WCRP CCMI-1: Goddard Space Flight Center (GSFC) GEOSCCM model output.\r\n\r\nThe WCRP Chemistry Climate Model Initiative phase 1 (CCMI-1), is a global chemistry climate model intercomparison project, coordinated by the University of Reading on behalf of the World Climate Research Program (WCRP).", "keywords": "CCMI-1, WCRP, climate change, chemistry, GSFC, GEOSCCM", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 128 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 103810, 103811, 103812, 103814, 103815, 103816, 103817, 103813, 103818 ], "onlineresource_set": [], "project_set": [ 25328 ] }, { "ob_id": 25335, "uuid": "a67013c3683d42a4a54be000c78a38e9", "short_code": "coll", "title": "PREcipitation STructures over Orography (PRESTO): Unified model simulation data", "abstract": "This dataset contains the input data (initial conditions, boundary conditions, initial perturbations) for Met Office Unified Model simulations performed during the PRESTO (PREcipitation STructures over Orography) project. It also contains the 2D and 3D output files from these simulations.\r\n\r\nThe PRESTO project was funded by the Natural Environment Research Council (NERC) with the grant references - NE/I024984/1 and NE/I026545/1 - led by Professor Suzanne Gray (University of Reading) and Professor David Schultz (University of Manchester).\r\n\r\nPRESTO provided a leap forward in the understanding and prediction of quasi-stationary orographic convection in the UK and beyond. This was achieved through an intensive climatological analysis over several regions of the globe where continuous radar data was available, which identified the environmental conditions that support the bands and their characteristic locations and morphologies. Complementary high-resolution numerical simulations pinpointed the underlying mechanisms behind the bands and their predictability in numerical weather prediction models. This work provides positive impacts for the forecasting community, general public, and other academics in the field. Forecasters benefit from the identification of simple diagnostics that can be used operationally to predict these events based on available model forecasts and/or upstream soundings. A series of activities were used to directly engage with forecasters to effectively disseminate our findings. The public benefit from this improved forecasting of potentially hazardous precipitation events. The academic community benefit from the advanced physical understanding (which was disseminated through conferences, workshops, and peer-reviewed publications) and the numerous international collaborations associated with this project.", "keywords": "PRESTO, UKV, Unified Model, Convection, Orography", "publicationState": "published", "dataPublishedTime": "2019-05-09T12:57:14", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25334, "uuid": "791be4212fd84472996f4d66474f3bb1", "short_code": "ob", "title": "PRESTO: Unified model simulation data", "abstract": "This dataset contains the input data (initial conditions, boundary conditions, initial perturbations) for Met Office Unified Model simulations performed during the PRESTO (PREcipitation STructures over Orography) project. It also contains the 2D and 3D output files from these simulations.\r\n\r\nThe PRESTO project was funded by the Natural Environment Research Council (NERC) with the grant references - NE/I024984/1 and NE/I026545/1 - led by Professor Suzanne Gray (University of Reading) and Professor David Schultz (University of Manchester). \r\n\r\nPRESTO provided a leap forward in the understanding and prediction of quasi-stationary orographic convection in the UK and beyond. This was achieved through an intensive climatological analysis over several regions of the globe where continuous radar data was available, which identified the environmental conditions that support the bands and their characteristic locations and morphologies. Complementary high-resolution numerical simulations pinpointed the underlying mechanisms behind the bands and their predictability in numerical weather prediction models. This work provides positive impacts for the forecasting community, general public, and other academics in the field. Forecasters benefit from the identification of simple diagnostics that can be used operationally to predict these events based on available model forecasts and/or upstream soundings. A series of activities were used to directly engage with forecasters to effectively disseminate our findings. The public benefit from this improved forecasting of potentially hazardous precipitation events. The academic community benefit from the advanced physical understanding (which was disseminated through conferences, workshops, and peer-reviewed publications) and the numerous international collaborations associated with this project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 103853, 103855, 103856, 103857, 103859, 103860, 103861, 103854, 103858, 103852 ], "onlineresource_set": [], "project_set": [ 12140 ] }, { "ob_id": 25346, "uuid": "26b7ccf9c2954e2f87c0bce1ba680b65", "short_code": "coll", "title": "BT Tower: O3 and NOx measurements", "abstract": "The BT Tower is a 190-m-tall telecommunications tower situated in central London, UK (51°31′17.4″N, 0°8′20.04″W). Mean building height is 8.8 ± 3.0 m within 1−10 km of the tower and 5.6 ± 1.8 m for suburban London beyond this.\r\n\r\nThis dataset collection contains O3 and NOx measurements made at the BT tower (T35 level) sampled from a height of approx 180 metres above the ground. The measurements were made using a TEI 49i analyser and TEI 42CTL analyser.", "keywords": "NCAS, BT tower, O3, NOx", "publicationState": "published", "dataPublishedTime": "2021-07-26T13:30:42", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 13 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25345, "uuid": "322d59be9b544a1d8f4beddc1acf244c", "short_code": "ob", "title": "BT Tower: O3 and NOx measurements", "abstract": "This dataset contains O3 and NOx measurements made at the BT tower, London (T35 level), sampled from a height of approx 180 metres above the ground. The measurements were made using a TEI 49i analyser and TEI 42CTL analyser. This dataset is part of longterm measurements at the BT tower for the National Centre for Atmospheric Science (NCAS)" }, { "ob_id": 3936, "uuid": "fe2960d53ceff07c5f8924e7bf339697", "short_code": "ob", "title": "ClearfLo: Atmospheric Chemistry measurements and NAME Airmass Footprint dispersion models output at BT Tower, London", "abstract": "ClearfLo (Clean Air for London) Project was a collaborative scientific project involving several academic institutions in the UK, which aimed to set up air pollution monitoring sites alongside meteorological measurements to investigate boundary layer pollution across London.\r\n\r\nThis dataset contains NAME airmass footprint images and measurements of ammonia, carbon dioxide, methane, carbon monoxide, nitrogen, nitrogen oxide and ozone at the BT-Tower, London." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 103937, 103938, 103939, 103940, 103941, 103943, 103944, 103945, 103942 ], "onlineresource_set": [ 23939 ], "project_set": [ 25347 ] }, { "ob_id": 25356, "uuid": "bea6b6bf17494ea3a0726740f5081095", "short_code": "coll", "title": "Assessment of ClNO2 as a missing oxidant in the UK atmosphere", "abstract": "This dataset collection contains ambient concentrations of ClNO2, Cl2, NO3, N2O5, NOx, CO and photolysis rates at the Penlee Point Atmospheric Observatory (UK), University of Leicester campus and Weybourne Atmospheric Observatory (WAO)\r\n\r\nThis project explores by way of concerted measurements and modelling whether, in the UK context, ClNO2 can release large concentrations of reactive chlorine (Cl) into the troposphere. The chemistry could be especially important for the United Kingdom as the UK is surrounded by the ocean, which provides a continuous source of sea-salt in the coastal areas and further inland. In addition, emissions from coal-fired power stations, spread of grit on roads during winter and usage of chlorinated compounds in swimming pools, sewage and water treatment plants, can provide significant sources of non sea-salt Cl. \r\n\r\nThe overall objective of this project was to assess the importance of ClNO2 as a chlorine activation pathway and its presence as a strong chlorine source that could affect the composition and oxidative capacity of the atmosphere, with a particular focus on the UK.", "keywords": "CINO2, troposphere, chemistry, climate", "publicationState": "published", "dataPublishedTime": "2018-01-09T12:09:37", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25359, "uuid": "6f77525671514a3ea7ac964e09631710", "short_code": "ob", "title": "Ambient concentrations of ClNO2, Cl2, NO3, N2O5, aerosol composition and photolysis rates at Leicester (UK)", "abstract": "This dataset contains ambient concentrations of ClNO2, Cl2, NO3, N2O5, aerosol composition and photolysis rates at Leicester (UK)" }, { "ob_id": 25361, "uuid": "7061e9b0e29d43769cc6e097a73e90c8", "short_code": "ob", "title": "Ambient concentrations of ClNO2, Cl2, NO3, N2O5, NO2, aerosol composition and photolysis rates at the Weybourne Atmospheric Observatory (UK)", "abstract": "This dataset contains ambient concentrations of ClNO2, Cl2, NO3, N2O5, NO2, aerosol composition and photolysis rates at the Weybourne Atmospheric Observatory (UK)" }, { "ob_id": 25355, "uuid": "563a5a9f6c3844a28dbdc1dd96e91717", "short_code": "ob", "title": "Ambient concentrations of ClNO2, Cl2, NO3, N2O5, NOx, CO and photolysis rates at the Penlee Point Atmospheric Observatory (UK)", "abstract": "This dataset contains ambient concentrations of ClNO2, Cl2, NO3, N2O5, NOx, CO and photolysis rates at the Penlee Point Atmospheric Observatory (UK)" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 103991, 103992, 103993, 103995, 103996, 103997, 103998, 103990, 103994, 103999, 104000 ], "onlineresource_set": [], "project_set": [ 12130 ] }, { "ob_id": 25390, "uuid": "9c334fbe6d424a708cf3c4cf0c6a53f5", "short_code": "coll", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 3.1 Data", "abstract": "This collection contains version 3.1 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI). The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided.\r\n\r\nThis dataset collection refers to the Version 3.1 data products held in the CEDA archive covering the period 1997-2016. Links to the individual datasets that make up this collection are given in the record below. \r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available.", "keywords": "ESA, Ocean Colour, CCI, ECV", "publicationState": "citable", "dataPublishedTime": "2018-06-14T11:07:49", "doiPublishedTime": "2018-07-04T14:25:34", "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25363, "uuid": "584d4028633a4b7e9fa36da72dbd91c7", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a sinusoidal projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 inherent optical properties (IOP) product (in mg/m3) on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the IOP data are also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25377, "uuid": "159649796f2943689a836999016188f0", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 3.1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25370, "uuid": "edaa7e7324e849f683d3726088a0c7bd", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a geographic projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 inherent optical properties (IOP) product (in mg/m3) on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, this the IOP data is also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25379, "uuid": "915d2340b178494f987a6942e263a2eb", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a sinusoidal projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the chlorophyll-a data are also included in the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25373, "uuid": "806b30b9dc7f44e6bd56a46d8bccf279", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a geographic projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25368, "uuid": "12d6f4bdabe144d7836b0807e65aa0e2", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a geographic projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 chlorophyll-a product (in mg/m3) on a geographic projection at 4 km spatial resolution and at number of time resolutions (daily, 5day, 8day and monthly composites). Note, this chlor_a data is also included in the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25375, "uuid": "b64b1a0ad7874fb39791e99c57b944bc", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a sinusoidal projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Remote Sensing Reflectance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25371, "uuid": "52266ccfbc3348a8afc27b67d6bbc6c2", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 3.1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25381, "uuid": "55c20c0cb35b4a7c8ef8b65694fe46e2", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a sinusoidal projection (All Products), Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 3.1 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). \r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25366, "uuid": "97aebb95404a4bde8405e9cf7e32b9f8", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a geographic projection (All Products), Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 3.1 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Data are also available as monthly climatologies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } ], "identifier_set": [ 9625 ], "responsiblepartyinfo_set": [ 105462, 105463, 105464, 105465, 109657, 105467, 204870, 204871, 105469, 105470, 105477, 105481, 105472, 105479, 105484, 105487, 105468, 105474, 105482, 105488, 105475, 105493, 105485, 105489, 105483, 105476, 105490, 105491, 105492, 105486, 105480, 105478, 105496, 105497, 105498, 105499, 105500, 105501, 105502, 105503, 105494, 105504, 105505, 105506, 105507, 105520, 105521, 105508, 105509, 105510, 105511, 105512, 105513, 105514, 105515, 105516, 105517, 105518, 105519, 105522, 105523, 105524, 105525, 105526, 105527, 105528, 105495, 105529, 105530, 105531, 105532, 105533 ], "onlineresource_set": [ 24004, 24003, 24002, 89153, 89154, 89155, 89156, 89157, 89158, 89159, 89160, 89161, 89162, 89163, 89164, 89165, 89166, 89167, 89168, 87348, 87349, 87350, 87351, 87352, 87353, 87354, 87355, 87356, 87357, 87358, 87359, 87608, 24001 ], "project_set": [ 13365 ] }, { "ob_id": 25442, "uuid": "1654ca5d1eb64564bc683b8505fea1db", "short_code": "coll", "title": "RS4forestEBV-A - Airborne remote sensing for monitoring essential biodiversity variables in forest ecosystems-A", "abstract": "This dataset collection contains the hyperspectral, lidar and photographic data collected by the NERC-\r\nAirborne Research Facility (ARF) on board the British Antarctic Survey (BAS) Twin-Otter aircraft over Bavaria, Germany for the EUFAR funded RS4forestEBV-A project.", "keywords": "EUFAR, ARF", "publicationState": "published", "dataPublishedTime": "2018-01-08T16:33:16", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 105731, 105729, 105724, 105728, 105726, 105725, 105727, 105723, 105730 ], "onlineresource_set": [], "project_set": [] }, { "ob_id": 25443, "uuid": "dc6402a6499047f893b0d1f6bbb482fc", "short_code": "coll", "title": "RS4forestEBV-A - Airborne remote sensing for monitoring essential biodiversity variables in forest ecosystems-A", "abstract": "This dataset collection contains the hyperspectral, lidar and photographic data collected by the NERC-\r\nAirborne Research Facility (ARF) on board the British Antarctic Survey (BAS) Twin-Otter aircraft over Bavaria, Germany for the EUFAR funded RS4forestEBV-A project.", "keywords": "EUFAR, ARF", "publicationState": "published", "dataPublishedTime": "2018-01-08T16:33:16", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 97 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 105740, 105738, 105733, 105737, 105735, 105734, 105736, 105732, 105739 ], "onlineresource_set": [], "project_set": [] }, { "ob_id": 25551, "uuid": "fe1fd79b09294a9d9854a21686fa79ac", "short_code": "coll", "title": "GB12_04: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf GB12_04 project.", "keywords": "GB12_04, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 106928, 106929, 106930, 106931, 106932, 106933, 106934, 106935 ], "onlineresource_set": [], "project_set": [ 25546 ] }, { "ob_id": 25565, "uuid": "abb40f2a226a4f0f9835d81ccfd60c71", "short_code": "coll", "title": "GB12_06: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf GB12_06 project.", "keywords": "GB12_06, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 106976, 106977, 106978, 106979, 106980, 106981, 106982, 106983 ], "onlineresource_set": [], "project_set": [ 25560 ] }, { "ob_id": 25583, "uuid": "a01da5e4e01b45409d50b298575bece0", "short_code": "coll", "title": "GB12_07: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf GB12_07 project.", "keywords": "GB12_07, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107036, 107037, 107038, 107039, 107040, 107041, 107042, 107043 ], "onlineresource_set": [], "project_set": [ 25578 ] }, { "ob_id": 25593, "uuid": "fd57c95424024c05aaea3e9f2248f19a", "short_code": "coll", "title": "RG12_10: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf RG12_10 project.", "keywords": "RG12_10, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [ { "ob_id": 25824, "uuid": "24c097cf77474644a4b3b17286abcd91", "short_code": "ob", "title": "ARSF Flight 2012_250 - for RG12_10: Hyperspectral Remote Sensing Measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ARSF RG12_10 project (flight reference: 2012_250).\r\n\r\nData were collected over the Bedford, UK area.\r\n" }, { "ob_id": 25818, "uuid": "c1bd61f95443402d8b34a91eeea903e5", "short_code": "ob", "title": "ARSF Flight 2012_208 - for RG12_10: Hyperspectral Remote Sensing Measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ARSF RG12_10 project (flight reference: 2012_208).\r\n\r\nData were collected over the Milton Keynes, UK area.\r\n" }, { "ob_id": 25821, "uuid": "5732da3b616843b19db7ff69598abf2c", "short_code": "ob", "title": "ARSF Flight 2012_249 - for RG12_10: Hyperspectral Remote Sensing Measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Hawk, ARSF Specim AISA Eagle and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ARSF RG12_10 project (flight reference: 2012_249).\r\n\r\nData were collected over the Luton, UK area.\r\n" }, { "ob_id": 25815, "uuid": "66513a25354543be9ea7587344cbb87a", "short_code": "ob", "title": "ARSF Flight 2012_206b - For RG12_10: Hyperspectral Remote Sensing Measurements", "abstract": "Hyperspectral remote sensing measurements using the ARSF Optech Airborne Laser Terrain Mapper 3033 LIDAR, ARSF Specim AISA Eagle, ARSF Specim AISA Hawk and ARSF Rollei Digital Camera instruments onboard the NERC ARSF Dornier Do228-101 D-CALM Aircraft for the ARSF RG12_10 project (flight reference: 2012_206b).\r\n\r\nData were collected over the Milton Keynes, UK area.\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 107072, 107073, 107074, 107075, 107076, 107077, 107078, 107079 ], "onlineresource_set": [], "project_set": [ 25588 ] }, { "ob_id": 25611, "uuid": "e421206ecb8545b98d0e1e2c5ac9a879", "short_code": "coll", "title": "GB12_05: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf GB12_05 project.", "keywords": "GB12_05, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107132, 107133, 107134, 107135, 107136, 107137, 107138, 107139 ], "onlineresource_set": [], "project_set": [ 25606 ] }, { "ob_id": 25621, "uuid": "804358d4bdd04b20abe4a96c311c7cae", "short_code": "coll", "title": "ET12_18: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf ET12_18 project.", "keywords": "ET12_18, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107168, 107169, 107170, 107171, 107172, 107173, 107174, 107175 ], "onlineresource_set": [], "project_set": [ 25616 ] }, { "ob_id": 25631, "uuid": "0906225b32c548bfac81a57e2864dc52", "short_code": "coll", "title": "EU09_06: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf EU09_06 project.", "keywords": "EU09_06, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107208, 107209, 107210, 107211, 107204, 107205, 107206, 107207 ], "onlineresource_set": [], "project_set": [ 25626 ] }, { "ob_id": 25637, "uuid": "3ac13a50a4434e4cb22fc3d658f766ca", "short_code": "coll", "title": "EM10_02: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf EM10_02 project.", "keywords": "EM10_02, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107228, 107229, 107230, 107231, 107232, 107233, 107234, 107235 ], "onlineresource_set": [], "project_set": [ 25632 ] }, { "ob_id": 25647, "uuid": "808b64d611f8433a8d1596e56bd24605", "short_code": "coll", "title": "EU12_12: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf EU12_12 project.", "keywords": "EU12_12, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107264, 107265, 107266, 107267, 107268, 107269, 107270, 107271 ], "onlineresource_set": [], "project_set": [ 25642 ] }, { "ob_id": 25657, "uuid": "fe32f53885ec477ca22bc89f0c00a644", "short_code": "coll", "title": "ET12_17: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf ET12_17 project.", "keywords": "ET12_17, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107300, 107301, 107302, 107303, 107304, 107305, 107306, 107307 ], "onlineresource_set": [], "project_set": [ 25652 ] }, { "ob_id": 25667, "uuid": "40aa864c206349c48ce3e4647dc60bd7", "short_code": "coll", "title": "BGS12_01: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf BGS12_01 project.", "keywords": "BGS12_01, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107336, 107337, 107338, 107339, 107340, 107341, 107342, 107343 ], "onlineresource_set": [], "project_set": [ 25662 ] }, { "ob_id": 25677, "uuid": "eba168b4359745a5942df069cebdfc35", "short_code": "coll", "title": "ET12_14: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf ET12_14 project.", "keywords": "ET12_14, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107372, 107373, 107374, 107375, 107376, 107377, 107378, 107379 ], "onlineresource_set": [], "project_set": [ 25672 ] }, { "ob_id": 25683, "uuid": "7874ed4d5bff4cceb1ee00d37f73327b", "short_code": "coll", "title": "BGS11_01: in-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft", "abstract": "In-situ airborne observations by the NERC ARSF Dornier Do228-101 D-CALM Aircraft aircraft for arsf BGS11_01 project.", "keywords": "BGS11_01, arsf, airborne, atmospheric measurments", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [], "member": [], "identifier_set": [], "responsiblepartyinfo_set": [ 107396, 107397, 107398, 107399, 107400, 107401, 107402, 107403 ], "onlineresource_set": [], "project_set": [ 25678 ] }, { "ob_id": 25832, "uuid": "43ddf5c677a14b9ebe8e8248797bdfb8", "short_code": "coll", "title": "High-End cLimate Impacts and eXtremes (HELIX): McArthur Forest Fire Danger Index (FFDI) and the Angström Index fire indices for 2061 - 2070.", "abstract": "The High-End cLimate Impacts and eXtremes (HELIX) project has calculated fire danger for the period 2061 to 2070 under two different climate change scenarios to assess the change in fire danger at 1.5 degrees compared to 2 degrees Celsius.\r\n\r\n\r\nThe two fire indices (the McArthur Forest Fire Danger Index (FFDI); and the Angström Index) were based on output from the Earth System Model HadGEM2-ES (Collins et al, 2011; Jones et al, 2011) at a spatial resolution of 1.875° x 1.25°, driven by concentrations following two experiments. The first was the strong mitigation scenario RCP2.6 (Representation Concentration Pathway) for the 2 degree change used within the World Climate Research Programme's (WCRP) Climate Modelling Intercomparison Project phase 5 (CMIP5). The second was a new experiment set up using a new run of RCP2.6+SRM initialised at 2020 and run to the end of the 21st century with SO₂ injected continuously and uniformly into the stratosphere at a height of 16-25 km in 4 member ensemble simulations. In the model, the SO₂ oxidises to form a sulphate aerosol which reflects incoming solar radiation and creates a cooling effect on the climate, simulating the effect of SRM in order to keep climate warming to 1.5°C.\r\n\r\n\r\n", "keywords": "HELIX, Angström, Climate, risk, McArthur, Forest Fire", "publicationState": "published", "dataPublishedTime": "2018-03-07T15:11:34", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 209 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25826, "uuid": "70ac55eb85344c3bb2239ed2d7b7575d", "short_code": "ob", "title": "HELIX: McArthur Forest Fire Danger Index (FFDI) for 2061 - 2070 at 1.5 and 2.0 degrees", "abstract": "The High-End cLimate Impacts and eXtremes (HELIX) project have calculated fire danger for the period 2061 to 2070 under two different climate change scenarios based on the Representative Concentration Scenario (RCP) scenarios used within the World Climate Research Programme's (WCRP) Climate Modelling Intercomparison Project phase 5 (CMIP5) using two Fire Indices, the McArthur Forest Fire Danger Index (FFDI), and the Angstroem Index. This work has been done to assess the change in fire danger at 1.5 degrees compared to 2 degrees Celsius.\r\n\r\nThis dataset presents those from the McArthur Forest Fire Danger Index (FFDI), utilising Met Office Earth System Model HadGEM2-ES model output at a spatial resolution of 1.875° x 1.25°. The original model data were produced and owned by the Met Office. These results have been saved into gridded netCDF files showing global fire risk. The files represent two experimental runs, one is driven by concentrations following the Representative Concentration Scenario (RCP) 2.6, and the second represents a theoretical Solar Radiation Management scenario using a sulphur dioxide aerosol injection to reduce global mean temperature to 1.5 degrees Celsius. There are 4 ensemble members for each experiment: apdib, apdic, apdid and apdie are the ensemble members for the RCP2.6+SRM run; ajnjm, kaadc, kaaec and kaafc are the ensemble members for the standard RCP2.6 run. A period of 10 years 2061-2070 is chosen for this analysis, and this is compared to a present day period of 2006-2015 (files are labelled according to the data period represented). " }, { "ob_id": 25827, "uuid": "75a7e567fe2342a493663a7a085d015e", "short_code": "ob", "title": "HELIX: Angström calculated fire risk index for 2061 - 2070 at 1.5 and 2.0 degrees", "abstract": "The High-End cLimate Impacts and eXtremes (HELIX) project have calculated fire danger for the period 2061 to 2070 under two different climate change scenarios based on the Representative Concentration Scenario (RCP) scenarios used within the World Climate Research Programme's (WCRP) Climate Modelling Intercomparison Project phase 5 (CMIP5) using two Fire Indices, the McArthur Forest Fire Danger Index (FFDI), and the Angström Index. This work has been done to assess the change in fire danger at 1.5 degrees compared to 2 degrees Celsius.\r\n\r\nThis dataset presents those from the Angström calculated fire risk index, utilising Met Office Earth System Model HadGEM2-ES model output at a spatial resolution of 1.875° x 1.25°. The original model data were produced and owned by the Met Office. These results have been saved into gridded netCDF files showing global fire risk. The files represent two experimental runs, one is driven by concentrations following the Representative Concentration Scenario (RCP) 2.6, and the second represents a theoretical Solar Radiation Management scenario using a sulphur dioxide aerosol injection to reduce global mean temperature to 1.5 degrees Celsius. There are 4 ensemble members for each experiment: apdib, apdic, apdid and apdie are the ensemble members for the RCP2.6+SRM run; ajnjm, kaadc, kaaec and kaafc are the ensemble members for the standard RCP2.6 run. A period of 10 years 2061-2070 is chosen for this analysis, and this is compared to a present day period of 2006-2015 (files are labelled according to the data period represented). " } ], "identifier_set": [], "responsiblepartyinfo_set": [ 107900, 107901, 107902, 107903, 107904, 107905, 107907, 107906, 107908, 107909, 107910, 107911 ], "onlineresource_set": [], "project_set": [] }, { "ob_id": 25891, "uuid": "66ab6655f9da44d9bf34b079dc8a25e6", "short_code": "coll", "title": "Effective sulphur dioxide (SO2) column amounts from the Infrared Atmospheric Sounding Interferometer (IASI) instrument", "abstract": "Effective sulphur dioxide (SO2) column amounts have been derived from the Infrared Atmospheric Sounding Interferometer (IASI) instrument on the METOP-A satellite, by the University of Oxford as part of the NERC Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET).\r\n\r\nThe data have been produced using the Walker et al. (2011, 2012) linear retrieval developed for the Infrared Atmospheric Sounding Interferometer, which is able to detect sulphur dioxide (SO2) gas. The dataset contained here consists of monthly averages of this retrieval output from June 2007 to December 2014 across the globe, within which it is possible to identify the period and the location of when we have an anomaly of SO2 in atmosphere. This includes volcanic eruptions alongside non-eruptive volcanic degassing, and human pollution sources.", "keywords": "", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [], "member": [ { "ob_id": 25886, "uuid": "8eb35b1ab1b2476986d174a2f0231307", "short_code": "ob", "title": "IASI global monthly averages of effective sulphur dioxide (SO2) column amounts, 2007 - 2014, version 1.0", "abstract": "This dataset contains global monthly averaged effective sulphur dioxide (SO2) column amounts derived from the Infrared Atmospheric Sounding Interferometer (IASI) instrument on the METOP-A satellite. The data have been produced by the University of Oxford as part of the NERC Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET). \r\n\r\nThis dataset has been produced using the Walker et al. (2011, 2012) linear retrieval developed for the Infrared Atmospheric Sounding Interferometer, which is able to detect sulphur dioxide (SO2) gas. This dataset contains monthly averages of this retrieval output from June 2007 to December 2014 across the globe, within which it is possible to identify the period and the location of when we have an anomaly of SO2 in atmosphere. This includes volcanic eruptions alongside non-eruptive volcanic degassing, and human pollution sources. \r\n\r\nWithin the dataset are the average effective SO2 column amounts in Dobson Units (DU) for 0.125º by 0.125º gridboxes across the globe. Also included for each grid box are the standard deviation, and the number of pixel boxes contributing to the mean. The results from this dataset are discussed in Taylor et al. (2018) 'Exploring the utility of IASI for monitoring volcanic SO2 emissions' in review at JGR: Atmospheres." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 108250, 108245, 108248, 108246, 108247, 204935, 204936, 204937, 108251, 108252 ], "onlineresource_set": [], "project_set": [] }, { "ob_id": 25939, "uuid": "5fda5ee95a544a3b894dd4a5392be618", "short_code": "coll", "title": "Sentinel 2B: High-resolution optical imaging data from the Multispectral Instrument (MSI)", "abstract": "This dataset collection contains land monitoring data from the Multispectral Instrument (MSI) on the European Space Agency (ESA) Sentinel 2B satellite. Sentinel 2B was launched on 7th March 2017 and provides sun-synchronous platform for the multispectral imaging data. The instrument uses 13 spectral bands from visible to the near infrared to obtain images with a swath width of 290km. Level 1C processing provides Top-Of-Atmosphere (TOA) reflectances in cartographic geometry. A further processing level, bottom-of-atmosphere (BOA) reflectance in cartographic geometry (prototype product) can be produced by the user with the Sentinel 2 toolbox. The BOA mode allows for the accurate assessment of biophysical parameters e.g. Leaf Area Index, with reduced cloud interference.", "keywords": "Sentinel, Multispectral Instrument, MSI", "publicationState": "published", "dataPublishedTime": "2016-11-16T16:24:30", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 148 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25276, "uuid": "f9df4417213b49a888ab2c85faefd2ba", "short_code": "ob", "title": "Sentinel 2B Multispectral Instrument (MSI) Level 1C data", "abstract": "This dataset contains Top-of Atmosphere (TOA) reflectances in cartographic geometry (level 1C) processed data, from the Multispectral Instrument (MSI) aboard the European Space Agency (ESA) Sentinel 2B satellite. Sentinel 2B was launched on 7th March 2016 and provides multispectral images of the earth’s surface as a continuation and enhancement of the Landsat and SPOT missions. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user.\r\n\r\nCEDA have switched to provide Sentinel 2 data for the UK and Dependencies along with data needed per project basis as of April 2019. Please contact us if you need data outside these areas and we will see what we can do." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 108428, 108422, 108425, 108423, 108424, 108426, 108429, 108427, 108430 ], "onlineresource_set": [ 24539, 24540, 24541 ], "project_set": [ 12321 ] }, { "ob_id": 25940, "uuid": "3a9a9c2af1c3439cabcda91edc4eaf56", "short_code": "coll", "title": "QA4ECV Albedo", "abstract": "Knowledge of albedo is of critical importance to land surface monitoring and modelling, particularly with regard to considerations of climate forecasting and energy exchanges within the biosphere. When albedo is used in models, it has often been specified as a fixed number for some given land cover type. However, many years of monitoring from single instruments, such as MODIS, have shown that it can vary significantly both spatially and temporally. That said, being an angular and spectral integral, it is relatively conservative inter-annually, other than due to factors such as snow and possibly fire and dramatic land cover change (e.g. flooding, urbanisation). As particularly high changes in albedo occur due to the presence of absence of snow, modellers tend to consider these two cases separately: a snow free albedo and one with snow included.\r\n\r\nGlobal albedo data of the land surface is produced from data from 1982-2016 from European and US satellites daily and monthly with estimated uncertainties for every pixel. There are 3 data products including: 1) AVHRR+GEO Broadband Albedo at 0.5 and 0.05 degrees; 2) Spectral Albedo at 1km; and 3) Sea Ice Spectral Albedo at 1km", "keywords": "", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 210 ], "discoveryKeywords": [], "member": [ { "ob_id": 25938, "uuid": "efb5c580d2774a37acf4515cbc5f7bba", "short_code": "ob", "title": "QA4ECV Global Broadband albedo (1982-2016)", "abstract": "Global albedo data of the land surface is produced from data from 1982-2016 from European and US satellites, daily and monthly products with estimated uncertainties for every pixel. This data product is produced from AVHRR+GEO Broadband Albedo at 0.5 and 0.05 degrees. This dataset contains Level-3 daily surface broadband albedo products. Level-3 data are raw observations processed to geophysical quantities, and placed onto a regular grid.\r\n\r\nKnowledge of albedo is of critical importance to land surface monitoring and modelling, particularly with regard to considerations of climate forecasting and energy exchanges within the biosphere. When albedo is used in models, it has often been specified as a fixed number for some given land cover type. However, many years of monitoring from single instruments, such as MODIS, have shown that it can vary significantly both spatially and temporally. That said, being an angular and spectral integral, it is relatively conservative inter-annually, other than due to factors such as snow and possibly fire and dramatic land cover change (e.g. flooding, urbanisation). As particularly high changes in albedo occur due to the presence of absence of snow, modellers tend to consider these two cases separately: a snow free albedo and one with snow included." }, { "ob_id": 25941, "uuid": "38296ae73f3b44f5b8d66dcc3ed398bd", "short_code": "ob", "title": "QA4ECV Polar sea-ice spectral albedo (2000-2016)", "abstract": "The Quality Assurance for Essential Climate Variables (QA4ECV) project produced four daily polar sea-ice products, each with a different averaging time window (24 hours, 7 days, 15 days, 31 days). For each time window, the number of samples, mean and standard deviation of Multi-angle Imaging SpectroRadiometer (MISR) cloud-free sea ice albedo was calculated. These products are on a predefined polar stereographic grid at three spatial resolutions (1 km, 5 km, 25 km). The time span of the generated sea ice albedo covers the months between March and September of each year from 2000 to 2016 inclusive.\r\n\r\nIf publishing results based on this dataset, please cite the following: S. Kharbouche and J.-P. Muller, “Sea Ice Albedo from MISR and MODIS: Production, Validation, and Trend Analysis,” Remote Sensing, vol. 11,no. 1, p. 9, Dec. 2018. DOI: 10.3390/rs11010009. URL:http://www.mdpi.com/2072-4292/11/1/9" }, { "ob_id": 25942, "uuid": "bd2ad818ebec44748078fefa5161bd83", "short_code": "ob", "title": "QA4ECV Europe Spectral albedo (1998-2000, 2005-2006)", "abstract": "European spectral albedo data of the land surface is produced from data from 1998-200 and 2005-2006 from European and US satellites daily and monthly with estimated uncertainties for every pixel. The spectral albedo is calculated at the first 6 of the MODIS spectral bands." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 108431, 108554, 108555, 108556, 204886, 204887, 204888, 108432 ], "onlineresource_set": [], "project_set": [ 25937 ] }, { "ob_id": 25943, "uuid": "597cdd6371ba410ea72bd4219181178c", "short_code": "coll", "title": "QA4ECV LAI and FAPAR", "abstract": "The Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product).\r\n\r\nBased on the global albedo data on 0.5 degree and 0.05 degree regular grids, TIP-LAI and TIP-FAPAR are available for 1982 to 2016.", "keywords": "", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 210 ], "discoveryKeywords": [], "member": [ { "ob_id": 25945, "uuid": "fb1df8ff08564616818d71d78db03f51", "short_code": "ob", "title": "QA4ECV BHR-TIP FAPAR/ effective LAI (1982-2016)", "abstract": "The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product). The definition of FAPAR in this product is the simulated absorption of the photosynthetically active radiation (estimated for the visible band) by a homogeneous canopy of infinitesimally small Lambertian surfaces, akin to a turbid medium." }, { "ob_id": 25944, "uuid": "050ab7126ebe4300b7a3dc9fce18b054", "short_code": "ob", "title": "QA4ECV LAI", "abstract": "The Leaf Area Index (LAI) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product). he definition of LAI in this product is half the total canopy area per unit ground area (m2 / m2) for a homogeneous canopy of infinitesimally small Lambertian surfaces, akin to a turbid medium." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 108456, 204851, 204852, 204853, 204854, 204855, 204856, 108457 ], "onlineresource_set": [], "project_set": [ 25937 ] }, { "ob_id": 25946, "uuid": "6e8371d872574bcb801011ace6bf393d", "short_code": "coll", "title": "QA4ECV AVHRR FAPAR", "abstract": "Need some more information here.", "keywords": "", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 210 ], "discoveryKeywords": [], "member": [ { "ob_id": 25947, "uuid": "5587614793674fa680a8e6e5b93c6bff", "short_code": "ob", "title": "QA4ECV DHR-FAPAR (1982-2006)", "abstract": "The Joint Research Centre (JRC) are currently producing a new Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product which ingests Advanced Very High Resolution Radiometer (AVHRR) data. The estimation of a state variable from the signals measured by a given sensor is constructed from sensor-specific simulated data sets, representative of various land surfaces, using radiative transfer models of the coupled surface atmosphere system. This approach defines a large number of simulated radiance fields, which can be sampled by a virtual instrument similar to the actual one in terms of the spectral and angular observing schemes. Similarly, the corresponding FAPAR values for the various terrestrial systems under investigation can be simultaneously estimated. The simulations of FAPAR values have been made by assuming that the spectral properties of leaves and soil correspond to the Photosynthesis Active Radiation (PAR) region which is between 400 nm and 700 nm. In this case, simulations are made with a homogeneous canopy model (Gobron et al. 1997) representing land surfaces." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 108472, 108547, 108548, 108549, 204910, 204911, 204912, 108473 ], "onlineresource_set": [], "project_set": [ 25937 ] }, { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.", "keywords": "surface meteorology, atmospheric composition, arctic", "publicationState": "published", "dataPublishedTime": "2018-04-14T11:27:46", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25955, "uuid": "f2f4675203d04e4eb269e230633d03db", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): high resolution ship motion data from the University of Leeds XSENS MTi-G-700 attitude and heading reference system on board Icebreaker Oden", "abstract": "This dataset contains high resolution attitude and motion measurements of the Icebreaker Oden ship's motion by the University of Leeds' XSENS MTi-G-700 attitude and heading reference system during the Arctic Cloud Summer Expedition (ACSE). The ACSE cruise took place in the Arctic during summer 2014. These data were obtained to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (Swedish-Russian-US Investigation) holdings - see online resources linked to this record.\r\n\r\nMeasurements were made at 40Hz for inertial measurements and 4Hz for GPS measurements. Though the inertial measurements were used at 20Hz when merged with sonic anemometer, 20 minute final fluxes (see related data within the parent data collection).\r\n\r\nThe XSens MTi-G-700 measures 3-axis accelerations, rotation rates, and magnetic field components as well as GPS position. Internal algorithm calculate 3-axis velocity, tilt angles and heading. However, users of these data should note that it is often not possible to calibrate magnetic field for local platform induced distortions (soft iron and hard iron corrections) resulting in errors in magnetic field and calculated outputs. Additionally, the heading measurements were found to unreliable on the ship.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF)." }, { "ob_id": 26010, "uuid": "d23f1cdf560f4ae185d1e008d1eef4b7", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): SPRS Icebreaker Oden ship navigation data", "abstract": "This dataset contains ship navigation data, including speed over group, course, heading etc, fomr the Swedish Polar Research Secretariat's (SPRS) Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThese data are provided as supportive data for use with the other datasets within this collection, helping to account for ship movement during the expedition for later data analysis. These data were prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 26026, "uuid": "3b1effa4b6554366b9ad571fc32a6f7d", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): composite cloud layer data for Icebreaker Oden", "abstract": "This dataset contains derived cloud layer measurements of Icebreaker Oden utilising data from the National Centre for Atmospheric Science's Atmospheric Measurement Facility's (NCAS AMF) Halo Doppler lidar and NOAA cloud radar on board Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe data provide altitudes of cloud base and top for the first two cloud layers. Cloud base was established from the laser ceilometer (base of liquid cloud) whist he cloud top was established from the cloud radar data. \r\n\r\nWhere fog was detected, the fog top altitude from the radar data is given. Note: it was possible for the radar to detect a cloud top where the laser ceilometer was not able to detecte a cloud base.\r\n\r\nThese data were prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 25964, "uuid": "ed7d19d3be8d43bbb3ae804418fb7bf4", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): visibility and precipitation measurements from the Finnish Meteorological Institute Vaisala FD12P present weather sensor on board Icebreaker Oden", "abstract": "This dataset contains visibility and precipitation measurements from the Finnish Meteorological Institute (FMI) Vaisala FD12P present weather sensor, operated by cruise participants from Stockholm University, on board Icebreaker Oden mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). These data were then prepared by Ian Brooks from the University of Leeds for inclusion in this archive.\r\n\r\nACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data such as these data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nSome outputs from this instrument were used as part of the quality control for some other measurements.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 25979, "uuid": "0af02f899ac14c218706295d3c6d1c4d", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): surface meteorology and radiation measurements from the Stockholm University's automatic weather station on board Icebreaker Oden", "abstract": "This dataset contains surface meteorological measurements including air temperature, relative humidity, surface irradiation and wind measurements from the Meteorologiska Institutionen Stockholms Universitet (MISU) weather station on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThese data came from an automatic weather station installed on the 7th deck of the Icebreaker Oden, approximately 25m above the surface, measuring at 1 Hz frequency. The system was operated by Joe Sedlar who also undertook data quality control and there are several flag variables for T/RH and radiation measurements documenting known data issues - notably when primary measurements have been replaced with those from other sensors, or corrections applied. This version of the dataset was then prepared for archiving with the Centre for Environmental Data Analysis by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 26021, "uuid": "da84490d169246d381f59bccdfd143f1", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): composite ship motion data for Icebreaker Oden from on board ship navigation data and University of Leeds' XSens motion sensor package.", "abstract": "This dataset contains combined measurements of platform motion and final velocity and attitude corrections for turbulence measurements on the foremast of Icebreaker Oden utilising data from the ship's navigation unit alongside data from the University of Leeds' XSens motion and heading sensory package. These data include ship speed over group, course, heading etc, for Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe XSens motion pack was mounted at the base of the sonic anemometer, in the same reference frame (rotated 30 deg to port from bow). Rotation angles given in the dataset are with respect to the earth frame, with x-axis positive to east. \r\n\r\nCorrections combine high rate data from the Xsens package with low rate data from the ship navigation system (heading and speed) to derive the full earth-relative platform motion at 20Hz. The motion calculation follows Edson et al. (1988) and Prytherch et al. (2015) - see linked documentation.\r\n\r\nThese data are provided as supportive data for use with the other datasets within this collection, helping to account for ship movement during the expedition for later data analysis. These data were prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 26852, "uuid": "72d29f16054d4a8ca056796a8c5d6e3d", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): wave statistics, wave spectra and raw buoy displacement data from the University of Leeds Datawell DWR-G4-Waverider buoy deployed from the Icebreaker Oden", "abstract": "This dataset contains derived wave statistics, directional wave spectra and raw buoy displacement data from the University of Leeds Datawell DWR-G4-Waverider buoy deployed from the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe buoy was deployed on numerous occasions during the voyage, including multiple deployments per day (the deployment number during the day is given in the filename following the date of deployment). However, some deployments are omitted from the archive where significant problems with the raw data were found (failure to obtain GPS lock; too-short a deployment, etc.). The deployment number for the day has been maintained to coincide with the buoy's deployment logs. Data are truncated to remove the deployment and recovery. No further quality control has been applied to the data.\r\n\r\nThe raw displacement timeseries data contains raw buoy displacements (up, north, west) from which the spectra were calculated. The spectra were calculated as 10-minute averages. The methodology used is detailed within the files, but include both raw (quite noisy) and smoothed spectra.\r\n\r\nThe overall wave statistics file contains all wave statistics data obtained during the voyage (significant wave height, spectral peak details, etc, along with the spectral moments from which the stats are calculated). These are all given for each spectrum as a whole, and partitioned into windsea and swell components. References to the techniques used to produce these statistics are given in the file.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 26024, "uuid": "e58fdade3a6c46bbaae7c53e948dd6d0", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): composite flux data for Icebreaker Oden", "abstract": "This dataset contains provides the final best estimates of fluxes, mean environmental variables and derived transfer coefficient estimates, along with asociated quality control flags, during the Icebreaker Oden voyage durning the Arctic Cloud Summer Expedition (ACSE) in summer 2014. These were calculated based on instrumentation data from the University of Leeds' Metek sonic anemometer, Licor LI-7500 gas analyzer and XSENS MTi-G-700 motion pack, plus mean surface meteorology data provided from the automatic weather station operated on board by the Department of Meteorology, Stockholm University (MISU).\r\n\r\nOther data from the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.\r\n\r\nThe document \"ACSE_turbulent_fluxes_readme.txt\" in the archive contains fuller details of the flux calculations. The final data, prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds, contain:\r\n\r\n1) The final quality controlled best estimates of 20-min averaged dynamic fluxes, associated mean environmental variables (10m wind, etc), transfer coefficients, and quality control flags.\r\n\r\n2) The raw kinematic fluxes, etc that go into generating (1), along with the quality control variables used in generating the QC flags, and the QC flags.\r\n\r\n3) Other environmental variables (in some cases with duplicates from multiple different sensors) averaged onto the same time base as the flux estimates.\r\n\r\nThe authors note that in all cases a lot of work has been done on quality control and applying suitable corrections to raw measurements. In many cases other choices could have been made, and additional QC measures may need to be applied.\r\n\r\nMost of the work on the flux data processing has been done by John Prytherch, with additional input from Ian Brooks and Dominic Salisbury. Additional work on ancillary data was undertaken by other members of the ACSE science team." }, { "ob_id": 25953, "uuid": "f2566ac78a664a58a23a42e9e45da788", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): University of Leeds Mobotix camera imagery on board Icebreaker Oden", "abstract": "This dataset contains digital imagery from the University of Leed's three 'Mobotix MX-M24M IP' cameras mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These imagery were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe three camera units were mounted pointing in the following directions:\r\n\r\n - Camera 1: pointing to starboard,\r\n - Camera 2: pointing to bow,\r\n - Camera 3: pointing to port.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF)." }, { "ob_id": 25951, "uuid": "bfa8b9457e1a4cb6aa506316295564b2", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): turbulence wind and sonic temperature measurements from the University of Leeds Metek USA-100 sonic anemometer on board Icebreaker Oden", "abstract": "This dataset contains turbulent winds and sonic temperature measurements by the University of Leeds' Metek USA-100 sonic anemometer during the Arctic Cloud Summer Expedition (ACSE). The ACSE cruise took place in the Arctic during summer 2014. These data were obtained to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nMeasurements were made at 20Hz from which 20-minute average fluxes were then derived.\r\n\r\nThe sonic anemometer was located on the foremast of the Icebreaker Oden ship at 20.58 m above the waterline. Data here includes the raw measurements and fully corrected turbulent winds (motion correction, flow distortion correction, etc), along with sonic temperature. For details of motion and flow distortion see the linked documentation. \r\n\r\nNote that while the Metek anemometer uses a left-handed reference frame, all measurements have been transformed to a right-handed frame here. The anemometer x-axis was rotated 30 deg anticlockwise from ship bow.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 25960, "uuid": "5f3fe268651e497d936a9893f61a043a", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): surface temperature measurements from the University of Leeds Heitronics KT15.85 infra red radiative temperature sensor on board Icebreaker Oden", "abstract": "This dataset contains surface temperature measurements from the University of Leeds' two Heitronics KT15.85 infra red radiative temperature sensors mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nBoth instruments were mounted to point to starboard, but instrument 1 pointing 45 degrees forward and instrument 2 pointing 45 degrees aft, taking raw measurements at 1Hz. The data contain both the raw measured temperature (t_meas) and a corrected value, adjusted for reflection of thermal radiation from surface. The correction follows that developed by Phil Hignett for a similar sensor on the UK Met Office C130 aircraft : MRF Tech note 28, 1988.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 25950, "uuid": "a3e0f0848a144484bdea833ef01ec834", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): carbon dioxide and water vapour measurements from the University of Leeds LI-COR Li-7500 gas analyzer on board Icebreaker Oden", "abstract": "This dataset contains carbon dioxide and water vapour concentration measurements from the University of Leeds' LI-COR LI-7500 open path gas analyser mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe instrument's sensing head was located on the foremast of Icebreaker Oden, approximately 1 m forward of the sonic anemometer. Note the LiCOR LI-7500 CO2 data are generally not suitable for flux measurements at sea. Only the water vapour signal has been used for flux analysis.\r\n\r\nData times were truncated to match those from the sonic anemometer and the internal lag was corrected for.\r\n\r\nUsers should also note that the instrument's temperature and pressure measurements are made inside the interface box. Temperature is thus likely to be high due to solar heating of box, and pressure will be biased low (box is ~3 m below sensor) and may be subject to dynamic pressure fluctuations resulting from airflow around pressure inlet.\r\n\r\nMeasurements are made at 20 Hz frequency.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 25968, "uuid": "e4b9bd20c2b144e9a34fb2d0ed2d0333", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): air temperature and relative humidity measurements from the Stockholm University's Rotronic T/RH sensor on board Icebreaker Oden", "abstract": "This dataset contains surface air temperature (T) and relative humidity (RH) measurements from the Meteorologiska Institutionen Stockholms Universitet (MISU) Rotronic T/RH sensor mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nMeasurements were made at 1 Hz frequency and this dataset was prepared for archiving by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 26007, "uuid": "61cd9961ecef43edadae89f842598f47", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): composite temperature, humidity and wind profiles and derived variables from the NCAS AMF radiosondes launched from Icebreaker Oden", "abstract": "This dataset contains composite temperature, humidity and wind profiles, plus derived products, from the National Centre for Atmospheric Science's Atmospheric Measurement Facility (NCAS AMF) radiosondes launched from the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThese data consist of individual radiosonde profiles as 2D time/height fields, with all profiles interpolated onto a fixed vertical grid for ease of analysis/plotting across the outward (leg 1) and return (leg 2) parts of the expedition.\r\n\r\nThe vertical grid used is: 1m step to 5km, 10m step between 5 and 12 km, 50m step between 12 and 20 km. The data also includes derived variables (potential temperature etc).\r\n\r\nBarbara Brooks (NCAS AMF) was responsible for the radiosonde ascents during the voyage and for the original data, whilst Ian Brookes prepared these data for archiving.\r\n\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." }, { "ob_id": 25996, "uuid": "ce693b9c237d4e8cb7968ef76dfc9584", "short_code": "ob", "title": "Arctic Cloud Summer Expedition (ACSE): composite lidar wind profile data from the NCAS AMF Halo Doppler lidar on board Icebreaker Oden", "abstract": "This dataset contains composite lidar wind profile data from the NCAS AMF Halo Doppler lidar mounted on a motion stabilised platform on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 108484, 108485, 108487, 108488, 108489, 108491, 108490, 108486, 108493, 108492, 109251, 108494, 108495, 109252, 109253, 109254, 109255, 109256, 109257 ], "onlineresource_set": [], "project_set": [ 24932 ] }, { "ob_id": 25978, "uuid": "f65252bf8ee5448baa1ae060cd07703a", "short_code": "coll", "title": "Quality Assurance for Essential Climate Variables (QA4ECV)", "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).", "keywords": "", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 210 ], "discoveryKeywords": [], "member": [ { "ob_id": 25938, "uuid": "efb5c580d2774a37acf4515cbc5f7bba", "short_code": "ob", "title": "QA4ECV Global Broadband albedo (1982-2016)", "abstract": "Global albedo data of the land surface is produced from data from 1982-2016 from European and US satellites, daily and monthly products with estimated uncertainties for every pixel. This data product is produced from AVHRR+GEO Broadband Albedo at 0.5 and 0.05 degrees. This dataset contains Level-3 daily surface broadband albedo products. Level-3 data are raw observations processed to geophysical quantities, and placed onto a regular grid.\r\n\r\nKnowledge of albedo is of critical importance to land surface monitoring and modelling, particularly with regard to considerations of climate forecasting and energy exchanges within the biosphere. When albedo is used in models, it has often been specified as a fixed number for some given land cover type. However, many years of monitoring from single instruments, such as MODIS, have shown that it can vary significantly both spatially and temporally. That said, being an angular and spectral integral, it is relatively conservative inter-annually, other than due to factors such as snow and possibly fire and dramatic land cover change (e.g. flooding, urbanisation). As particularly high changes in albedo occur due to the presence of absence of snow, modellers tend to consider these two cases separately: a snow free albedo and one with snow included." }, { "ob_id": 25945, "uuid": "fb1df8ff08564616818d71d78db03f51", "short_code": "ob", "title": "QA4ECV BHR-TIP FAPAR/ effective LAI (1982-2016)", "abstract": "The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product). The definition of FAPAR in this product is the simulated absorption of the photosynthetically active radiation (estimated for the visible band) by a homogeneous canopy of infinitesimally small Lambertian surfaces, akin to a turbid medium." }, { "ob_id": 25941, "uuid": "38296ae73f3b44f5b8d66dcc3ed398bd", "short_code": "ob", "title": "QA4ECV Polar sea-ice spectral albedo (2000-2016)", "abstract": "The Quality Assurance for Essential Climate Variables (QA4ECV) project produced four daily polar sea-ice products, each with a different averaging time window (24 hours, 7 days, 15 days, 31 days). For each time window, the number of samples, mean and standard deviation of Multi-angle Imaging SpectroRadiometer (MISR) cloud-free sea ice albedo was calculated. These products are on a predefined polar stereographic grid at three spatial resolutions (1 km, 5 km, 25 km). The time span of the generated sea ice albedo covers the months between March and September of each year from 2000 to 2016 inclusive.\r\n\r\nIf publishing results based on this dataset, please cite the following: S. Kharbouche and J.-P. Muller, “Sea Ice Albedo from MISR and MODIS: Production, Validation, and Trend Analysis,” Remote Sensing, vol. 11,no. 1, p. 9, Dec. 2018. DOI: 10.3390/rs11010009. URL:http://www.mdpi.com/2072-4292/11/1/9" }, { "ob_id": 25973, "uuid": "ef63d8590dd7445c8783df00f0ba654b", "short_code": "ob", "title": "QA4ECV MODIS spectral BRDF climatology (2000-2016)", "abstract": "Spectral BRDF climatology from merge of snow and nosnow products upscaled at 0.05º derived from 17 records (one for each year form 2000..2016) for each land surface pixel for each day of year. each pixel has an estimated uncertainty based on a weighting of the MODIS MCD43A2 Quality bit flags. This dataset represents a global climatology in the 7 MODIS spectral bands and is used within the QA4ECV for regularisation purposes as the \"prior\" for spectral inversions." }, { "ob_id": 25947, "uuid": "5587614793674fa680a8e6e5b93c6bff", "short_code": "ob", "title": "QA4ECV DHR-FAPAR (1982-2006)", "abstract": "The Joint Research Centre (JRC) are currently producing a new Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product which ingests Advanced Very High Resolution Radiometer (AVHRR) data. The estimation of a state variable from the signals measured by a given sensor is constructed from sensor-specific simulated data sets, representative of various land surfaces, using radiative transfer models of the coupled surface atmosphere system. This approach defines a large number of simulated radiance fields, which can be sampled by a virtual instrument similar to the actual one in terms of the spectral and angular observing schemes. Similarly, the corresponding FAPAR values for the various terrestrial systems under investigation can be simultaneously estimated. The simulations of FAPAR values have been made by assuming that the spectral properties of leaves and soil correspond to the Photosynthesis Active Radiation (PAR) region which is between 400 nm and 700 nm. In this case, simulations are made with a homogeneous canopy model (Gobron et al. 1997) representing land surfaces." }, { "ob_id": 25942, "uuid": "bd2ad818ebec44748078fefa5161bd83", "short_code": "ob", "title": "QA4ECV Europe Spectral albedo (1998-2000, 2005-2006)", "abstract": "European spectral albedo data of the land surface is produced from data from 1998-200 and 2005-2006 from European and US satellites daily and monthly with estimated uncertainties for every pixel. The spectral albedo is calculated at the first 6 of the MODIS spectral bands." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 108647, 108648, 204889, 204890, 204891, 204892, 204893, 108646 ], "onlineresource_set": [], "project_set": [] }, { "ob_id": 26018, "uuid": "5fcae68057ea43259d0a4530d34e4ba5", "short_code": "coll", "title": "UKCP18 Simulations of Sea Surface Elevation for UK Waters", "abstract": "Historical and future simulations of sea surface elevation for UK waters for 1970-2100 produced by the Met Office for UK Climate Projections 2018 (UKCP2018). The data is available at hourly temporal resolution.", "keywords": "UKCP18, UKCP, Climate, Marine, Simulations, Historical, Projections", "publicationState": "published", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 212 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26016, "uuid": "9b204cb345994797b9197744d0ef619c", "short_code": "ob", "title": "UKCP18 Future Simulations of Gridded Sea Surface Elevation around the UK for 2007-2100", "abstract": "The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 RCP8.5 simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 2007 to 2099, and applies to the UK coast.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section." }, { "ob_id": 26017, "uuid": "610a8d5b32fc4c51b8a2ed64de95ed73", "short_code": "ob", "title": "UKCP18 Historical Simulations of Gridded Sea Surface Elevation around the UK for 1970-2006", "abstract": "\"The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 historical simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 1970 to 2005, and applies to the UK coast.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 108810, 108811, 108812, 108814, 108816, 108817, 112311, 112313, 108813, 108815, 112312 ], "onlineresource_set": [ 24591, 24592, 24593, 25970, 27311, 27312 ], "project_set": [ 26015 ] }, { "ob_id": 26049, "uuid": "1cec31b7f73d429d8d273064d0a8f824", "short_code": "coll", "title": "ODYSEA: Ocean Dynamics as Driver of Seasonal to Decadal European Atmospheric variability project data", "abstract": "A collection of data products produced by the NERC project ODYSEA: Ocean Dynamics as Driver of Seasonal to Decadal European Atmospheric variability.", "keywords": "NE/M006107/1, decadal European atmospheric variability", "publicationState": "published", "dataPublishedTime": "2018-04-19T13:54:47", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26047, "uuid": "c0c7998800414e46b6823dc75751bb4c", "short_code": "ob", "title": "Envelope field of Northern hemispheric upper tropospheric (300 hPa) quasi-stationary waves (June 1979 to August 2015)", "abstract": "This dataset comprises 12 hourly data of the envelope field of Northern hemispheric upper tropospheric (300 hPa) quasi-stationary waves calculated between1979-06-01 and 2015-08-31. The data were derived as part of the NERC funded ODYSEA project (Ocean Dynamics as Driver of Seasonal to Decadal European Atmospheric variability).\r\n\r\nThe envelope field in this dataset is a phase-independent measure of the wave amplitude and is derived from the meridional wind at 300 hPa of the ERA-Interim reanalysis data. To remove the faster transient signals a 15-day lowpass filter was applied to the meridional wind and then subtracted from a daily climatology. The envelope field allows for the identification of a slowly evolving stationary or slowly moving wave packet.\r\n\r\nFull details of the method are described in the methodology statement that can be found in the docs section." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 109039, 109040, 109041, 109044, 109047, 109042, 109043, 109046, 109045, 169541 ], "onlineresource_set": [], "project_set": [ 26048 ] }, { "ob_id": 26096, "uuid": "8ec7ddba554844b4ad1a600ff2196e1c", "short_code": "coll", "title": "Re-analysis (ERA-20C, ERA-Interim, NCEP-CFS) European winter extra-tropical cyclone tracks 1900/1979-2010", "abstract": "This dataset collection contains winter (October - March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from three re-analysis datasets: ERA-20C (1900-2010), ERA-Interim (1979-2010) and NCEP-CFS (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.", "keywords": "extra-tropical, cyclone, European, track, tracks, ETC, storm, storms", "publicationState": "published", "dataPublishedTime": "2018-06-15T13:01:31", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26093, "uuid": "100dd91da981445fa4a350cc9cfe60bf", "short_code": "ob", "title": "Re-analysis ERA-20C European winter extra-tropical cyclone tracks 1900-2010", "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from the ERA-20C (1900-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)" }, { "ob_id": 26094, "uuid": "421688bf376b41b884246b34bd274356", "short_code": "ob", "title": "Re-analysis ERA-Interim European winter extra-tropical cyclone tracks 1979-2010", "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from the ERA-Interim (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)" }, { "ob_id": 26095, "uuid": "994193d395314c9fa33bdd38364f5171", "short_code": "ob", "title": "Re-analysis NCEP-CFS European winter extra-tropical cyclone tracks 1979-2010", "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from NCEP-CFS (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 109298, 109303, 109304, 109305, 109306, 109308, 109309, 109310, 109307, 168800, 109299, 109300, 109301, 109302 ], "onlineresource_set": [], "project_set": [ 26098 ] }, { "ob_id": 26156, "uuid": "9842e395f2d04f48a177c3550756bf98", "short_code": "coll", "title": "UKCP18 Probabilistic Climate Projections", "abstract": "Probabalistic climate projections for the UK from 1961-2100 produced by the Met Office for UK Climate Projections 2018 (UKCP18). The data is available on a 25km OSGB grid.", "keywords": "UKCP18, UKCP, Climate, UK, Probabalistic, Historical, Projections", "publicationState": "published", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 212 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26115, "uuid": "10538cf7a8d84e5e872883ea09a674f3", "short_code": "ob", "title": "UKCP18 Probabilistic Projections by UK River Basins for 1961-2100", "abstract": "This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 23 river basin regions in the UK is provided.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to." }, { "ob_id": 26114, "uuid": "8eca5b80ee244d9486162e699c5197f5", "short_code": "ob", "title": "UKCP18 Probabilistic Projections by Administrative Regions over the UK for 1961-2100", "abstract": "\"This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 16 administrative regions in the UK is provided. Further information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to under UK Climate Projections (UKCP18) news in the documentation section.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to under UK Climate Projections (UKCP18) news in the documentation section." }, { "ob_id": 26116, "uuid": "3d63c07922fd482b9d43394e02c9d3a8", "short_code": "ob", "title": "UKCP18 Probabilistic Projections by UK Countries for 1961-2100", "abstract": "\"This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 8 'country' regions in the UK is provided: Channel Islands, England, England and Wales, Isle of Man, Northern Ireland, Scotland, United Kingdom, Wales. Further information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links under UK Climate Projections (UKCP18) news in the documentation.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to under UK Climate Projections (UKCP18) news in the documentation section." }, { "ob_id": 30651, "uuid": "49fe5d454bf54b54afe0c7e8934e6db8", "short_code": "ob", "title": "UKCP18 Probabilistic Projections Global Temperature Means for 1860-2100", "abstract": "This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents mean global temperature anomalies with respect to the baseline periods 1981-2000, 1961-1990 or 1981-2010, and cover the period 1861 to 2100.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section." }, { "ob_id": 26112, "uuid": "9f8dfaf790644dbcb2c3f69f409a70d6", "short_code": "ob", "title": "UKCP18 Probabilistic Projections on a 25km grid over the UK for 1961-2100", "abstract": "This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline periods 1961-1990, 1981-2000 and 1981-2010, and cover the period 1 Dec 1960 to 30 Nov 2099. Gridded data on a 25km grid over the United Kingdom, the Isle of Man and the Channel Islands is provided. Further information on this dataset and UKCP18 can be found under UK Climate Projections (UKCP18) guidance and reports in the documentation section.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to under UK Climate Projections News in the documentation section.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to under UK Climate Projections News in the documentation section." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 110961, 112283, 112284, 112285, 112287, 112289, 112286, 204869, 112288 ], "onlineresource_set": [ 25965, 27321, 27322 ], "project_set": [ 26111 ] }, { "ob_id": 26157, "uuid": "f1a2fc3c120f400396a92f5de84d596a", "short_code": "coll", "title": "UKCP18 Global Climate Model Projections for the entire globe", "abstract": "Global climate model runs from 1900-2100 produced by the Met Office for UK Climate Projections 2018 (UKCP18) using the HadGEM3 climate model. The data is available at daily and monthly temporal resolutions on a N216 Gaussian grid which has a 60km resolution over the UK.", "keywords": "UKCP18, UKCP, Climate, Global, Simulations, GCM, Historical, Projections", "publicationState": "published", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 212 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26117, "uuid": "97bc0c622a24489aa105f5b8a8efa3f0", "short_code": "ob", "title": "UKCP18 Global Projections at 60km Resolution for 1900-2100", "abstract": "Global climate model projections for the CMIP5 RCP8.5 emissions scenario produced as part of the UK Climate Projection 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe set of 28 projections is a combination of 15 coupled model simulations produced by the Met Office Hadley Centre, and 13 coupled simulations from CMIP5 contributed by different climate modelling centres.\r\n\r\nThis data set provides information on changes in climate across the entire globe from 1900 to 2100 for RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across many climate variables at different times and spatial locations.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 110962, 112290, 112291, 112292, 112294, 112296, 112293, 204941, 112295 ], "onlineresource_set": [ 25966, 27313, 27314 ], "project_set": [ 26111 ] }, { "ob_id": 26158, "uuid": "45b332cd72c14fb3beddb4bf05077c97", "short_code": "coll", "title": "UKCP18 Regional Climate Model Projections for the NW Europe Region", "abstract": "Regional climate model runs from the North-West Europe regional climate model runs from 1980-2080 produced by the Met Office for UK Climate Projections 2018 (UKCP18). The data is available at daily and monthly temporal resolutions on a 12km latitude-longitude grid.", "keywords": "UKCP18, UKCP, Climate, NW-Europe, Simulations, RCM", "publicationState": "published", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 212 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26903, "uuid": "8c6c0ae2c25947168826a70d2241b797", "short_code": "ob", "title": "UKCP18 Regional Projections at 12km Resolution for 1980-2080", "abstract": "Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains 12km data for Europe on the 12km rotated pole grid. Further information on this dataset and UKCP18 can be found in the documentation section." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 110963, 112297, 112298, 112299, 112301, 112303, 112300, 204934, 112302 ], "onlineresource_set": [ 25967, 27317, 27318 ], "project_set": [ 26111 ] }, { "ob_id": 26160, "uuid": "0dc7d552eb674036800670241fa31dcf", "short_code": "coll", "title": "UKCP18 High Temporal Resolution Short-term Events for Marine Case Studies", "abstract": "Short event case studies for UK waters produced by the Met Office for UK Climate Projections 2018 (UKCP2018). Data is available at 6-minute and 15-minute temporal resolution.", "keywords": "UKCP18, UKCP, Climate, Marine, Case Studies, Tides", "publicationState": "published", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 212 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26020, "uuid": "e5297a0c0329426380d4cd6e58c48f45", "short_code": "ob", "title": "UKCP18 Simulated Impact of Mean Sea Level Change on Tidal Characteristics around the UK", "abstract": "The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone. The data were produced by the Met Office Hadley Centre. The data were produced to investigate the impact of simulated mean sea level increase on UK coastal tides. To produce the data, the CS3 continental shelf model was used to simulate the tides under various different amounts of mean sea level increase (simulated by simply increasing the bathymetry). The data are the resulting simulated sea surface elevations above the mean sea level. The data covers a period of about 28 days (one spring-neap cycle), and applies to the UK coast.\r\n\r\nThere are several caveats which should be noted when using the ‘UKCP18 Simulated Impact of Mean Sea Level Change on Tidal Characteristics around the UK’ dataset:\r\n1.\tThe spin-up period has been included in the data. It takes about 48 hours to spin up to a realistic tide so users should remove the first 48 hours of data, or conduct their own analysis to assess how much spin-up time to remove, in order to get a realistic representation of the tide.\r\n2.\tA land-sea mask has not been applied to the data so users should take care to ensure they are only using data from sea locations.\r\n3.\tThere is a rim of zeros around the edge of the data which should be ignored.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section." }, { "ob_id": 26019, "uuid": "58c393f773504caaad48cdb6310e17b2", "short_code": "ob", "title": "UKCP18 Short Event Case Studies of Historical and Future Sea Surface Elevation around the UK", "abstract": "The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 RCP8.5 simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 2007 to 2099, and applies to the UK coast.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 110965, 112314, 112315, 112316, 112318, 112320, 112317, 204913, 112319 ], "onlineresource_set": [ 25971, 27319, 27320 ], "project_set": [ 26015 ] }, { "ob_id": 26163, "uuid": "72407f08415c4b868c85b934033691b3", "short_code": "coll", "title": "UKCP18 Time-mean Sea Level Projections", "abstract": "Time-mean Sea Level Projections for the UK produced by the Met Office for UK Climate Projections 2018 (UKCP2018). Data has been produced by standard and exploratory methods.", "keywords": "UKCP18, UKCP, Climate, Marine, sea level", "publicationState": "published", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 212 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26120, "uuid": "0f8d27b1192f41088cd6983e98faa46e", "short_code": "ob", "title": "UKCP18 21st century time-mean sea level projections around the UK for 2007-2100", "abstract": "The UKCP18 21st century sea level projections are provided as spatially a continuous dataset around the UK coastline. The projections are rooted in CMIP5 climate model simulations and the process-based methods described in IPCC AR5 (Church et al, 2013). The data consist of annual time series of the projected change in the time-mean coastal water level relative to the average value for the period 1981-2000. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). Nine percentiles are provided to characterise the projection uncertainty. The 5th, 50th and 95th percentiles are equivalent to the IPCC AR5 lower, central, and upper estimate of projected sea level change, based on underlying modelling uncertainty.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThis dataset was updated in March 2023 to correct a minor processing error in the earlier version of the UKCP18 site-specific sea level projections relating to the adjustment applied to convert from the IPCC AR5 baseline of 1986-2005 to the baseline period of 1981-2000. The update results in about a 1 cm increase compared to the original data release for all UKCP18 site-specific sea level projections at all timescales. Further details can be found in the accompanying technical note." }, { "ob_id": 26122, "uuid": "a077f4058cda4cd4b37ccfbdf1a6bd29", "short_code": "ob", "title": "UKCP18 exploratory extended time-mean sea level projections around the UK for 2007-2300", "abstract": "The UKCP18 exploratory extended time-mean sea level projections are provided as spatially a continuous dataset around the UK coastline for the period 2007-2300. These exploratory projections have been devised to be used seamlessly with the UKCP18 21st Century projections and provide very similar values for the period up to 2100. Users should be aware that post-2100 projections have a far greater degree of uncertainty than the 21st Century projections and should therefore be treated as illustrative of the potential future changes. Note that we cannot rule out substantially larger sea level rise in the coming centuries than is represented in the projections presented here. The data consist of annual time series of the projected change in the time-mean coastal water level relative to the average value for the period 1981-2000. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). As with the 21st Century projections, nine percentiles are provided to characterise the projection uncertainty, based on underlying modelling uncertainty. However, users should view these uncertainties with a much lower degree of confidence for the period post-2100.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThis dataset was updated in March 2023 to correct a minor processing error in the earlier version of the UKCP18 site-specific sea level projections relating to the adjustment applied to convert from the IPCC AR5 baseline of 1986-2005 to the baseline period of 1981-2000. The update results in about a 1 cm increase compared to the original data release for all UKCP18 site-specific sea level projections at all timescales. Further details can be found in the accompanying technical note." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 110966, 112321, 112322, 112323, 112325, 112327, 112324, 204868, 112326 ], "onlineresource_set": [ 25972, 27309, 27310 ], "project_set": [ 26015 ] }, { "ob_id": 26164, "uuid": "d2eea061026240eb8a2f9cc64a691338", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 03.2 data collection", "abstract": "Soil Moisture data (version 03.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2014-12-31 and the Active product covering 1991-08-05 to 2014-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD) or the paper by Wagner 2012, both available in linked documentation. Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014", "keywords": "ESA, Soil Moisture, CCI", "publicationState": "citable", "dataPublishedTime": "2018-06-25T10:45:47", "doiPublishedTime": "2018-06-29T11:15:17", "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24841, "uuid": "c4f117ba38544e8a80338b6cf1000a91", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 03.2", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v03.2 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 24714, "uuid": "71e20f6a7d6e4ec392f9afcbce14eced", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 03.2", "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v03.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2015-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 24715, "uuid": "7c7a38b2d2ce448b99194bff85a85248", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 03.2", "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satelllite instruments. \r\n\r\nThe product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2015-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors associated with it is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 24712, "uuid": "c657ee46354d480b8cf668addf0b43f2", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 03.2", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2,. and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v03.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2015-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "identifier_set": [ 9622 ], "responsiblepartyinfo_set": [ 109395, 109396, 109397, 109400, 109401, 109402, 109987, 109398, 109405, 109988, 109989, 109990, 109991, 109992, 109993, 109994, 109995, 109996 ], "onlineresource_set": [ 24734, 24737, 24736, 24900, 24901, 24902, 24735, 87593, 94839, 94840 ], "project_set": [ 13332 ] }, { "ob_id": 26165, "uuid": "3729b3fbbb434930bf65d82f9b00111c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 02.2 data collection", "abstract": "Soil Moisture data (version 02.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2014-12-31 and the Active product covering 1991-08-05 to 2014-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD) or the paper by Wagner 2012, both available in linked documentation. Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321", "keywords": "ESA, Soil Moisture, CCI", "publicationState": "citable", "dataPublishedTime": "2018-06-22T15:46:23", "doiPublishedTime": "2018-06-29T11:11:30", "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14401, "uuid": "953545f5c4454952a26db065bbca004f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 02.2", "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v02.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2014-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version or the paper by Wagner 2012, both available in the documentation section. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 14397, "uuid": "33ac39755cad49e38e34b048678a67aa", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 02.2", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v02.2 Soil Moisture CCI data.\r\n\r\nFor further information on these and the references associated with them please see the Product Specification Document (PSD), a link to which is provided in the documentation section. The \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website or within the Product Specification Document." }, { "ob_id": 14403, "uuid": "663a557e848a4a9f8f0d205c6b3cb7f6", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 02.2", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v02.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2014-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 14399, "uuid": "c89cb1c86f42456bb84e49ea06621c7e", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 02.2", "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. \r\n\r\nThe v02.2 product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2014-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors associated with it is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" } ], "identifier_set": [ 9621 ], "responsiblepartyinfo_set": [ 109406, 109408, 109409, 109410, 109411, 109412, 109910, 109414, 109416, 109911, 109912, 109913, 109914, 109915, 109916, 109917, 109918, 109919, 109920, 109921, 109922, 109923, 109924 ], "onlineresource_set": [ 24742, 24745, 24741, 24744, 24743, 87850, 87615, 94678, 94679 ], "project_set": [ 13332 ] }, { "ob_id": 26166, "uuid": "b810601740bd4848b0d7965e6d83d26c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 03.3 data collection", "abstract": "Soil Moisture data (version 03.3) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014", "keywords": "ESA, Soil Moisture, CCI", "publicationState": "citable", "dataPublishedTime": "2018-06-25T12:54:37", "doiPublishedTime": "2018-06-29T11:17:56", "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26173, "uuid": "0f4570c780ba41b19a362e774509c883", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 03.3", "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v03.3 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 26232, "uuid": "7f320bf20d9e4c7994031c3b0a2170aa", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 03.3", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v03.3 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 26237, "uuid": "5644c9ab30ef499ba1cc9ecfc6b6474c", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 03.3", "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v03.3 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 26245, "uuid": "1d28a3d5d74d4439a2be8938dfb550f8", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 03.3", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v03.3 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using the complete three references as follows:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "identifier_set": [ 9623 ], "responsiblepartyinfo_set": [ 109417, 109418, 109422, 109423, 109424, 109425, 110038, 109420, 110039, 109427, 110040, 110041, 110042, 110043, 110044, 110045, 110046, 110047 ], "onlineresource_set": [ 24746, 24749, 24747, 24748, 25017, 25018, 25019, 25077, 25078, 25079, 25081, 25080, 25082, 87612, 87613, 94686 ], "project_set": [ 13332 ] }, { "ob_id": 26170, "uuid": "3a8a94c3fa464d68b6d70df291afd457", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 04.2 data collection", "abstract": "Soil Moisture data (version 04.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014", "keywords": "ESA, Soil Moisture, CCI", "publicationState": "citable", "dataPublishedTime": "2018-06-25T13:54:11", "doiPublishedTime": "2018-06-29T11:21:15", "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26234, "uuid": "f77cbcfbb6214448aebaa2119d829692", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 04.2", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v04.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 26242, "uuid": "0869e3b34fa4465a911e2588396ff1ec", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 04.2", "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v04.2 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 26247, "uuid": "55bff4add65d489e86c195edbae8f970", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 04.2", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v04.2 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 26239, "uuid": "a4f9546935a644d3b3260b7f6a0a183f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 04.2", "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v04.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "identifier_set": [ 9624 ], "responsiblepartyinfo_set": [ 109434, 109428, 109430, 109431, 109432, 109433, 110091, 109436, 109438, 110092, 110093, 110094, 110095, 110096, 110097, 110098, 110099, 110100 ], "onlineresource_set": [ 24754, 24757, 24756, 24755, 25050, 25049, 25051, 25094, 25096, 25098, 25099, 25095, 25097, 94841 ], "project_set": [ 13332 ] }, { "ob_id": 26171, "uuid": "b11f3fa3303e46e6b0d44b058947a3f5", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 05.2 data collection", "abstract": "Soil Moisture data (version 05.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments..\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31 and the ACTIVE product covering 1991-08-05 to 2019-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070", "keywords": "ESA, Soil Moisture, CCI", "publicationState": "citable", "dataPublishedTime": "2020-11-23T14:36:41", "doiPublishedTime": "2020-12-01T14:45:00", "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26236, "uuid": "dd3da2570363429791b51120bdd29c02", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 05.2", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.\r\n\r\nThe v05.2 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, { "ob_id": 26241, "uuid": "f0580e34da524770b0a5d43c033b33dc", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE Product, Version 05.2", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v05.2 PASSIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, { "ob_id": 26249, "uuid": "91719888102e4c81b7884cb57cb2f3e3", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 05.2", "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v05.2 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, { "ob_id": 26244, "uuid": "057dd6c36f0741d3b97f9eee688b7835", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 05.2", "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v05.2 COMBINED product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" } ], "identifier_set": [ 10794 ], "responsiblepartyinfo_set": [ 109440, 109441, 109439, 109447, 109446, 109444, 109445, 109442, 109449, 141770, 141771, 141772, 110177, 110178, 110182, 141773, 110183, 110179, 141774, 141775 ], "onlineresource_set": [ 24760, 25052, 25053, 24759, 25054, 41791, 41792, 94801, 94802, 94803, 94804 ], "project_set": [ 13332 ] }, { "ob_id": 26172, "uuid": "f4f77c55fd304ada9bfe2195927a053b", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 02.1 data collection", "abstract": "Soil Moisture data (version 02.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2014-12-31 and the Active product covering 1991-08-05 to 2014-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD) or the paper by Wagner 2012, both available in linked documentation. Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using all three references as follows:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321", "keywords": "ESA, Soil Moisture, CCI", "publicationState": "citable", "dataPublishedTime": "2018-06-22T13:57:41", "doiPublishedTime": "2018-06-29T11:02:28", "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 12881, "uuid": "a1ff285fb94c4c359269b1a12df957ec", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 02.1", "abstract": "The Soil Moisture CCI Passive dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer and radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer and radiometer soil moisture products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v02.1 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2013-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors of the dataset is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 12890, "uuid": "4eec83c4bbec4c8ea873188d90fc243f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 02.1", "abstract": "Ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v02.1 Soil Moisture CCI data.\r\n\r\nFor further information on these and the references associated with them please see the Product Specification Document (PSD), a link to which is provided in linked documentation. The \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website or within the Product Specification Document." }, { "ob_id": 12878, "uuid": "515df65d974541df82740062974212aa", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 02.1", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v02.1 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2013-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors of the dataset is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 12886, "uuid": "2cc1cbc906444322845e6a51916a1f03", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 02.1", "abstract": "The Combined Soil Moisture CCI dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these both being fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. \r\n\r\nThe v02.1 product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2013-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors associated with it is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" } ], "identifier_set": [ 9620 ], "responsiblepartyinfo_set": [ 109451, 109453, 109454, 109455, 109456, 109457, 109832, 109459, 109833, 109461, 109834, 109835, 109836, 109837, 109838, 109839, 109840, 109841, 109842, 109843, 109844, 109845, 109846 ], "onlineresource_set": [ 24765, 24766, 24769, 24768, 24767, 94837, 94838 ], "project_set": [ 13332 ] }, { "ob_id": 26184, "uuid": "dbd451271eb04662beade68da43546e1", "short_code": "coll", "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)", "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA.", "keywords": "MIDAS, Met Office, meteorology, UK, land, daily, hourly", "publicationState": "published", "dataPublishedTime": "2019-02-12T10:22:26", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 69 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 31890, "uuid": "1dc8578eb7434a7d8a661744d53eedf9", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v202007", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2019.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 27816, "uuid": "6ad6792f44c84c228651b01d182d9d73", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v201908", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2018. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, { "ob_id": 27818, "uuid": "6c441aea187b44819b9e929e575b0d7e", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v201908", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, { "ob_id": 40649, "uuid": "c21639861fb54623a749e502ebac74ed", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v202308", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, { "ob_id": 42337, "uuid": "8606115371e44b079e25d479cfec465c", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v202407", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2023. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version (202308) of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, { "ob_id": 38067, "uuid": "8bcf6925cddc4681b96f94d424537b9e", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v202207", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2021. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, { "ob_id": 27815, "uuid": "b37382e8c1e74b849831a5fa13afdcae", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201908", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2018. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, { "ob_id": 32973, "uuid": "d399794d81fa41779a925b6d4758a5cd", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v202107", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2020. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. Of particular note, however, is that as well as including data for 2020, historical data recovery has added further data for Eastbourne (1887-1910).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, { "ob_id": 27819, "uuid": "d6bbe115245042dc93ee68caa253d60b", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v201908", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2018.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 32968, "uuid": "92e823b277cc4f439803a87f5246db5f", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v202107", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2020. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. Of particular note, however, is that as well as including data for 2020, historical data recovery has added further data for Eskdalemuir (1915-1948) and Eastbourne (1887-1910).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, { "ob_id": 40656, "uuid": "68920a29caf44f21be6371d9f87f578b", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v202308", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2022.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 26899, "uuid": "11c15f2640f541d4847dafe9be1bb90a", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v201901", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2017. For further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 42334, "uuid": "6c619c67138843b8839a5788ac749e12", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v202407", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2023.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, { "ob_id": 27820, "uuid": "ddcfd8bb1ff44cd2855e81838b40b17c", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v201908", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 32970, "uuid": "f7ae919f96b44a1c9695f40a9cf988dd", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v202107", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2020.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, { "ob_id": 44579, "uuid": "76e54f87291c4cd98c793e37524dc98e", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v202507", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light. \r\n\r\nFor details about the different measurements made and the limited number of sites making them please see the MIDAS Solar Irradiance table linked to in the online resources section of this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2024.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2024.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 32969, "uuid": "cabc37d867fa4f2a84302350df908693", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v202107", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2020.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 44580, "uuid": "406b7689394542919d682e46afb7c819", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v202507", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2024.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2024.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 31899, "uuid": "85b9dad7af814bfa9047a525927257f4", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v202007", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2019.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 32974, "uuid": "3bd7221d4844435dad2fa030f26ab5fd", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v202107", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2020.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. Of particular note, however, is that as well as including data for 2020, historical data recovery has added further data for Eskdalemuir (1914-1944) and Eastbourne (1887-1910).\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, { "ob_id": 38069, "uuid": "4b44cec2f9a846f39d5007983b7eaaab", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v202207", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2021. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021, and additional historical data for Sheffield (South Yorkshire, 1898-1935).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, { "ob_id": 40651, "uuid": "220b9b8ffbed43fcbbd323e739118f6c", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v202308", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2022. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, { "ob_id": 32972, "uuid": "4d48efaaeb7f47a7963df75d6d1dbdc5", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v202107", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2020.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 27164, "uuid": "1e040656ae0a4646acafbef6144b10f2", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v201901", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2017.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 31883, "uuid": "8d85f664fc614ba0a28af3a2d7ef4533", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v202007", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2019.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. Of particular note, however, is that as well as including data for 2019, historical data recovery has added temperature and weather data for Bude (1937-1958), Teignmouth (1912-1930), and Eskdalemuir (1915-1948).\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, { "ob_id": 40650, "uuid": "3f3809143a224c84962f52757d668f77", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v202308", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2022. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version (202207) of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, { "ob_id": 42331, "uuid": "91cb9985a6c2453d99084bde4ff5f314", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v202407", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2023.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 44582, "uuid": "9244f715ecfd4e74b0b6200de55e1b1a", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v202507", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2024. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2024.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, { "ob_id": 40654, "uuid": "87eb67c08f5c4518a3723d0ca2d9b4b1", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v202308", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light. \r\n\r\nFor details about the different measurements made and the limited number of sites making them please see the MIDAS Solar Irradiance table linked to in the online resources section of this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 40653, "uuid": "85596b72ff024837a64bf22a8d1a72be", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v202308", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2022.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 26896, "uuid": "c58c1af69b9745fda4cdf487a9547185", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v201901", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2017.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, { "ob_id": 38071, "uuid": "15deeb29cdcd4524b07560e5aad45ded", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v202207", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2021. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version (202107) of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021, and additional historical data for Colmonell (Ayrshire, 1924-1960), Camps Reservoir (Lanarkshire, 1934-1960), and Greenock (Renfrewshire, 1910-1960).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, { "ob_id": 44581, "uuid": "8ddfd4dd5af443f9ad382cd77366d877", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v202507", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2024. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version (202407) of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2024.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, { "ob_id": 38068, "uuid": "fa83484e57854d6fbde16ff945ff6dc0", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v202207", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2021.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 31885, "uuid": "f7e09e89de234c15964a4cc7a75f3f74", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v202007", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2019.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 42336, "uuid": "b7c6295b72c54fa9bcd8308fea2727e7", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v202407", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2023. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, { "ob_id": 26901, "uuid": "a7ba08d073eb40a9aab5e312f371d007", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v201901", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2017.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 38073, "uuid": "4ecbf3fa1b084c5a9080248433275124", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v202207", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2021.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 44585, "uuid": "bed3b1f2ce0c4ba780927e9fac04f696", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v202507", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2024.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2024.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 44586, "uuid": "c0cd9756b5234f1881c375fb6bb94245", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v202507", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2024. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2024.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, { "ob_id": 40655, "uuid": "c9663d0c525f4b0698f1ec4beae3688e", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v202308", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2022.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, { "ob_id": 27817, "uuid": "cb47cc464c5a41de8c718d117437b4e6", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v201908", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2018. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, { "ob_id": 38074, "uuid": "e3a7f3336ff8464f9ae6534a8e8676e5", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v202207", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light. \r\n\r\nFor details about the different measurements made and the limited number of sites making them please see the MIDAS Solar Irradiance table linked to in the online resources section of this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2021.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 26438, "uuid": "ec54d5e5288a4ebb8c7ad2a1ef6aec42", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v201901", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2017. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, { "ob_id": 31887, "uuid": "ec9e894089434b03bd9532d7b343ec4b", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v202007", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2019. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, { "ob_id": 26892, "uuid": "0049795739e44310a4982e26d8e26748", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v201901", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2017. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, { "ob_id": 44584, "uuid": "99173f6a802147aeba430d96d2bb3099", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v202507", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2024.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2024.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, { "ob_id": 27821, "uuid": "9972bc173ef94068b2070d4b26f849a7", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v201908", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 31884, "uuid": "f8612c43a1244fda9463787313d3892a", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v202007", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2019. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. Of particular note, however, is that as well as including data for 2019, historical data recovery has added temperature and weather data for Bude (1937-1958), Teignmouth (1912-1930), and Eskdalemuir (1915-1948).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, { "ob_id": 27822, "uuid": "a58b9c8a724e4ec795a40a74455462b7", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v201908", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2018.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, { "ob_id": 42330, "uuid": "a6bb3e8def544b5790d4b05a6f37f901", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v202407", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2023.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 42333, "uuid": "0afba628c2f4462da68b0a81ebf1ff4c", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v202407", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light. \r\n\r\nFor details about the different measurements made and the limited number of sites making them please see the MIDAS Solar Irradiance table linked to in the online resources section of this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2023.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 32971, "uuid": "d6bcf4171c2f4754a7455d00deda0f72", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v202107", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2020. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, { "ob_id": 42332, "uuid": "c50776e4903942cdb329589da70b83fe", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v202407", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2023.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, { "ob_id": 31889, "uuid": "064f3a982cfc4b07bc5de627cd8676f1", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v202007", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2019. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. Of particular note, however, is that as well as including data for 2019, historical data recovery has added temperature and weather data for Bude (1937-1958), Teignmouth (1912-1930), and Eskdalemuir (1915-1948).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, { "ob_id": 42335, "uuid": "8070d47e1b7340468fa7cf654dee938b", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v202407", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2023. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, { "ob_id": 26437, "uuid": "a39add95a8dc49709f6e984c020c8dbc", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201901", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2017. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, { "ob_id": 26894, "uuid": "7aaa582fb00246b794dc85950f1be265", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v201901", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2017.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, { "ob_id": 31888, "uuid": "77187ac1e0a341ca993c3366f8c59c3c", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v202007", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2019.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, { "ob_id": 40652, "uuid": "1ce37461affc43bbbd78beaaacf5911d", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v202308", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2022. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, { "ob_id": 38070, "uuid": "6180fb7ed76a442eb1b8f3f152fd08d7", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v202207", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2021.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2021, and additional historical data for Sheffield (South Yorkshire, 1882-1935).\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, { "ob_id": 32975, "uuid": "625f5ea4ddac4578a2aacf47bcf39657", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v202107", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2020.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, { "ob_id": 44583, "uuid": "c75ca7291a5048739010380dce6ebc99", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v202507", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2024.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, { "ob_id": 38072, "uuid": "64f5d7be890a4ac08cb2b4e78eb5fcc1", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v202207", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2021.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 109561, 109555, 109556, 109560, 109554, 109558, 109559, 109557, 110982 ], "onlineresource_set": [ 24862, 24852, 42169, 24863, 24853, 24851 ], "project_set": [ 1186 ] }, { "ob_id": 26216, "uuid": "b4d24b3df3754b9d9028447eb3cd89c6", "short_code": "coll", "title": "UKCP18 Regional Climate Model Projections for the UK", "abstract": "UK-scale data from regional climate model for the UK from North-West Europe regional climate model runs from 1980-2080 produced by the Met Office for UK Climate Projections 2018 (UKCP18). The data is available at various temporal resolutions: daily, monthly, seasonal and annual and various spatial resolutions: on a 12km OSGB grid, for major UK river catchments and each of the countries of the United Kingdom.", "keywords": "UKCP18, UKCP, Climate, UK, Simulations, RCM", "publicationState": "published", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 212 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26213, "uuid": "589211abeb844070a95d061c8cc7f604", "short_code": "ob", "title": "UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080", "abstract": "\"Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains 12km data for the United Kingdom, the Isle of Man and the Channel Islands provided on the Ordnance Survey's British National Grid. Further information on this dataset and UKCP18 can be found in the documentation section." }, { "ob_id": 26210, "uuid": "22a3c9e91b4446df9569a44e43bbfffc", "short_code": "ob", "title": "UKCP18 Regional Projections by UK River Basins for 1980-2080", "abstract": "Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 23 river basin regions across the UK. Further information on this dataset and UKCP18 can be found in the documentation section." }, { "ob_id": 26207, "uuid": "b70faeaf5f7a445cbfde3fc968150767", "short_code": "ob", "title": "UKCP18 Regional Projections for UK Countries for 1980-2080", "abstract": "Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 8 \"\"country\"\" regions including Channel Islands, England, England and Wales, Isle of Man, Northern Ireland, Scotland, United Kingdom, Wales. Further information on this dataset and UKCP18 can be found in the documentation section." }, { "ob_id": 26204, "uuid": "eabb6bced80049e790c7fe1c9e917d1e", "short_code": "ob", "title": "UKCP18 Regional Projections by Administrative Regions over the UK for 1980-2080", "abstract": "Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980,-30/11/2080 for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 16 administrative regions across the UK. Further information on this dataset and UKCP18 can be found in the documentation section." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 110964, 112304, 112305, 112306, 112308, 112310, 112307, 204879, 112309 ], "onlineresource_set": [ 25969, 27315, 27316 ], "project_set": [] }, { "ob_id": 26222, "uuid": "43fdd19d25b44ec2a9176288d1085ef0", "short_code": "coll", "title": "Atmospheric Chemistry In The Earth System (ACITES)", "abstract": "The Atmospheric Chemistry In The Earth System (ACITES) Network has been funded by the Natural Environment Research Council to bring together the atmospheric chemistry process community and the Earth system modelling community. \r\n\r\nThe ACITES data collection includes: Monthly global surface ozone concentration and ozone dry deposition flux fields from models and observation , land cover data. The data collection also includes the python code used to create the netCDF data files.", "keywords": "ACITES, Atmospheric Chemistry, Ozone, Land Surface", "publicationState": "published", "dataPublishedTime": "2018-10-16T10:07:22", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26227, "uuid": "b7953003f065461c9568e3fd9a13460f", "short_code": "ob", "title": "ACITES: Monthly ozone observations from European and North American sites and CASTNET data.", "abstract": "Monthly surface ozone concentration and ozone dry deposition flux fields from observations in Europe and North America and from CASTNET data saved in NetCDF format." }, { "ob_id": 26224, "uuid": "89a34bc430834422bef1f72e2172e3b9", "short_code": "ob", "title": "ACITES: Monthly global surface ozone concentration and ozone dry deposition flux fields from models", "abstract": "Monthly global surface ozone concentration and ozone dry deposition flux fields from models participating in the UN/ECE Task Force on Hemispheric Transport of Air Pollution (TF HTAP) intercomparison. Models were driven by meteorological fields for the year 2001.\r\n\r\nData are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format." }, { "ob_id": 26225, "uuid": "b117e4bd7f754d22a65fc823694fa388", "short_code": "ob", "title": "ACITES: Land cover data for the Olson and Global Land Cover Facility data sets", "abstract": "Model grid cell areas and land cover data for the Olson and Global Land Cover Facility. Data are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format.\r\nThe Olson land cover dataset was developed from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993.\r\nThe Global Land Cover Facility dataset was developed from monthly satellite sensor data of NDVI values for 1987." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 109679, 109677, 112054, 112055, 130052, 130053, 130054, 141570, 109681, 109676, 109678 ], "onlineresource_set": [ 25585, 41699 ], "project_set": [ 12136 ] }, { "ob_id": 26331, "uuid": "cdecaea11e59472b8800d5d938a3c8ee", "short_code": "coll", "title": "MACSSIMIZE: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE).", "keywords": "MACSSIMIZE, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2018-04-18T13:19:19", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26355, "uuid": "49834bb8b0884eb4aeb8b67e87c4a426", "short_code": "ob", "title": "FAAM C089 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26351, "uuid": "68c905840fd14d9782fff72c945303e8", "short_code": "ob", "title": "FAAM C088 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26339, "uuid": "b04281cc10c44d9dab1eb2e4eb19d5b8", "short_code": "ob", "title": "FAAM C085 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26371, "uuid": "a51720f607a8453fb4bbffd348a49ee9", "short_code": "ob", "title": "FAAM C093 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26359, "uuid": "466e7aa2f62548d88a44b3ca3f012f3f", "short_code": "ob", "title": "FAAM C090 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26343, "uuid": "acd351de266a4030be8fe600ea3f849d", "short_code": "ob", "title": "FAAM C086 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26330, "uuid": "8848c9dee32c422aa3253b186165ac3e", "short_code": "ob", "title": "FAAM C083 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26347, "uuid": "35ecd42642ee45b68f733b43098de2bb", "short_code": "ob", "title": "FAAM C087 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26367, "uuid": "6f48c449731b42c5a9081d36de2d333d", "short_code": "ob", "title": "FAAM C092 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." }, { "ob_id": 26363, "uuid": "9b921e31f33e4115b6d2d74dce097489", "short_code": "ob", "title": "FAAM C091 MACSSIMIZE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE) project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 110476, 110477, 110478, 110481, 110482, 110483, 110484, 110485, 110479, 110480 ], "onlineresource_set": [], "project_set": [ 25113 ] }, { "ob_id": 26459, "uuid": "6accd46663bc4669afaac418f2bf498e", "short_code": "coll", "title": "Sentinel 5 Precursor: Level 2 data", "abstract": "Need some info!", "keywords": "", "publicationState": "working", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 148 ], "discoveryKeywords": [], "member": [ { "ob_id": 27467, "uuid": "b33ec61670644124ab4af661009ec507", "short_code": "ob", "title": "Sentinel 5P: Methane (CH4) Total Column level 2 data", "abstract": "This dataset contains level 2 (geolocated) total column Methane (CH4) data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel 5P satellite.\r\n\r\nSentinel 5 Precursor (S5P) was launched on the 13th October 2017 carrying TROPOMI. Methane (CH4) is an important atmospheric trace gas for our understanding of tropospheric chemistry. TROPOMI aims at providing CH4 column concentrations with high sensitivity to the Earth’s surface, good spatiotemporal coverage, and sufficient accuracy to facilitate inverse modeling of sources and sinks. TROPOMI uses absorption information from the Oxygen-A Band (760nm) and the SWIR spectral range to monitor CH4 abundances in the Earth's atmosphere.\r\n\r\nThe Sentinel-5 Precursor mission flies in loose formation (about 3.5 – 5 minutes behind) with the S-NPP (SUOMI-National Polar-orbiting Partnership) mission to use VIIRS (Visible Infrared Imaging Radiometer Suite) cloud information to select cloud-free TROPOMI pixels for high quality methane retrieval." }, { "ob_id": 30115, "uuid": "d69dccc3b50041bb91a126b85e9154d0", "short_code": "ob", "title": "Sentinel 5P: Suomi-NPP VIIRS cloud level 2 data", "abstract": "The S5P NPP Cloud product contains information on cloud and scene homogeneity for TROPOMI scenes, derived from operational products from the VIIRS (Visible Infra-red Imaging Radiometer Suite) on board the Suomi National Polar-orbiting Partnership (S-NPP) platform. S5P operates in loose formation orbit with NPP, so that measurements from VIIRS are well co-located with TROPOMI, with a time difference of about 3.5 minutes. There is no specific validation of auxiliary products within the S5P Mission Performance Centre.\r\n\r\nSentinel 5 Precursor (S5P) was launched on the 13th October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). The TROPOMI instrument onboard S5P is a nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. The instrument uses passive remote sensing techniques to attain its objective by measuring, at the Top Of Atmosphere (TOA), the solar radiation reflected by and radiated from the earth.\r\n\r\nThe S5P level 2 methane product is dependent on having information on cloud occurrence at spatial resolution finer than that achievable from TROPOMI itself. This information is also useful for other purposes, including assessing the influence of cloud on other L2 products and issues related to spatial co-registration. NPP-Cloud was therefore developed as a level 2 auxiliary product to describe cloud in the TROPOMI field of view (FOV), using co-located observations of VIIRS on the U.S. S-NPP. \r\n\r\nThe main information contained in the S5P-NPP product is:\r\n\r\n1. A statistical summary for each S5P FOV of the NPP-VIIRS L2 Cloud Mask (VCM).\r\n2. The mean and standard deviation of the sun-normalised radiance in a number of VIIRS moderate resolution bands.\r\nThis information is provided for three S5P spectral bands (to account for differences in spatial sampling)." }, { "ob_id": 26441, "uuid": "e34eaffcf6bb4f3c87fffe0814f5c9bf", "short_code": "ob", "title": "Sentinel 5P: Nitrogen Dioxide (NO2) Total Column level 2 data", "abstract": "Sentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). These data products provide geolocated total, tropospheric, or stratospheric Nitrogen dioxide concentrations. The TROPOMI NO2 data products pose an improvement over previous NO2 data sets, particularly in their unprecedented spatial resolution (7×3.5 km2), but also in the separation of the stratospheric and tropospheric contributions of the retrieved slant columns, and in the calculation of the air-mass factors used to convert slant to total columns.\r\n\r\nNitrogen dioxide (NO2) and nitrogen oxide (NO) together are usually referred to as nitrogen oxides (NOx = NO + NO2). They are important trace gases in the Earth’s atmosphere, present in both the troposphere and the stratosphere. They enter the atmosphere as a result of anthropogenic activities (notably fossil fuel combustion and biomass burning) and natural processes (such as microbiological processes in soils, wildfires and lightning). During the daytime, i.e. in the presence of sunlight, a photochemical cycle involving ozone (O3) converts NO into NO2 (and vice versa) on a timescale of minutes, so that NO2 is a robust measure for concentrations of nitrogen oxides. Tropospheric and stratospheric concentrations of NO2 are monitored all over the world by a variety of instruments either ground-based, in-situ (balloon, aircraft), or satellite-based each with its own specific advantages." }, { "ob_id": 26461, "uuid": "84ff4498eab64f6885a0e2391b993064", "short_code": "ob", "title": "Sentinel 5P: Carbon Monoxide (CO) Total Column level 2 data", "abstract": "Sentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). TROPOMI on the Sentinel 5 Precursor (S5P) satellite observes the CO global abundance exploiting clear-sky and cloudy-sky Earth radiance measurements in the 2.3 µm spectral range of the shortwave infrared (SWIR) part of the solar spectrum. TROPOMI clear sky observations provide CO total columns with sensitivity to the tropospheric boundary layer. For cloudy atmospheres, the column sensitivity changes according to the light path. Carbon monoxide (CO) is an important atmospheric trace gas for our understanding of tropospheric chemistry. In certain urban areas, it is a major atmospheric pollutant. The main sources of CO are the combustion of fossil fuels, biomass burning, and atmospheric oxidation of methane and other hydrocarbons. Whereas fossil fuel combustion is the main source of CO at Northern mid-latitudes, the oxidation of isoprene and biomass burning play an important role in the tropics." }, { "ob_id": 37840, "uuid": "ba5618b8ad6540c4b16df4877350464c", "short_code": "ob", "title": "Sentinel 5P: Cloud (CLOUD) level 2 data", "abstract": "This dataset contains data that can be used for cloud correction of satellite trace gas retrievals these include: cloud fraction, cloud optical thickness (albedo), and cloud-top pressure (height).\r\n\r\nSentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). Cloud parameters from TROPOMI are not only used for enhancing the accuracy of trace gas retrievals but also to extend the satellite data record of cloud information derived from oxygen A-band measurements initiated with the Global Ozone Monitoring Experiment (GOME).\r\n\r\nThe TROPOMI/S5P cloud properties retrieval is based on the Optical Cloud Recognition Algorithm (OCRA) and Retrieval of Cloud Information using Neural Networks (ROCINN) algorithms currently being used in the operational GOME and GOME-2 products. OCRA retrieves the cloud fraction using measurements in the UV/VIS spectral regions and ROCINN retrieves the cloud height (pressure) and optical thickness (albedo) using measurements in and around the oxygen A-band at 760 nm. For TROPOMI/S5P we use OCRA/ROCINN Version 3.0, which is based on a more realistic treatment of clouds as optically uniform layers of light-scattering particles. Additionally, the cloud parameters are also provided for a cloud model which assumes the cloud to be a Lambertian reflecting boundary." }, { "ob_id": 38310, "uuid": "3dfc1388681941cb973a0dbd6f3056f2", "short_code": "ob", "title": "Sentinel 5P: Tropospheric Ozone Column (O3_TCL) level 2 data", "abstract": "The TROPOspheric Monitoring Instrument (TROPOMI) tropospheric ozone product is a level-2c product that represents three days of averaged tropospheric ozone columns on a 0.5° by 1° latitude-longitude grid for the tropical region between 20°N and 20°S. The TROPOMI tropospheric ozone column product uses the TROPOMI Level-2 total OZONE and CLOUD products as input.\r\n\r\nThe TROPOMI instrument onboard the Copernicus Sentinel-5 Precursor is a nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. The instrument uses passive remote sensing techniques to attain its objective by measuring, at the Top Of Atmosphere (TOA), the solar radiation reflected by and radiated from the earth." }, { "ob_id": 26499, "uuid": "aeb840c2e8994f12a22f3c49b46929d8", "short_code": "ob", "title": "Sentinel 5P: Ultraviolet (UV) Aerosol Index level 2 data", "abstract": "Sentinel 5 Precursor (S5P) was launched on the 13th October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). The Aerosol Index (AI) is a well-established data product that has been calculated for several different satellite instruments spanning a period of nearly 40 years. The S5P/TROPOMI aerosol index is referred to as the Ultraviolet Aerosol Index (UVAI). The relatively simple calculation of the Aerosol Index is based on wavelength dependent changes in Rayleigh scattering in the UV spectral range where ozone absorption is very small. UVAI can also be calculated in the presence of clouds so that daily, global coverage is possible. This is ideal for tracking the evolution of episodic aerosol plumes from dust outbreaks, volcanic ash, and biomass burning." }, { "ob_id": 26440, "uuid": "887a695bf0b24f5590097a16c42604d6", "short_code": "ob", "title": "Sentinel 5P: Total column ozone (O3) level 2 data", "abstract": "Sentinel 5P total column ozone products contain total ozone, ozone temperature, and error information including averaging kernels. These data products are provided in a 7km x 3.5km resolution. \r\nOzone (O3) is of crucial importance for the equilibrium of the Earth's atmosphere. In the stratosphere, the ozone layer shields the biosphere from dangerous solar ultraviolet radiation. In the troposphere, it acts as an efficient cleansing agent, but at high concentrations, it also becomes harmful to the health of humans, animals, and vegetation. Ozone is also an important greenhouse-gas contributor to ongoing climate change. Since the discovery of the Antarctic ozone hole in the 1980s and the subsequent Montreal Protocol regulating the production of chlorine-containing ozone-depleting substances, ozone has been routinely monitored from the ground and from space. For TROPOMI/S5P, there are two algorithms that will deliver total ozone: GDP for the near real-time and GODFIT for the offline products. GDP is currently being used for generating the operational total ozone products from GOME, SCIAMACHY and GOME-2; while GODFIT is being used in the ESA CCI and the Copernicus C3S projects." }, { "ob_id": 27469, "uuid": "19a97e70e5a848ddaebac0243ff41684", "short_code": "ob", "title": "Sentinel 5P: Sulphur Dioxide (SO2) Total Column level 2 data", "abstract": "This dataset contains total column Sulphur Dioxide (SO2) data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel 5P satellite. \r\n\r\nSentinel 5 Precursor (S5P) was launched on the 13th October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). The TROPOMI instrument is a nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. The instrument uses passive remote sensing techniques to attain its objective by measuring, at the Top Of Atmosphere (TOA), the solar radiation reflected by and radiated from the earth.\r\n\r\nSulphur dioxide (SO2) enters the Earth’s atmosphere through both natural and anthropogenic processes. It plays a role in chemistry on a local and global scale and its impact ranges from short-term pollution to effects on climate. Only about 30% of the emitted SO2 comes from natural sources; the majority is of anthropogenic origin. SO2 emissions adversely affect human health and air quality. SO2 has an effect on climate through radiative forcing, via the formation of sulphate aerosols. Volcanic SO2 emissions can also pose a threat to aviation, along with volcanic ash. S5P/TROPOMI samples the Earth’s surface with a revisit time of one day with an unprecedented spatial resolution of 3.5 x 7 km which allows the resolution of fine details including the detection of much smaller SO2 plumes.\r\n\r\nBesides the total column of SO2, enhanced levels of SO2 are flagged within the products. The recognition of enhanced SO2 values is essential in order to detect and monitor volcanic eruptions and anthropogenic pollution sources. Volcanic SO2 emissions may also pose a threat to aviation, along with volcanic ash." }, { "ob_id": 37838, "uuid": "300559d22d9549049017f06bf38db929", "short_code": "ob", "title": "Sentinel 5P: Formaldehyde (HCHO) Total Column level 2 data", "abstract": "This dataset contains total column Formaldehyde (HCHO) data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel 5P satellite.\r\n\r\nSentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). The TROPOMI is a nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. The instrument uses passive remote sensing techniques to attain its objective by measuring, at the Top Of Atmosphere (TOA), the solar radiation reflected by and radiated from the earth. In addition to the main product results, such as HCHO slant column, vertical column, and air mass factor, the level 2 (geolocated total columns) data files contain several additional parameters and diagnostic information.\r\n\r\nFormaldehyde is an intermediate gas in almost all oxidation chains of Non-Methane Volatile Organic Compounds (NMVOC), leading eventually to CO2. NMVOCs are, together with NOx, CO, and CH4, among the most important precursors of tropospheric O3. The major HCHO source in the remote atmosphere is CH4 oxidation. Over the continents, the oxidation of higher NMVOCs emitted from vegetation, fires, traffic and industrial sources results in important and localised enhancements of the HCHO levels." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 111207, 111208, 111209, 111210, 111211, 111212, 111214, 111213, 111215 ], "onlineresource_set": [ 25323 ], "project_set": [ 12321 ] }, { "ob_id": 26474, "uuid": "bc7ec29506114a228efd4783ea15b2fd", "short_code": "coll", "title": "SaddleworthMoor: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for SADDLEWORTHMOOR FAAM Aircraft Project (SaddleworthMoor).", "keywords": "SaddleworthMoor, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2018-07-09T15:51:06", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26473, "uuid": "eceeb80a8e244fd1a9a5e01dffd64757", "short_code": "ob", "title": "FAAM C110 SaddleworthMoor flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for SADDLEWORTHMOOR FAAM Aircraft Project (SaddleworthMoor) project." }, { "ob_id": 26478, "uuid": "b8ca8754a54845b2959124b48578343e", "short_code": "ob", "title": "FAAM C111 MOYA and SaddleworthMoor flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Methane Observations and Yearly Assessments (MOYA) and SADDLEWORTHMOOR FAAM Aircraft Project projects." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 111269, 111270, 111271, 111274, 111275, 111276, 111277, 111278, 111272, 111273 ], "onlineresource_set": [], "project_set": [ 26471 ] }, { "ob_id": 26538, "uuid": "d491b9e869d845a3a727b569f95dde60", "short_code": "coll", "title": "Sentinel 5 Precursor: Level 1 data", "abstract": "Level 1 radiance and irradiance data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel 5P satellite. Sentinel 5P was launched on 13th October 2017. This satellite aims to provide atmospheric measurements relating to air quality, climate forcing, ozone and ultraviolet radiation. This data looks to build on the data from GOME, SCIAMACHY and OMI missions.", "keywords": "Sentinel 5P, TROPOMI, ESA", "publicationState": "published", "dataPublishedTime": "2022-11-03T08:22:35", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 148 ], "discoveryKeywords": [], "member": [ { "ob_id": 25900, "uuid": "4e1ed175588d41f193dd6f8f0140e7e3", "short_code": "ob", "title": "Sentinel 5P: TROPOspheric Monitoring Instrument (TROPOMI) Radiance level 1b data.", "abstract": "This dataset contains level 1b earth radiance spectra data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the European Space Agency (ESA) Sentinel 5P satellite. Sentinel 5P was launched on 13th October 2017. Level 1b data is geo-located and radiometrically corrected top of the atmosphere Earth radiances in all spectral bands. There is one L1b radiance product type for each spectral band (product identifiers L1B_RA_BD1 through L1B_RA_BD8). The radiance products are the main input for the Level-2 processors.\r\n\r\nSentinel 5P aims to provide atmospheric measurements relating to air quality, climate forcing, ozone and ultraviolet radiation. This data looks to build on the data from GOME, SCIAMACHY and OMI missions. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user." }, { "ob_id": 26509, "uuid": "0b4390871dce48ce91bc9dcf42137600", "short_code": "ob", "title": "Sentinel 5P: TROPOspheric Monitoring Instrument (TROPOMI) level 1b Irradiance product UVN module data.", "abstract": "This dataset contains level 1B data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the European Space Agency (ESA) Sentinel 5P satellite. Sentinel 5P was launched on 13th October 2017. This satellite aims to provide atmospheric measurements relating to air quality, climate forcing, ozone and ultraviolet radiation. This data looks to build on the data from GOME, SCIAMACHY and OMI missions. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 111506, 111508, 111509, 111504, 111503, 111505, 111507, 111510, 111511 ], "onlineresource_set": [ 25404 ], "project_set": [ 12321 ] }, { "ob_id": 26567, "uuid": "1f850b0d4d6f4c4fbb59fdc5fe46307e", "short_code": "coll", "title": "CURBCO2: Coupled physical-biogeochemical ocean simulations model output", "abstract": "This dataset collection contains coupled physical-biogeochemical ocean simulations model output using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes.\r\n\r\nThis data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015.", "keywords": "CURB, CO2, Oceans, alkalinity, temperature, salinity", "publicationState": "published", "dataPublishedTime": "2019-01-16T16:47:59", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26569, "uuid": "cbc7f00cde514dfebfb8d75913ee4862", "short_code": "ob", "title": "CURBCO2: Coupled Physical-biogeochemical ocean NEMO-HadOCC simulation output forced by GFDL-ESM2M atmosphere", "abstract": "This dataset contains coupled physical-biogeochemical ocean second generation Geophysical Fluid Dynamics Laboratory (GFDL-ESM2M) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes.\r\n\r\n Job IDs included in this dataset are:\r\n GFDL-ESM2M surface fluxes (started on 19th July ~14h):\r\n RCP85: u-ao541 (copy from u-ao419, change model names, restart + reduce walltime for nemo to test )\r\n RCP26: u-ao551 (copy from u-ao541 and change rcp26 surface fluxes)\r\n Constant atm CO2:\r\n RCP85: u-ao552 (copy from u-ao541 with cst atm changes)\r\n RCP26: u-ao554 (copy from u-ao551 with cst atm changes)\r\n\r\nThis data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015." }, { "ob_id": 26573, "uuid": "5a819e8e510a47b7bd8b1356caed43cb", "short_code": "ob", "title": "CURBCO2: Coupled Physical-biogeochemical ocean NEMO-HadOCC simulation output forced by IPSL-CM5A-LR atmosphere", "abstract": "This dataset contains coupled physical-biogeochemical ocean second generation Institut Pierre-Simon Laplace (IPSL-CM5A-LR) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes.\r\n\r\n Job IDs included in this dataset are:\r\n IPSL-CM5A-LR surface fluxes:\r\n RCP85: u-ao559 (copy from u-ao419, change model names, restart + reduce walltime for nemo to test)\r\n Failed in nemo_cice 20431201: v10 not found in y2044 (and same for the years after) => download,merge,transfer,re-run => fixed\r\n RCP26: u-ao562 (copy from u-ao559 and change rcp26 surface fluxes)\r\n Constant atm CO2:\r\n RCP85: u-ao563 (copy from u-ao559 with cst atm changes)\r\n RCP26: u-ao564 (copy from u-ao562 with cst atm changes)\r\n\r\nThis data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015." }, { "ob_id": 26571, "uuid": "70440cf97bd04a9890800566f9d31399", "short_code": "ob", "title": "CURBCO2: Coupled Physical-biogeochemical ocean NEMO-HadOCC simulation output forced by HadGEM2-ES atmosphere", "abstract": "This dataset contains coupled physical-biogeochemical ocean second generation Met Office (HadGEM2-ES) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes.\r\n\r\n Job IDs included in this dataset are:\r\n HadGEM2-ES surface fluxes (2099 for rcp85 not resolved yet) (runs started on 26th July)\r\n RCP85: u-ao789 (nov 2099)(copy from u-ao559,change model name, restart path, and surface fluxes files)\r\n RCP26: u-ao790 (nov 2099) (copy from u-ao789,change rcp26 surface fluxes)\r\n Constant atm CO2\r\n RCP85: u-ao791 (nov 2099) (copy from u-ao789 with cst atm changes)\r\n RCP26: u-ao793 (nov 2099) copy from u-ao790 with cst atm changes)\r\n\r\nThis data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015." }, { "ob_id": 26556, "uuid": "3ecd1690bab2432db4ecb1de08388cfe", "short_code": "ob", "title": "CURBCO2: Coupled Physical-biogeochemical ocean NEMO-HadOCC simulation output forced by CanESM2 atmosphere", "abstract": "This dataset contains coupled physical-biogeochemical ocean second generation Canadian Earth System Model (CanESM2) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes.\r\n\r\nJob IDs included in this dataset:\r\n CanESM2 surface fluxes (started on 18th for first, 21st for second, and on the 19th for other 2):\r\n RCP85: u-ao419\r\n RCP26: u-ao519\r\n Constant atm CO2:\r\n RCP85: u-ao529\r\n RCP26: u-ao531 (reduce walltime for nemo to test)\r\n\r\nThis data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 111639, 111640, 111641, 111642, 111644, 111645, 111646, 111647, 111643, 168842, 111648, 111649 ], "onlineresource_set": [], "project_set": [] } ] }