Result List
Get a list of Result objects. Results have a 1:1 mapping with Observations.
GET /api/v3/results/?format=api&offset=8200
{ "count": 11555, "next": "https://api.catalogue.ceda.ac.uk/api/v3/results/?format=api&limit=100&offset=8300", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/results/?format=api&limit=100&offset=8100", "results": [ { "ob_id": 32194, "uuid": "cc10c09a1a9b48b1bb8160a5ccd711ba", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v05.3/", "numberOfFiles": 10743, "volume": 9089649738, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32193, "uuid": "1da8dadcdfb642f4aad2384f02efe756", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 05.3", "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) 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 v05.3 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 is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2020-12-31. 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" }, "onlineresource_set": [] }, { "ob_id": 32196, "uuid": "053eba6c3075496ab6715c35931e2e34", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/COMBINED/v05.3", "numberOfFiles": 15403, "volume": 17180152392, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32195, "uuid": "e43aead9947549078c2d108b2c3632b2", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 05.3", "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 v05.3 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 2020-12-31. 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" }, "onlineresource_set": [] }, { "ob_id": 32198, "uuid": "e2923d45ecc748f9a3224a59a5d4b424", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/PASSIVE/v05.3", "numberOfFiles": 15403, "volume": 14634871307, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32197, "uuid": "31137897d305407c9b83d49d124e4d1d", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE Product, Version 05.3", "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 v05.3 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 2020-12-31. 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" }, "onlineresource_set": [] }, { "ob_id": 32208, "uuid": "844629d391ef4ad1b78426936096312b", "short_code": "result", "curationCategory": "", "dataPath": "/badc/aphh/data/delhi/delhiflux/man-aethalometer/", "numberOfFiles": 2, "volume": 1577135, "fileFormat": "Data are BADC-CSV formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32200, "uuid": "18a5685b5bbc4b3caefc469881f5f784", "short_code": "ob", "title": "APHH: Aethalometer measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) site during the pre and post monsoon periods for the DelhiFlux field campaign 2018", "abstract": "This dataset contains Black carbon (BC) concentrations in ugm-3 measured with an Aethalometer model AE31 made during the Pre- Monsoon and Post-Monsoon periods of the APHH Delhi campaigns in 2018 at Indira Gandhi Delhi Technical University for Women (IGDTUW) site. The data has been corrected following the Weingartner method. Absorption coefficients were calculated following the Sandradewi model to determine biomass burning and fossil fuel contributions in Mm-1. The measurements were collected at a height of 4m.\r\n\r\nThe data were collected as part of the DelhiFlux project part of Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme." }, "onlineresource_set": [] }, { "ob_id": 32211, "uuid": "2fc30e7930a541279d5bdb4eb4a03f35", "short_code": "result", "curationCategory": "", "dataPath": "/badc/aphh/data/delhi/delhiflux/man-maap-bc", "numberOfFiles": 2, "volume": 31817, "fileFormat": "Data are BADC-CSV formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32210, "uuid": "131a1935809540488cbb20bf5be5e8b3", "short_code": "ob", "title": "APHH: Multi Angle Absorption Photometer (MAAP) measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) site during the post monsoon periods for the DelhiFlux field campaign 2018", "abstract": "This dataset contains Black carbon (BC) concentrations in ugm-3 measured with an Multi Angle Absorption Photometer (MAAP) made during Post-Monsoon period of the APHH Delhi campaign in 2018 at Indian Meteorological Department (IMD) site. The measurements were collected at a height of ~ 26m.\r\nThe data has been corrected following the Weingartner method. Absorption coefficients were calculated following the Sandradewi model to determine biomass burning and fossil fuel contributions in Mm-1. The measurements were collected at a height of 4m.\r\n\r\nThe data were collected as part of the DelhiFlux project part of Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme." }, "onlineresource_set": [] }, { "ob_id": 32214, "uuid": "cdcf9d5415074cb1a9196ab5d9c01e17", "short_code": "result", "curationCategory": "", "dataPath": "/badc/aphh/data/delhi/delhiflux/man-ctof-ams/", "numberOfFiles": 3, "volume": 242731, "fileFormat": "Data are BADC-CSV formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32213, "uuid": "b7c9aeb6aee54698aef82f20365fc441", "short_code": "ob", "title": "APHH: Compact Time of Flight Aerosol Mass Spectrometer measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) site and India Meteorological Department (IMD) during the post monsoon periods for the DelhiFlux field campaign 2018", "abstract": "This dataset contains includes Organic aerosols, NO3, SO4, NH4 and Cl concentrations in ugm-3 measured with Compact Time of Flight Aerosol Mass Spectromete made during the Post-Monsoon periods of the APHH Delhi campaigns in 2018 at Indira Gandhi Delhi Technical University for Women (IGDTUW) site and India Meteorological Department site. Organic aerosol factors (HOA, LVOOA, BBOA, COA and SVOOA were identified using PMF factorization.\r\n\r\nThe data were collected as part of the DelhiFlux project part of Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme." }, "onlineresource_set": [] }, { "ob_id": 32218, "uuid": "134e4342bc7c48ecb26e336b2a066669", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/arsf/2004/04_27", "numberOfFiles": 35, "volume": 701660985, "fileFormat": "TIF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32217, "uuid": "d4c52191d8d54fab8162b413527d1ec2", "short_code": "ob", "title": "Data from the Photographic Camera on-board the Dornier Do228-101 D-CALM Aircraft during Flight 04/17 over the Dorchester Area", "abstract": "ARSF project 04/27 led by John Hilton. Site:Dorchester." }, "onlineresource_set": [] }, { "ob_id": 32221, "uuid": "5cb1a7f232a940dfada68e70ee5767e4", "short_code": "result", "curationCategory": "", "dataPath": "/badc/aphh/data/delhi/delhiflux/man-sp2/", "numberOfFiles": 4, "volume": 493295, "fileFormat": "Data are BADC-CSV formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32220, "uuid": "81cf5b23a50446a0991eba0dc9cb46eb", "short_code": "ob", "title": "APHH: Single Particle Soot Photometer (SP2) measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) site during the pre and post monsoon periods for the DelhiFlux field campaign 2018", "abstract": "This dataset includes black carbon mass and number concentrations measurements performed by the University of Manchester with a Single Particle Soot Photometer (SP2) made during the Pre- Monsoon and Post-Monsoon periods of the APHH Delhi campaigns in 2018 at Indira Gandhi Delhi Technical University for Women (IGDTUW) site.\r\n\r\nThe data were collected as part of the DelhiFlux project part of Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme." }, "onlineresource_set": [] }, { "ob_id": 32233, "uuid": "7855781abf6549e3b53887bc5cf5e569", "short_code": "result", "curationCategory": "", "dataPath": "/badc/sa-monsoon/data/incompass/v2-convective-cells", "numberOfFiles": 8, "volume": 58170164, "fileFormat": "Data are BADC-CSV formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32232, "uuid": "b28633ddc0f44d77a6aa81ad7bd66285", "short_code": "ob", "title": "INCOMPASS: India Meteorology Department Doppler radar convective cell statistics v2", "abstract": "This dataset contains radar-derived measurements of cell-top height, size, 2 km reflectivity, and cell latitude and longitude from all convective cells between 14 May and 30 September 2016, where radar is available. The data was collected as part of the NERC/MoES Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) field campaign.\r\n\r\nThe seven sites analysed here represent four different Indian climate regions, allowing the study of the spatiotemporal development of convection during the 2016 monsoon season at high (1 km) resolution. Variation in these different cell statistics are found over timescales of variability such as the diurnal cycle, active-break periods, and monsoon progression.\r\n\r\nThe updated radar-derived cell statistics here have been corrected from the previous version by removing all convective cells that touch the outer edge of the radar domain.\r\n\r\nThe data were collected as part of the INCOMPASS field campaign May-July 2016, funded by Natural Environmental Research Council (NERC) (NE/L01386X/1). The aim of the project was to improve the skill of rainfall prediction in operational weather and climate models by way of better understanding and representation of interactions between the land surface, boundary layer, convection, the large-scale environment and monsoon variability on a range of scales." }, "onlineresource_set": [] }, { "ob_id": 32234, "uuid": "49699282111644138e3efefba845eb79", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/cloud/data/obs4MIPs/DWD/ESACCI-CLOUD-ATSR2-AATSR-3-0/mon/", "numberOfFiles": 134, "volume": 7568311564, "fileFormat": "Data are in NetCDF format. Data has been formatted according to Obs4MIPs specifications", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32224, "uuid": "be40716c1036498cb6b16b0ef25c5535", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): Obs4MIPs format monthly gridded cloud products from ATSR2 and AATSR, version 3", "abstract": "This dataset provides a version of the Cloud_cci ATSR2-AATSRv3 monthly gridded dataset in Obs4MIPs format. The Cloud_cci ATSR2-AATSRv3 dataset (covering 1995-2012) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). \r\n\r\nThis dataset is based on measurements taken by the Along-Track Scanning Radiometer (ATSR-2) on-board the European Remote Sensing Satellite -2 (ERS-2), and by the Advanced Along-Track Scanning Radiometer (AATSR) on-board the Environmental Satellite (Envisat). It contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval framework. \r\n\r\nThis particular Obs4MIPS product has been generated for inclusion in Obs4MIPs (Observations for Model Intercomparisons Project), which is an activity to make observational products more accessible for climate model intercomparisons. \r\n\r\nIndividual files are provided covering seven cloud variables:\r\nCloud area fraction in atmospheric layer (clCCI);\r\nAtmospheric cloud ice content (clivi);\r\nCloud area fraction (cltCCI);\r\nLiquid water cloud area fraction in atmospheric layer(clwCCI);\r\nLiquid water cloud area fraction (clwtCCI);\r\nAtmosphere mass content of cloud condensed water (clwvi);\r\nAir pressure at cloud top (pctCCI)" }, "onlineresource_set": [] }, { "ob_id": 32236, "uuid": "7952010a34b54ddaa31a5804e9c4b396", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/cloud/data/obs4MIPs/DWD/ESACCI-CLOUD-AVHRR-AM-3-0/mon/", "numberOfFiles": 190, "volume": 13879586305, "fileFormat": "Data are in NetCDF format. Data has been formatted according to Obs4MIPs specifications.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32235, "uuid": "ff5f152a3f194ab1be33543f291e65cd", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): Obs4MIPs format monthly gridded cloud products from AVHRR (AVHRR-AM), version 3", "abstract": "This dataset provides a version of the Cloud_cci AVHRR-AMv3 monthly gridded dataset in Obs4MIPs format. The Cloud_cci AVHRR-AMv3 dataset (covering 1991-2016) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). \r\n\r\nThis dataset is based on intercalibrated measurements from the Advanced Very High Resolution Radiometer (AVHRR) sensors on-board the NOAA prime morning (AM) satellite NOAA-12,-15,-17, and the EUMETSAT Metop-A satellite. It contains a multi-annual, global dataset of cloud and radiation properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval framework. \r\n\r\nThis particular Obs4MIPS product has been generated for inclusion in Obs4MIPs (Observations for Model Intercomparisons Project), which is an activity to make observational products more accessible for climate model intercomparisons. \r\n\r\nIndividual files are provided covering seven cloud variables:\r\nCloud area fraction in atmospheric layer (clCCI);\r\nAtmospheric cloud ice content (clivi);\r\nCloud area fraction (cltCCI);\r\nLiquid water cloud area fraction in atmospheric layer(clwCCI);\r\nLiquid water cloud area fraction (clwtCCI);\r\nAtmosphere mass content of cloud condensed water (clwvi);\r\nAir pressure at cloud top (pctCCI)" }, "onlineresource_set": [] }, { "ob_id": 32238, "uuid": "193e220603434e37a38f70607d916a4c", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/cloud/data/obs4MIPs/DWD/ESACCI-CLOUD-AVHRR-PM-3-0/mon/", "numberOfFiles": 253, "volume": 20697306221, "fileFormat": "Data are in NetCDF format. They have been formatted according to Obs4MIPs specifications.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32237, "uuid": "919157930d7447caac6d42e84e377289", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): Obs4MIPs format monthly gridded cloud products from AVHRR (AVHRR-PM), version 3", "abstract": "This dataset provides a version of the Cloud_cci AVHRR-PMv3 monthly gridded dataset in Obs4MIPs format. The Cloud_cci AVHRR-PMv3 dataset (covering 1982-2016) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). \r\n\r\nThis dataset is based on intercalibrated measurements from the Advanced Very High Resolution Radiometer (AVHRR) sensors on-board the NOAA prime afternoon (PM) satellite NOAA-7,-9,11,-14,-16,-18,-19 satellites. It contains a multi-annual, global dataset of cloud and radiation properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval framework. \r\n\r\nThis particular Obs4MIPS product has been generated for inclusion in Obs4MIPs (Observations for Model Intercomparisons Project), which is an activity to make observational products more accessible for climate model intercomparisons. \r\n\r\nIndividual files are provided covering seven cloud variables:\r\nCloud area fraction in atmospheric layer (clCCI);\r\nAtmospheric cloud ice content (clivi);\r\nCloud area fraction (cltCCI);\r\nLiquid water cloud area fraction in atmospheric layer(clwCCI);\r\nLiquid water cloud area fraction (clwtCCI);\r\nAtmosphere mass content of cloud condensed water (clwvi);\r\nAir pressure at cloud top (pctCCI)" }, "onlineresource_set": [] }, { "ob_id": 32242, "uuid": "376f20f389614513aaafcde29291f7ef", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/snow/data/scfg/AVHRR_MERGED/v1.0", "numberOfFiles": 13770, "volume": 34835500668, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 31210, "uuid": "5484dc1392bc43c1ace73ba38a22ac56", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from AVHRR (1982 - 2019), version1.0", "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space over land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFG time series provides daily products for the period 1982-2019. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. \r\n\r\nThe retrieval method of the snow_cci SCFG product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 630 nm and 1.61 µm (channel 3a or the reflective part of channel 3b), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. \r\n\r\nThe following auxiliary data sets are used for product generation: i) ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map; ii) Forest canopy transmissivity map; this layer is based on the tree cover classes of the ESA CCI Land Cover 2000 data set and the tree cover density map from Landsat data for the year 2000 (Hansen et al., Science, 2013, DOI: 10.1126/science.1244693). This layer is used to apply a forest canopy correction and estimate in forested areas the fractional snow cover on ground.\r\n\r\nThe SCFG product is aimed to serve the needs of users working in cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern is responsible for the SCFG product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation.\r\n\r\nThe SCFG AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 38 years." }, "onlineresource_set": [] }, { "ob_id": 32243, "uuid": "6c34735cbeb4464393a56245cfd2482d", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/snow/data/scfg/MODIS/v1.0", "numberOfFiles": 7191, "volume": 203818851581, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 31205, "uuid": "3b3fd2daf3d34c1bb4a09efeaf3b8ea9", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from MODIS (2000-2019), version 1.0", "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from MODIS, produced by the Snow project of the ESA Climate Change Initiative programme.\r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space on land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. \r\n\r\nThe SCFG time series provides daily products for the period 2000 – 2019. \r\n\r\nThe SCFG product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. \r\n\r\nThe retrieval method of the snow_cci SCFG product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFG product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 550 nm and 1.6 µm, and an emissive band centred at about 11 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include (i) the utilisation of background and forest reflectance maps derived from statistical analyses of MODIS time series replacing the constant values for snow free ground and snow free forest used in the GlobSnow approach, and (ii) the usage of a global forest transmissivity map developed and created within snow_cci based on forest density from Hansen et al. (2013) and forest type layers from Land Cover CCI (Defourny, 2019). The forest transmissivity map is used to account for the shading effects of the forest canopy and estimate also in forested areas the fractional snow cover on ground.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFG product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.\r\n\r\nThe SCFG product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nENVEO is responsible for the SCFG product development and generation from MODIS data, SYKE supported the development.\r\n\r\nThere are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2018. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFG products are available but have data gaps." }, "onlineresource_set": [] }, { "ob_id": 32246, "uuid": "8624ab574e184cfcb655a3b57caf6e5c", "short_code": "result", "curationCategory": "", "dataPath": "/badc/aphh/data/delhi/asap-delhi/bham-nox", "numberOfFiles": 5, "volume": 13558958, "fileFormat": "Data are NASA Ames formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32245, "uuid": "a2ccd940e4c046978c1a3a472ae68007", "short_code": "ob", "title": "APHH: Atmospheric NO, NO2 and NOx measurements made at Indian Institute of Technology (IIT) Delhi", "abstract": "This dataset contains NO, NO2 and NOx mixing ratio measurements using the commercially available Thermo 42C chemiluminescence monitor. Measurements were made at the Indian Institute of Technology Delhi (IIT-Delhi), India. Mixing ratios are reported in parts per billion (ppb). The stationary inlet was located on the roof of a 5-storey building at Block IV, Indian Institute of Technology Delhi campus. \r\n\r\nThe data were collected over three measurement periods (i) winter: 12/01/2018 - 13/02/2018, (ii) pre-monsoon: 26/04/2018 - 05/06/2018 and (iii) post-monsoon: 13/10/2018 - 10/11/2018, by the University of Birmingham.\r\n\r\nThese data were collected as part of the ASAP-Delhi project as part of the Atmospheric Pollution and Human Health in an Indian Megacity (APHH) programme." }, "onlineresource_set": [] }, { "ob_id": 32251, "uuid": "b807c162a79647f39564a1941a65f72e", "short_code": "result", "curationCategory": "", "dataPath": "/badc/aphh/data/delhi/asap-delhi/bham-bc-ae33", "numberOfFiles": 3, "volume": 2632332, "fileFormat": "Data are NASA Ames formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32250, "uuid": "c09edb49931045e98287eac3ea17b423", "short_code": "ob", "title": "APHH: Atmospheric black carbon measurements made at Indira Gandhi Delhi Technical University for Women (IGDTUW)", "abstract": "This dataset contains black carbon concentrations using the aethalometer AE33 monitor. Measurements were made at the Indira Gandhi Delhi Technical University for Women (IGDTUW), India. Concentrations are reported in micrograms per cubic centimetre (ug.cm-3). The stationary inlet was located on the roof of a 4-storey building at IGDTUW campus. \r\n\r\nThe data were collected over two measurement periods (i) winter: 17/01/2018 - 09/02/2018 and (ii) pre-monsoon: 02/05/2018 - 25/05/2018, by the University of Birmingham.\r\n\r\nThese data were collected as part of the ASAP-Delhi project as part of the Atmospheric Pollution and Human Health in an Indian Megacity (APHH) programme." }, "onlineresource_set": [] }, { "ob_id": 32254, "uuid": "efc18289db4746bbb54cd7e14ea7b15a", "short_code": "result", "curationCategory": "", "dataPath": "/badc/aphh/data/delhi/asap-delhi/bham-o3-49i", "numberOfFiles": 4, "volume": 6471037, "fileFormat": "Data are NASA Ames formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32253, "uuid": "fc48b67355554aa1bf4e6a8a358bca72", "short_code": "ob", "title": "APHH: Atmospheric O3 measurements made at Indian Institute of Technology (IIT) Delhi", "abstract": "This dataset contains online measurements of O3 mixing ratios using the commercially available Thermo 49i monitor. Measurements were made at the Indian Institute of Technology Delhi (IIT-Delhi), India. Mixing ratios are reported in parts per billion (ppb). The stationary inlet was located on the roof of a 5-storey building at Block IV, Indian Institute of Technology Delhi campus. \r\n\r\nThe data were collected over three measurement periods (i) winter: 12/01/2018 - 13/02/2018, (ii) pre-monsoon: 26/04/2018 - 05/06/2018 and (iii) post-monsoon: 13/10/2018 - 10/11/2018, by the University of Birmingham. \r\n\r\nThese data were collected as part of the ASAP-Delhi project as part of the Atmospheric Pollution and Human Health in an Indian Megacity (APHH) programme." }, "onlineresource_set": [] }, { "ob_id": 32260, "uuid": "a3b8e95d57004fc0aea00aa7a9da7958", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/snow/data/scfv/MODIS/v1.0", "numberOfFiles": 7191, "volume": 203930783168, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 31204, "uuid": "ef8eb5ff84994f2ca416dbb2df7f72c7", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2019), version 1.0", "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from the MODIS satellite instruments, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. \r\n\r\nThe SCFV time series provides daily products for the period 2000 – 2019. \r\n\r\nThe SCFV product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. \r\n\r\nThe retrieval method of the snow_cci SCFV product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFV product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 550 nm and 1.6 µm, and an emissive band centred at about 11 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include (i) the utilisation of a background reflectance map derived from statistical analyses of MODIS time series replacing the constant values for snow free ground used in the GlobSnow approach, and (ii) the adaptation of the retrieval method for mapping in forested areas the SCFV. \r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFV product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nENVEO is responsible for the SCFV product development and generation from MODIS data, SYKE supported the development.\r\n\r\nThere are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2018. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFV products are available but have data gaps." }, "onlineresource_set": [] }, { "ob_id": 32261, "uuid": "fdacebf0223d4f30831ab5b93d2dbbae", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/snow/data/scfv/AVHRR_MERGED/v1.0", "numberOfFiles": 13770, "volume": 35670768784, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 31209, "uuid": "d9df331e346f4a50b18bcf41a64b98c7", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable (SCFV) from AVHRR (1982 - 2019), version 1.0", "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFV time series provides daily products for the period 1982-2019. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. \r\nThe retrieval method of the snow_cci SCFV product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 630 nm and 1.61 µm (channel 3a or the reflective part of channel 3b), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. \r\n\r\nThe following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern is responsible for the SCFV product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation. \r\n\r\nThe SCFV AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 38 years." }, "onlineresource_set": [] }, { "ob_id": 32262, "uuid": "93154dc8ff9c46ec892704ff0032cda7", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ecmwf-for", "numberOfFiles": 1, "volume": 937, "fileFormat": "GRIB", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32263, "uuid": "4d9eb71f6874435ab88d3c37539f1ed7", "short_code": "ob", "title": "ECMWF Forecasts for project support.", "abstract": "This dataset contained a variety of forecast data from ECMWF, which supported observation campaigns. The variables, geo-temporal extent and other aspects were different for each campaign supported. The project supported were: adient, catlin, cloudmap2, crose, troccinox, itop, plume, slimcat, torch and vintersol.\r\n\r\nThese data are no longer relevant, and were not reusable due the very specific access conditions that applied to each project." }, "onlineresource_set": [] }, { "ob_id": 32264, "uuid": "2dcdc897c1284fb48ba6a3c95dd290c0", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/sentinel5p/data/L2_CO/", "numberOfFiles": 118863, "volume": 11222010975576, "fileFormat": "These data are provided in NetCDF format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "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." }, "onlineresource_set": [] }, { "ob_id": 32266, "uuid": "ec0968155fa74ec7b27226f12301a0ff", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/sentinel3b/data/SRAL/L1_SRA/", "numberOfFiles": 60298, "volume": 1231521483425, "fileFormat": "Data are provided by ESA in zipped SAFE format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32265, "uuid": "e28a2d786c79494ca77206178bae5dcf", "short_code": "ob", "title": "Sentinel 3B Synthetic Aperture Radar Altimeter (SRAL) Level 1B data", "abstract": "This dataset contains level 1b altimetry data from the Synthetic Aperture Radar Altimeter (SRAL) aboard the European Space Agency (ESA) Sentinel 3B Satellite. Sentinel 3B was launched on the 25th of April 2018. These level 1b products are geo-located and fully calibrated multi-looked High-Resolution power echoes. Complex echoes (In-phase (I) and Quadrature (Q)) for the Low-Resolution Mode (LRM) and/or Synthetic Aperture Radar (SAR) mode both for C Band and Ku band. When the altimeter is in SAR mode, this product also contains the so-called Pseudo LRM (PLRM) echoes. All Sentinel-3 Non-Time Critical (NTC) products are available in less than 30 days. Data are provided by ESA and are made available via CEDA to any registered user." }, "onlineresource_set": [] }, { "ob_id": 32267, "uuid": "d443f3b1b19b4e11a4b13fc056766687", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/acsoe/trajectory", "numberOfFiles": 29016, "volume": 3208923003, "fileFormat": "Text", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32269, "uuid": "fd0960d18dc74454b9b79e92b0628a4b", "short_code": "ob", "title": "Computed air parcel trajectory used for campaign support during the Atmospheric Chemistry Studies in the Oceanic Environment (ACSOE) programme.", "abstract": "Computed air parcel trajectory used for campaign support during the Atmospheric Chemistry Studies in the Oceanic Environment (ACSOE) programme." }, "onlineresource_set": [] }, { "ob_id": 32268, "uuid": "b61f51d935de46a6a2a5a2c7ca76af45", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/sentinel5p/data/L2_O3/", "numberOfFiles": 67239, "volume": 10565012646038, "fileFormat": "These data are provided in netCDF format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "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." }, "onlineresource_set": [] }, { "ob_id": 32271, "uuid": "57e8543a6bde4dc8bb357d647ad9ab4e", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/sea_level_budget_closure/data/timeseries_slb_elements/v2.1/", "numberOfFiles": 2, "volume": 114122, "fileFormat": "Data are in BADC-CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32239, "uuid": "1562578dd07844f19f01f0db9366106d", "short_code": "ob", "title": "ESA Sea Level Budget Closure Climate Change Initiative (SLBC_cci): Time series of global mean sea level budget and ocean mass budget elements (1993-2016, at monthly resolution), version 2.1", "abstract": "This dataset is a compilation of time series, together with uncertainties, of the following elements of the global mean sea level budget and ocean mass budget:\r\n(a) global mean sea level\r\n(b) the steric contribution to global mean sea level, that is, the effect of ocean water density change, which is dominated, on a global average, by thermal expansion\r\n(c) the mass contribution to global mean sea level\r\n(d) the global glaciers contribution (excluding Greenland and Antarctica)\r\n(e) the Greenland Ice Sheet and Greenland peripheral glaciers contribution\r\n(f) the Antarctic Ice Sheet contribution\r\n(g) the contribution from changes in land water storage (including snow cover).\r\n\r\nThe compilation is a result from the Sea-level Budget Closure (SLBC_cci) project conducted in the framework of ESA’s Climate Change Initiative (CCI). It provides assessments of the global mean sea level and ocean mass budgets. Assessment of the global mean sea level budget means to assess how well (a) agrees, within uncertainties, to the sum of (b) and (c) or to the sum of (b), (d), (e), (f) and (g). Assessment of the ocean mass budget means to assess how well (c) agrees to the sum (d), (e), (f) and (g).\r\n\r\nAll time series are expressed in terms of anomalies (in millimetres of equivalent global mean sea level) with respect to the mean value over the 10-year reference period 2006-2015. \r\nThe temporal resolution is monthly. The temporal range is from January 1993 to December 2016. Some time series do not cover this full temporal range. All time series are complete over the temporal range from January 2003 to August 2016.\r\n\r\nFor some elements, more than one time series are given, as a result of different assessments from different data sources and methods.\r\n\r\nData and methods underlying the time series are as follows:\r\n(a) satellite altimetry analysis by the Sea Level CCI project.\r\n(b) a new analysis of Argo drifter data with incorporation of sea surface temperature data; an alternative time series consists in an ensemble mean over previous global mean steric sea level anomaly time series.\r\n(c) analysis of monthly global gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry mission.\r\n(d) results from a global glacier model.\r\n(e) analysis of satellite radar altimetry over the Greenland Ice Sheet, amended by results from the global glacier model for the Greenland peripheral glaciers; an alternative time series consists of results from GRACE satellite gravimetry.\r\n(f) analysis of satellite radar altimetry over the Antarctic Ice Sheet; an alternative time series consists of results from GRACE satellite gravimetry.\r\n(g) results from the WaterGAP global hydrological model." }, "onlineresource_set": [] }, { "ob_id": 32273, "uuid": "919e27b77faa4d04ba5aa9fc792c0370", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2019/HyTES19/HyTES19-2019_168_Grosseto", "numberOfFiles": 110, "volume": 116699790969, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32272, "uuid": "8dff6e1d989643df977bf0c6766adb60", "short_code": "ob", "title": "NERC-ARF 2019_168 - HyTES19 Flight: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 17 June 2019 onboard the Natural Environment Research Council Airborne Research Facility (NERC-ARF) Dornier Do228-101 D-CALM Aircraft for the NET-Sense - joint NASA ESA Temperature Sensing Experiment (HyTES19) project (flight reference: 2019_168). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager.\r\n\r\nData were collected over the Grosseto, Italy area." }, "onlineresource_set": [] }, { "ob_id": 32278, "uuid": "f82b1991401c4b4f9cb5d4948c4a6a2d", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2019/HyTES19/HyTES19-2019_169_Grosseto", "numberOfFiles": 343, "volume": 173035767130, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32277, "uuid": "d555c81c6f08490984b2822d733d1661", "short_code": "ob", "title": "NERC-ARF Flight 2019_169 - for HyTES19: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 18 June 2019 onboard the Natural Environment Research Council Airborne Research Facility (NERC-ARF) Dornier Do228-101 D-CALM Aircraft for the NET-Sense - joint NASA ESA Temperature Sensing Experiment (HyTES19) project (flight reference: 2019_169). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager.\r\n\r\nData were collected over the Grosseto, Italy area." }, "onlineresource_set": [] }, { "ob_id": 32282, "uuid": "6d183d037d724cf98dfd3fccf25c6dba", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/landsat5/data/TM/", "numberOfFiles": 25647, "volume": 910781409269, "fileFormat": "These data are provided by NASA/USGS in GeoTIFF format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32283, "uuid": "c8b4b03778b145f79facce0af21237cb", "short_code": "ob", "title": "Landsat 5 Thematic Mapper (TM) data", "abstract": "The Landsat Thematic Mapper (TM) sensor was carried onboard Landsats 4 and 5 from July 1982 to May 2012 with a 16-day repeat cycle, referenced to the Worldwide Reference System-2. Very few images were acquired from November 2011 to May 2012. The satellite began decommissioning activities in January 2013.\r\n\r\nThe Thematic Mapper (TM) is an advanced, multispectral scanning, Earth resources sensor designed to achieve higher image resolution, sharper spectral separation, improved geometric fidelity, and greater radiometric accuracy and resolution than the Multispectral Scanner (MSS) sensor. TM data are sensed in seven spectral bands simultaneously. A TM scene has an Instantaneous Field Of View (IFOV) of 30m x 30m in bands 1-5 and 7 while band 6 has an IFOV of 120m x 120m on the ground (band 6 was collected at 120 meters, but was resampled to 30 meters). Band 6 senses thermal (heat) infrared radiation. Landsat can only acquire night scenes in band 6. The approximate scene size is 170 km north-south by 183 km east-west (106 mi by 114 mi)." }, "onlineresource_set": [] }, { "ob_id": 32311, "uuid": "8d6b236c9e3f4bc0951db4d407a7b3db", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/COMBINED/v06.1/", "numberOfFiles": 15403, "volume": 17966772658, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32296, "uuid": "43d73291472444e6b9c2d2420dbad7d6", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 06.1", "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, SMAP, FY-3B and GPM satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v06.1 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 2020-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. 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 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" }, "onlineresource_set": [] }, { "ob_id": 32312, "uuid": "fda9fb8c226b4cd3a389c828e38334f8", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v06.1/", "numberOfFiles": 10743, "volume": 8895156913, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32297, "uuid": "c2af8764c84744de87a69db7fecf7af9", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 06.1", "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) 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 v06.1 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 is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2020-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. 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 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" }, "onlineresource_set": [] }, { "ob_id": 32313, "uuid": "1192a6a818fb49bf89b92d74808212da", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/PASSIVE/v06.1/", "numberOfFiles": 15403, "volume": 15182338233, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32295, "uuid": "f5ffbd016e6b44858a33ae38ed2a149e", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 06.1", "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, SMAP, FY-3B and GPM satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v06.1 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 2020-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. 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 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" }, "onlineresource_set": [] }, { "ob_id": 32314, "uuid": "88c5ed5fd3ec493b81101556f6b36f62", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v06.1/", "numberOfFiles": 6, "volume": 1558698, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32298, "uuid": "c3bd175b6ed64020b439eb08ed9c8fc2", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 06.1", "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 v06.1 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which these data were used to develop are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS, SMAP, FY-3B, GPM 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 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" }, "onlineresource_set": [] }, { "ob_id": 32317, "uuid": "532ad56779134949b2c62451844abdb1", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2019/HyTES19/HyTES19-2019_171a_Grosseto", "numberOfFiles": 0, "volume": 0, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 32321, "uuid": "f871762a0bdf441ab94a9049fea808fb", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2019/HyTES19/HyTES19-2019_171a_Grosseto", "numberOfFiles": 174, "volume": 62292355647, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32320, "uuid": "2e1a4658858d4c678d861bd84e120e57", "short_code": "ob", "title": "NERC-ARF Flight 2019_171a - for HyTES19: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 20 June 2019 by the Natural Environment Research Council Airborne Research Facility (NERC-ARF) onboard the British Antarctic Survey (BAS) Twin-Otter Aircraft for the NET-Sense - joint NASA ESA Temperature Sensing Experiment (HyTES19) project (flight reference: 2019_171a). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager.\r\n\r\nData were collected over the Grosseto, Italy area." }, "onlineresource_set": [] }, { "ob_id": 32325, "uuid": "a72713f7204e43f381533ec3d3fc3524", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/sg-wex/data/um-data/sgwex_Jan2015_SG_u-ag477", "numberOfFiles": 1539, "volume": 1904402654650, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32324, "uuid": "6cd2bd9bf3e143009a7df234e4a8f55c", "short_code": "ob", "title": "SG-WEx: Unified Model output for January 2015 over South Georgia, with island orography included (run: u-ag477)", "abstract": "This dataset contains modelling output from the u-ag477 run of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the Met Office Unified Model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period January 2015 with the island orography included. See related dataset for output from a complementary run with a flat orography file for the island for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. These runs also coincided with radiosonde campaigns launched from the island.\r\n\r\nTechnical details regarding the configuration of these runs is described Vosper (2015, doi:10.1002/qj.2566). Further information and science results can be found in Jackson et al. (2018, doi:10.1175/BAMS-D-16-0151.1) and Hindley (2021, doi:10.5194/acp-21-7695-2021). See online resources linked to this record for further details." }, "onlineresource_set": [] }, { "ob_id": 32347, "uuid": "9abd3884dd374d7c9aba72864522eca2", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/break_adjusted_COMBINED/v06.1/", "numberOfFiles": 15403, "volume": 13058542122, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32310, "uuid": "3bfe0c2d51544f72837a99306a74e359", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Experimental Break-Adjusted COMBINED Product, Version 06.1", "abstract": "An experimental break-adjusted soil-moisture product has been generated by the ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project for the first time with their v06.1 data release. The product attempts to reduce breaks in the final CCI product by matching the statistics of the datasets between merging periods. At v06.1, the break-adjustment process (explained in Preimesberger et al. 2020) is applied only to the COMBINED product, using ERA5 soil moisture as a reference. 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, SMAP, FY-3B and GPM satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v06.1 COMBINED break-adjusted 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 2020-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document and Preimesberger et al. 2020. 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 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "onlineresource_set": [] }, { "ob_id": 32370, "uuid": "9f35dbe23eee41d3a201d42c3f568d7a", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2018/icoza/data/weybourne/", "numberOfFiles": 7, "volume": 4488585, "fileFormat": "NASA-Ames", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 26561, "uuid": "ddf1032d626b45f78ce1c5e94f289a66", "short_code": "ob", "title": "ICOZA: Atmospheric species measurements of OH, HONO, HO2, NO, NO2, NOy, O3, SO2 and CO from Weybourne Atmosphere Observatory July 2015", "abstract": "This dataset contains concentration measurements of atmospheric species performed at the Weybourne Atmospheric Observatory (WAO) on the North Norfolk coast. Measurements were all performed at ground level. Data was collected from 30th June till the 31st July 2015. This data was collected as part of Integrated Chemistry of Ozone in the Atmosphere (ICOZA) project, which aimed to apply in situ measurements to examine the response of the local atmospheric ozone production rate to NOx and VOC levels. The following instruments measured these species: LOPAP – Nitrous Acid (HONO) FAGE – OH, HO2, total organic RO2 Trace gases - NO, NO2, NOy, O3, SO2 and CO Gas chromatography (GC) - volatile organic compounds The measurements and data processing were performed by researchers from the Universities of Birmingham, East Anglia, Leeds and York. In-situ measurements of the ozone production rate are still in progress." }, "onlineresource_set": [] }, { "ob_id": 32378, "uuid": "9e3e7fd15a3042e999d45e4b0548667b", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MCD12Q1", "numberOfFiles": 2838, "volume": 12294148338, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32377, "uuid": "2bdeefa63a234a18a8fd0fabd4fa62b0", "short_code": "ob", "title": "MCD12Q1 - MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD12Q1\n\n\n\n\n\nThe MODIS Land Cover Type product contains multiple classification schemes, which describe land cover properties derived from observations spanning a year's input of Terra and Aqua data. The primary land cover scheme identifies 17 land cover classes defined by the International Geosphere Biosphere Programme (IGBP), which includes 11 natural vegetation classes, 3 developed and mosiacked land classes, and three non-vegetated land classes.\n\nThe MODIS Terra + Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid product incorporates five different land cover classification schemes, derived through a supervised decision-tree classification method:\n\nLand Cover Type 1: IGBP global vegetation classification schemeLand Cover Type 2: University of Maryland (UMD) schemeLand Cover Type 3: MODIS-derived LAI/fPAR schemeLand Cover Type 4: MODIS-derived Net Primary Production (NPP) schemeLand Cover Type 5: Plant Functional Type (PFT) scheme\n\nAdditional layers include a Land Cover Type Assessment SDS, a Land Cover Percent SDS, and a Land Cover Quality Control SDS.\n\nCollection 5.1 Land Cover Type products are produced with revised training data and certain algorithm refinements. For further details, please consult the following paper:\n\nFriedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., andHuang, X. (2010). MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment, 114, 168-182.\n\nShortname: MCD12Q1 , Platform: Combined Aqua Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: annual , ArchiveSets: 6 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE41 , File Naming Convention: MCD12Q1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf AAYYYYDDD = Acquisition Year and Day of Year hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Mark Friedl, Damien Sulla-Menashe - Boston University and MODAPS SIPS - NASA. (2015). MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MCD12Q1.006 , Keywords: Climate Change, Climate Modeling, Land Cover " }, "onlineresource_set": [] }, { "ob_id": 32380, "uuid": "ba43a3b579e8484faed7ba83ce7d121d", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MCD15A2H", "numberOfFiles": 3068, "volume": 11493179517, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32379, "uuid": "6d0b4c8c5191408d943310e08ed6dd06", "short_code": "ob", "title": "MCD15A2H - MODIS/Terra+Aqua Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD15A2H\n\n\n\n\n\nThe level-4 MODIS global Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) product is composited every 8 days at 1-kilometer resolution on a Sinusoidal grid. Science Data Sets provided in the MCD15A2H include LAI, FPAR, a quality assurance rating, and standard deviation for each variable.\n\nThe LAI variable defines the number of equivalent layers of leaves relative to a unit of ground area, whereas FPAR measures the proportion of available radiation in the photosynthetically active wavelengths that are absorbed by a canopy. Both variables are used as satellite-derived parameters for calculating surface photosynthesis, evapotranspiration, and net primary production, which in turn are used to calculate terrestrial energy, carbon, water cycle processes, and biogeochemistry of vegetation.\n\nCollection-5 MODIS Combined Terra and Aqua LAI products are Validated Stage 2, accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Collection-5 MODIS/Terra FPAR products are Validated Stage 1, meaning that accuracy has been estimated using a small number of independent measurements obtained from selected locations and time periods and ground-truth/field program efforts. Although there may be later improved versions, these data are ready for use in scientific publications.\n\nShortname: MCD15A2H , Platform: Combined Aqua Terra , Instrument: MODIS , Processing Level: Level-4 , Spatial Resolution: 500 m , Temporal Resolution: 8 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE34 , File Naming Convention: MCD15A2H.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Ranga Myneni, Knyazikhin, Yuri, Taejin Park - Boston University and MODAPS SIPS - NASA. (2015). MOD15A2H MODIS/Combined Terra+Aqua Leaf Area Index/FPAR Daily L4 Global 500m SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD15A2H.006 , Keywords: Climate Change, Biomass, Evapotranspiration, Plant Phenology, Forest Composition/Vegetation Structure, Length of Growing Season, Leaf Characteristics, Canopy Characteristics, Photosynthetically Active Radiation " }, "onlineresource_set": [] }, { "ob_id": 32382, "uuid": "68cdd973b5c742bc9622978eda15af2e", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MCD19A2", "numberOfFiles": 980278, "volume": 6171666938882, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32381, "uuid": "051d6075847747329a987b2175f2affc", "short_code": "ob", "title": "MCD19A2 - MODIS/Terra+Aqua Land Aerosol Optical Depth Daily L2G Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD19A2\n\n\n\n\n\nMCD19A2 is the shortname for the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm-based Level-2 gridded (L2G) aerosol optical thickness over land surfaces product. Derived using both Terra and Aqua MODIS inputs, this L2 product is produced daily at 1 km pixel resolution. This product helps generate a number of atmospheric and geometric properties/parameters that are used to produce another facet of the MAIAC algorithm: the land surface Bidirectional Reflectance Factor.\n\nThe MCD19A2 product contains two data groups with the following Science Data Set parameters:\n\nGrid500m groupAerosol Optical Depth at 047 micronAerosol Optical Depth at 055 micronAOD Uncertainty at 047 micronFine-Mode Fraction for OceanColumn Water Vapor in cm liquid waterAOD QAAOD Model (Regional background model used)Injection Height (Smoke injection height over local surface height)Grid5km groupCosine of Solar Zenith AngleCosine of View Zenith AngleRelative Azimuth AngleScattering AngleGlint Angle\n\nThe MCD19A2 product has achieved Stage-3 validation.\n\nShortname: MCD19A2 , Platform: Combined Aqua Terra , Instrument: MODIS , Processing Level: Level-2 Tiled , Spatial Resolution: 1 km , Temporal Resolution: daily , ArchiveSets: 6 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE113 , File Naming Convention: MCD19A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Alexi Lyapustin - NASA GSFC, Yujie Wang - Univeristy of Maryland Baltimore County and MODAPS SIPS - NASA. (2015). MCD19A2 MODIS/Terra+Aqua Aerosol Optical Thickness Daily L2G Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MCD19A2.006 , Keywords: Atmospheric Correction, MODIS, MAIAC, Bidirectional Surface reflectance, Aerosols " }, "onlineresource_set": [] }, { "ob_id": 32384, "uuid": "81ecbb5a799b4ab0a7210c90cce54878", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MCD43A1", "numberOfFiles": 1865358, "volume": 132336001274763, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32383, "uuid": "ba706617a7a84034af8f13eeb86a8c9d", "short_code": "ob", "title": "MCD43A1 - MODIS/Terra+Aqua BRDF/Albedo Model Parameters Daily L3 Global - 500m", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD43A1\n\n\n\n\n\nThe MODerate-resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo Model Parameters product (MCD43A1) contains three-dimensional (3D) data sets providing users with weighting parameters for the models used to derive the Albedo and BRDF products (MCD43A3 and MCD43A4). The models support the spatial relationship and parameter characterization best describing the differences in radiation due to the scattering (anisotropy) of each pixel, relying on multi-date, atmospherically corrected, cloud-cleared input data measured over 16-day periods.\n\nBoth Terra and Aqua data are used in the generation of this product, providing the highest probability for quality assurance input data. It is designated with a shortname beginning with MCD, which is used to refer to 'combined' products, those comprised of data using both Terra and Aqua.\n\nNote that the V006 MODIS MCD43 products are retrieved daily and represent the best BRDF possible based on 16 days worth of inputs with the day of interest emphasized. Unlike the earlier reprocessed versions (where the date of the product signifies the first day of the retrieval period), and the Direct Broadcast version (where the date signifies the last day of the retrieval period), the date associated with each daily V006 retrieval is the center of the moving 16 day input window. This change is in response to user requests.\n\nVersion-5 MODIS BRDF & Albedo products have attained Validation Stage 3.\n\nShortname: MCD43A1 , Platform: Combined Aqua Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: daily , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE23 , File Naming Convention: MCD43A1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Crystal Schaaf - University of Massachusetts Boston, Zhuosen Wang - NASA GSFC and MODAPS SIPS - NASA. (2015). MCD43A1C MODIS/Terra+Aqua BRDF/Albedo Model Parameters Daily L3 Global - 500m. NASA LP DAAC. http://doi.org/10.5067/MODIS/MCD43A1C.006 , Keywords: Climate Change, Albedo, Reflectance " }, "onlineresource_set": [] }, { "ob_id": 32386, "uuid": "978535859cc3402b985cb9f5ead22639", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MCD43A2", "numberOfFiles": 1218582, "volume": 14700434193638, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32385, "uuid": "cf8e3e801a114979a160e809deb5cc9f", "short_code": "ob", "title": "MCD43A2 - MODIS/Terra+Aqua BRDF/Albedo Quality Daily L3 Global - 500m", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD43A2\n\n\n\n\n\nThe MODerate-resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo Quality product (MCD43A2) describes the overall condition of the other BRDF and Albedo products. The MCD43A2 product contains 16 days of data at 500 meter spatial resolution provided in a level-3 gridded data set in Sinusoidal projection, and includes albedo quality assurance, snow conditions, ancillary information, and inversion information.\n\nBoth Terra and Aqua data are used in the generation of this product, providing the highest probability for quality assurance input data. It is designated with a shortname beginning with MCD, which is used to refer to 'combined' products, those comprised of data using both Terra and Aqua.\n\nNote that the V006 MODIS MCD43 products are retrieved daily and represent the best BRDF possible based on 16 days worth of inputs with the day of interest emphasized. Unlike the earlier reprocessed versions (where the date of the product signifies the first day of the retrieval period), and the Direct Broadcast version (where the date signifies the last day of the retrieval period), the date associated with each daily V006 retrieval is the center of the moving 16 day input window. This change is in response to user requests.\n\nVersion-5 MODIS BRDF & Albedo products have attained Validation Stage 3.\n\nShortname: MCD43A2 , Platform: Combined Aqua Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: daily , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE23 , File Naming Convention: MCD43A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Crystal Schaaf - University of Massachusetts Boston, Zhuosen Wang - NASA GSFC and MODAPS SIPS - NASA. (2015). MCD43A2C MODIS/Terra+Aqua BRDF/Albedo Quality Daily L3 Global - 500m. NASA LP DAAC. http://doi.org/10.5067/MODIS/MCD43A2C.006 , Keywords: Climate Change, Albedo, Reflectance " }, "onlineresource_set": [] }, { "ob_id": 32388, "uuid": "addc6d9d599b44b095d3dba086ed3a94", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MCD43A3", "numberOfFiles": 1942163, "volume": 84219885167950, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32387, "uuid": "48efa9b67d69435caffd2d06cf8406d3", "short_code": "ob", "title": "MCD43A3 - MODIS/Terra+Aqua BRDF/Albedo Daily L3 Global - 500m", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD43A3\n\n\n\n\n\nThe MODerate-resolution Imaging Spectroradiometer (MODIS) Albedo product (MCD43A3) provides 500-meter data describing both directional hemispherical reflectance (black-sky albedo) and bihemispherical reflectance (white-sky albedo). The MCD43A3 product contains 16 days of data provided in a level-3 gridded data set in Sinusoidal projection.\n\nBoth Terra and Aqua data are used in the generation of this product, providing the highest probability for quality assurance input data. It is designated with a shortname beginning with MCD, which is used to refer to 'combined' products, those comprised of data using both Terra and Aqua.\n\nNote that the V006 MODIS MCD43 products are retrieved daily and represent the best BRDF possible based on 16 days worth of inputs with the day of interest emphasized. Unlike the earlier reprocessed versions (where the date of the product signifies the first day of the retrieval period), and the Direct Broadcast version (where the date signifies the last day of the retrieval period), the date associated with each daily V006 retrieval is the center of the moving 16 day input window. This change is in response to user requests.\n\nVersion-5 MODIS BRDF & Albedo products have attained Validation Stage 3.\n\nShortname: MCD43A3 , Platform: Combined Aqua Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: daily , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE23 , File Naming Convention: MCD43A3.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Crystal Schaaf - University of Massachusetts Boston, Zhuosen Wang - NASA GSFC and MODAPS SIPS - NASA. (2015). MCD43A3 MODIS/Terra+Aqua BRDF/Albedo Daily L3 Global - 500m. NASA LP DAAC. http://doi.org/10.5067/MODIS/MCD43A3.006 , Keywords: Climate Change, Albedo, Reflectance " }, "onlineresource_set": [] }, { "ob_id": 32390, "uuid": "bf0be052be104632a9cf91fa620e98ca", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MCD64A1", "numberOfFiles": 51466, "volume": 99084227056, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32389, "uuid": "0f3d112f9da048a786d3f54e08b4d642", "short_code": "ob", "title": "MCD64A1 - Combined Level 3 Direct Broadcast Burned Area Monthly Global 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MCD64A1\n\n\n\n\n\nMCD64A1 Burned Area Product is a monthly Level-3 gridded 500-meter product containing per-pixel burning and quality information, and tile-level metadata.\n\nThe MODIS Collection 6 burned-area mapping approach employs daily 500-m MODIS surface reflectance data coupled with 1-km MODIS active fire observations. The hybrid algorithm applies dynamic thresholds to composite imagery generated from a burn-sensitive vegetation index derived from MODIS short-wave infrared channels 5 and 7, and a measure of temporal texture. Cumulative active fire maps are used to guide the selection of burned and unburned training samples and to guide the specification of prior probabilities. The combined use of active-fire and reflectance data enables the algorithm to adapt regionally over a wide range of pre- and post-burn conditions and across multiple ecosystems.\n\nShortname: MCD64A1 , Platform: Combined Aqua Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: monthly , ArchiveSets: 6 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE134 , File Naming Convention: MCD64A1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Keywords: Climate Change, Fires, Wildfires " }, "onlineresource_set": [] }, { "ob_id": 32392, "uuid": "343b527d1f714bfd81e3457918d68a4a", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD021KM", "numberOfFiles": 2703725, "volume": 313225769951764, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32391, "uuid": "55aa94abf6bf40fab87143f24849ac89", "short_code": "ob", "title": "MOD021KM - Level 1B Calibrated Radiances - 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD021KM\n\n\n\n\n\n\"The MODIS Level-1B data set contains calibrated and geolocated at-aperture radiances for 36 discrete bands located in the 0.4 µm to 14.4 µm region of the electromagentic spectrum. These data are generated from MODIS Level-1A scans of raw radiance, and in the process are converted to geophysical units of W/(m2µm sr). In addition, the Bidirectional Reflectance Distribution Function (BRDF) may be determined for the solar reflective bands (1-19, 26) through knowledge of the solar irradiance (e.g., determined from MODIS solar diffuser data, and from the target illumination geometry). Additional data are provided including quality flags, error estimates and calibration data.\n\nVisible, shortwave infrared, and near infrared measurements are only made during the daytime, while radiances for the thermal infrared region (bands 20-25, 27-36) are measured continuously.\n\nThe resolution of channels 1 and 2 is 250 m, channels 3 through 7 are 500m resolution, and the rest are 1 km resolution. However, for the MODIS L1B 1 km product, the 250 m and 500 m band radiance data and their associated uncertainties have been aggregated to 1 km resolution. Thus, the entire channel data set is referenced to the same spatial and geolocation scales. Separate L1B products are available for just the 250 m channels (MOD02QKM) and the 500 m channels (MOD02HKM) that preserve the original resolution of the data.\n\nSpatial resolution for pixels at nadir is 1 km, degrading to 4.8 km in the along-scan direction at the scan extremes. However, thanks to the overlapping of consecutive swaths and the respective pixels there, the resulting resolution at the scan extremes is about 2 km. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330 km orbital swath width with global coverage every one to two days. A single MODIS Level-1B granule will nominally contain a scene built from 203 scans (or swaths) sampled 1354 times in the cross-track direction, corresponding to approximately 5 minutes worth of data. Since an individual MODIS scan (or swath) will contain 10 along-track spatial elements, the scene will be composed of 1354 by 2030 pixels, resulting in a spatial coverage of 2330 km by 2030 km. Due to the MODIS scan geometry, there will be increasing overlap occurring beyond about a 25 degree scan angle.\n\nUsers requiring the full-resolution geolocation and solar/satellite geometry can obtain the separate MODIS Level-1 Geolocation product (MOD03) from LAADS.\"\n\nShortname: MOD021KM , Platform: Terra , Instrument: MODIS , Processing Level: Level-1B , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE02 , File Naming Convention: MOD021KM.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time YYYYDDD = Year and Day of Year of acquisition , Citation: MODIS Characterization Support Team (MCST), 2017. MODIS 1km Calibrated Radiances Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MOD021KM.061 , Keywords: Climate Change, Radiance " }, "onlineresource_set": [] }, { "ob_id": 32394, "uuid": "5e7d0714041c4669a022a19f6c07f760", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD04_L2", "numberOfFiles": 1499706, "volume": 3730802415990, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32393, "uuid": "f5e2886edf254a42804b9a77af6d5c9c", "short_code": "ob", "title": "MOD04_L2 - MODIS/Terra Aerosol 5-Min L2 Swath 10km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD04_L2\n\n\n\n\n\n\"The MODIS Aerosol Product monitors the ambient aerosol optical thickness over the oceans globally and over a portion of the continents. Further, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents. Daily Level-2 data are produced at the spatial resolution of a 10x10 1-km pixel array (at nadir).\n\nPrior to MODIS, satellite measurements were limited to reflectance measurements in one (GOES, METEOSAT) or two (AVHRR) channels. There was no real attempt to retrieve aerosol content over land on a global scale. Algorithms had been developed for use only over dark vegetation. The blue channel on MODIS, not present on AVHRR, offers the possibility to extend the derivation of optical thickness over land to additional surfaces. The algorithms use MODIS bands 1 through 7 and 20 and require prior cloud screening using MODIS data. Over the land, the dynamic aerosol models are derived from ground-based sky measurements and used in the net retrieval process.\n\nOver the ocean, three parameters that describe the aerosol loading and size distribution are retrieved. Pre-assumptions on the general structure of the size distribution are required in the inversion of MODIS data, and the volume-size distribution is described with two log-normal modes: a single mode to describe the accumulation mode particles (radius < 0.5 µm) and a single coarse mode to describe dust and/or salt particles (radius > 1.0 µm).\n\nThe quality assurance control of these products will be based on comparison with ground stations and climatology.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates. \"\n\nShortname: MOD04_L2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 10 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE04 , File Naming Convention: MOD04_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Levy, R., Hsu, C., et al., 2015. MODIS Atmosphere L2 Aerosol Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MOD04_L2.061 , Keywords: Climate Change, Atmospheric Correction, Aerosol Optical Depth/Thickness " }, "onlineresource_set": [] }, { "ob_id": 32396, "uuid": "3db212daa3234dda9efc7a1b47f8f86a", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD06_L2", "numberOfFiles": 2774352, "volume": 175835672066627, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32395, "uuid": "be30127db24d45c3826367af7d0fcc44", "short_code": "ob", "title": "MOD06_L2 - MODIS/Terra Clouds 5-Min L2 Swath 1km and 5km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD06_L2\n\n\n\n\n\nThe MODIS Level-2 Cloud product consists of cloud optical and physical parameters. These parameters are derived using remotely sensed infrared, visible and near infrared solar reflected radiances. MODIS infrared channel radiances are used to derive cloud top temperature, cloud top height, effective emissivity, cloud phase (ice vs. water, opaque vs. non-opaque), and cloud fraction under both daytime and nighttime conditions. MODIS visible radiances are used to derive cloud optical thickness and effective particle radius and cloud shadow effects. Near-infrared solar reflected radiance provides additional information for the retrieval of cloud particle phase (ice vs. water, clouds vs. snow). The shortname for this Level-2 MODIS cloud product is MOD06_L2. MOD06_L2 consists of parameters at a spatial resolution of either 1km or 5km (at nadir). Each MOD06_L2 product file covers a 5-minute time interval. This means that for 5km resolution parameters, the output grid is 270 pixels wide by 406 pixels in length. Every tenth granule has an output grid size of 270 by 408 pixels. For 1-km resolution parameters, the output grid is 1354 pixels in width by 2030 pixels in length and every tenth granule has an output grid size of 1354 by 2040 pixels.\n\nMOD06_L2 product files are stored in Hierarchical Data Format (HDF-EOS). All gridded cloud parameters are stored as Scientific Data Sets (SDS) within the file, except two (band number and statistics). These are stored as Vdata (table arrays). Approximately 288 files are produced daily. Nighttime files are smaller than their daytime counterparts since only the cloud top properties are retrieved at night.\n\nThe MODIS Cloud Product will be used to investigate seasonal and inter-annual changes in cirrus (semi-transparent) global cloud cover and cloud phase with multispectral observations at 1km spatial resolution.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates.\n\nShortname: MOD06_L2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE06 , File Naming Convention: MOD06_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Platnick, S., Ackerman, S., King, M., et al., 2015. MODIS Atmosphere L2 Cloud Product (06_L2). NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MOD06_L2.061 , Keywords: Water Vapor, Precipitable Water " }, "onlineresource_set": [] }, { "ob_id": 32398, "uuid": "c5da0dfb51ad4eafbda1d3ca217ed53e", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD11A1", "numberOfFiles": 1362985, "volume": 2773452117017, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32397, "uuid": "35bb28eafbaa461db578e1218808c038", "short_code": "ob", "title": "MOD11A1 - MODIS/Terra Land Surface Temperature/Emissivity Daily L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD11A1\n\n\n\n\n\nThe MODIS/Terra Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based to grid-based global products. The MODIS/Terra LST/E Daily L3 Global 1 km SIN Grid,(Short name: MOD11A1), is a gridded version of the L2 Daily LST/E data set, whose LSTs are retrieved by the split-window algorithm.\n\nThe Collection-4 (C4) LST/E L3 MOD11A1 product inputs include the MODIS L1B calibrated and geolocated radiances, geolocation, cloud mask, atmospheric profiles, land and snow cover. The band 31 and 32 emissivities are estimated by a classification-based emissivity method, which relies on the pixel's land cover type as determined by the land and snow cover inputs. Until June 2001, the AVHRR-based IGBP land cover product was used. Following that time, MODIS-derived land cover product was used. The estimated emissivities in arid and semi-arid areas are potentially uncertain, and users are advised to exercise caution in their applications. The day/night alogorithm extracts average temperatures (in Kelvin) and applies them to a pair of MODIS daytime and nighttime observations. This method yields 1 K accuracy for materials with known emissivities. The V4 MOD11A1 product has a temporal acquisition range of February 24, 2000 (2000-055) until January 3, 2007 (200-003). The C4 collection remains consistent with C41, and users may combine the two collections in a time-series analysis.\n\nThe MODIS/Terra Collection 41 (C41) products use a modified Collection-4 (C4) LST algorithm and Collection-5 (C5) data inputs. The C41 products primarily address underestimation problems in the C5 Climate Modeling Grid (CMG) products. Recent validation activities reveal that the C5 CMG products underestimate LSTs up to 6K especially in desert and semi-arid regions. The availability of this collection starts with MODIS/Terra data acquisition on January 1, 2007 (2007-001). This date is driven by the availability of the MODIS C5 data inputs (level-1B radiance data, geolocation data, cloud mask, atmospheric profiles, and land and snow cover data).\n\nThe MODIS/Terra C5 LST/E L3 Global 5 km Grid product incorporates 1-km pixels, which are produced daily using the generalized split-window LST algorithm. This algorithm is optimally used to separate ranges of atmospheric column water vapor and lower boundary air surface temperatures into tractable sub-ranges. The surface emissivities in bands 31 and 32 are estimated from land cover types. The C5 MOD11_L2 product's acquisition range started March 5, 2000 (2000-065) and will continue until some time after the C6 reprocessing is complete.\n\nThe C41 and C5 MODIS/Terra LST/E products, including the MOD11A1, are validated to Stage-2 with well-defined uncertainties over a range of representative conditions. Further details regarding MODIS land product validation for the LST/E products are available from the MODIS land team validation site referenced under 'Val Status' section.\n\nThe C41 LST products from 2007-001 will remain consistent with similar products from C4, and hence are amenable to combine them in a time-series analysis. Users should exercise caution, and not mix the C4.x (i.e., C4 and C41) and C5 LST products in their analyses.\n\nShortname: MOD11A1 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: daily , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE16M , File Naming Convention: MOD11A1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Zhengming Wan - University of California Santa Barbara, Simon Hook, Glynn Hulley - JPL and MODAPS SIPS - NASA. (2015). MOD11A1 MODIS/Terra Land Surface Temperature and the Emissivity Daily L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD11A1.006 , Keywords: Climate Change, Land Surface Temperature, Emissivity, Fires " }, "onlineresource_set": [] }, { "ob_id": 32400, "uuid": "24b9566ec5714b59981bf4db4e1afe07", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD11A2", "numberOfFiles": 70048, "volume": 266773663355, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32399, "uuid": "15f057994f074b08a60daa1f188014e6", "short_code": "ob", "title": "MOD11A2 - MODIS/Terra Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD11A2\n\n\n\n\n\nThe MOD11A2 Level-3 MODIS Land Surface Temperature and Emissivity (LST/E) 8-day products are composed of data from the daily 1-kilometer LST product (MOD11A1) stored on a 1-km Sinusoidal grid as the average values of clear-sky LSTs during an 8-day period.\n\nMOD11A2 is comprised of daytime and nighttime LSTs, quality assurance assessment, observation times, view angles, bits of clear sky days and nights, and emissivities estimated in Bands 31 and 32 from land cover types.\n\nCollection-5 MODIS/Terra Land Surface Temperature/Emissivity products are validated to Stage 2, which means that their accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Further details regarding MODIS land product validation for the LST/E products are available from the following URL: http://landval.gsfc.nasa.gov/ProductStatus.php?ProductID=MOD11.\n\nShortname: MOD11A2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: 8 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE31 , File Naming Convention: MOD11A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Zhengming Wan - University of California Santa Barbara, Simon Hook, Glynn Hulley - JPL and MODAPS SIPS - NASA. (2015). MOD11A2 MODIS/Terra Land Surface Temperature and the Emissivity 8-Day L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD11A2.006 , Keywords: Climate Change, Land Surface Temperature, Emissivity, Fires " }, "onlineresource_set": [] }, { "ob_id": 32402, "uuid": "3e7fd716381a435ba1fcae09e1f1d276", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD13A2", "numberOfFiles": 57650, "volume": 527218355189, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32401, "uuid": "d65aab04c69b4df391e6e7fc4b901aef", "short_code": "ob", "title": "MOD13A2 - MODIS/Terra Vegetation Indices 16-Day L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD13A2\n\n\n\n\n\nGlobal MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared reflectances, centered at 469-nanometers, 645-nanometers, and 858-nanometers, respectively, are used to determine the MODIS daily vegetation indices.\n\nThe MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's Advanced Very High Resolution Radiometer (AVHRR) NDVI products providing continuity for time series applications over this rich historical archive. MODIS also includes a new Enhanced Vegetation Index (EVI) product that minimizes canopy background variations and maintains sensitivity over dense vegetation conditions. The EVI also uses the blue band to remove residual atmosphere contamination caused by smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI products are computed from atmospherically-corrected bi-directional surface reflectances that have been masked for water, clouds, heavy aerosols, and cloud shadows.\n\nGlobal MOD13A2 data are provided every 16 days at 1-kilometer spatial resolution as a gridded level-3 product in the Sinusoidal projection. Vegetation indices are used for global monitoring of vegetation conditions and are used in products displaying land cover and land cover changes. These data may be used as input for modeling global biogeochemical and hydrologic processes and global and regional climate. These data also may be used for characterizing land surface biophysical properties and processes, including primary production and land cover conversion.\n\nCollection-5 MODIS/Terra Vegetation Indices products are Validated at Stage 2, meaning that accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Although there may be later improved versions, these data are ready for use in scientific publications.\n\nShortname: MOD13A2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: 16 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE35 , File Naming Convention: MOD13A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Kamel Didan - University of Arizona, Alfredo Huete - University of Technology Sydney and MODAPS SIPS - NASA. (2015). MOD13A2 MODIS/Terra Vegetation Indices 16-Day L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD13A2.006 , Keywords: Climate Change, Canopy Characteristics, Biomass, Vegetation Index, Plant Phenology, Length of Growing Season " }, "onlineresource_set": [] }, { "ob_id": 32404, "uuid": "1b825b9a356248ec9ac6e5e3e7159575", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD14A1", "numberOfFiles": 7, "volume": 2866, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32403, "uuid": "e3ee4b286e97482fb3c979ca9268f228", "short_code": "ob", "title": "MOD14A1 - MODIS/Terra Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD14A1\n\n\n\n\n\nMODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of a fire (when the fire strength is sufficient to detect), and on detection relative to its background (to account for variability of the surface temperature and reflection by sunlight). Numerous tests are employed to reject typical false alarm sources like sun glint or an unmasked coastline.\n\nMOD14A1 is produced every 8 days at 1-kilometer resolution as a gridded level-3 product in the Sinusoidal projection. This product is unique in that it has three dimensions: fire-mask (1D) and a maximum fire-radiative-power (2D) are provided for each day (3D) in the 8-day period. For example, the fire-mask contains eight, band sequential (day) 1200 x 1200 images of fire data representing consecutive days of data collection.\n\nThe Terra MODIS instrument acquires data twice daily (10:30 AM and PM), as does the Aqua MODIS (1:30 PM and AM). These four daily MODIS fire observations serve to advance global monitoring of the fire process and its effects on ecosystems, the atmosphere, and climate.\n\nCollection-5 MODIS/Terra Thermal Anomalies/Fire products are Validated Stage 3, meaning that uncertainties in the product and its associated structure are well quantified from comparison with reference in situ or other suitable reference data. These data are ready for use in scientific publications.\n\nShortname: MOD14A1 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: daily , ArchiveSets: 6 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE29 , File Naming Convention: MOD14A1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Louis Giglio, Chris Justice - University of Maryland and MODAPS SIPS - NASA. (2015). MOD14A1 MODIS/Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD14A1.006 , Keywords: Climate Change, Land Surface Temperature, Fires " }, "onlineresource_set": [] }, { "ob_id": 32406, "uuid": "f6b2f5fff89945a3b2d9c4bdee4de69c", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD35_L2", "numberOfFiles": 1567970, "volume": 12183761451887, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32405, "uuid": "2a777ecbac9847639617c053072c4af2", "short_code": "ob", "title": "MOD35_L2 - MODIS/Terra Cloud Mask and Spectral Test Results 5-Min L2 Swath 250m and 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD35_L2\n\n\n\n\n\n\"\nThe MODIS Cloud Mask product is a Level-2 product generated at 1-km and 250-m (at nadir) spatial resolutions. The algorithm employs a series of visible and infrared threshold and consistency tests to specify confidence that an unobstructed view of the Earth's surface has been observed. An indication of shadows affecting the scene is also provided. The 250-m cloud mask flags are based on visible channel data only. Radiometrically-accurate radiances are required, thus holes in the Cloud Mask will appear wherever the input radiances are incomplete or of poor quality assurance. There are two MODIS Cloud Mask data product files: MOD35_L2, containing data collected from the Terra platform; and MYD35_L2, containing data collected from the Aqua platform.\n\nThe MODIS cloud mask algorithm employs a battery of spectral tests, which use methodology applied in the AVHRR Processing scheme Over cLoudy Land and Ocean (APOLLO), International Satellite Cloud Climatology Project (ISCCP), CLoud Advanced Very high resolution Radiometer (CLAVR), and the Support of Environmental Requirements for Cloud Analysis and Archive (SERCAA) algorithms to identify cloudy FOVs. From these, a clear-sky confidence level (high confident clear, probably clear, undecided, cloudy) is assigned to each FOV. For inconclusive results, spatial- and temporal-variability tests are applied. The spectral tests rely on radiance (temperature) thresholds in the infrared and reflectance thresholds in the visible and near-infrared. Thresholds vary with surface type, atmospheric conditions (moisture, aerosol, etc.), and viewing geometry. In addition to the MOD02 calibrated radiances, a 1-km land/water mask, DEM, ecosystem analysis, snow/ice cover map, NCEP analysis of surface temperature and wind speed, and an estimate of precipitable water are required as inputs.\n\nA determination of the presence of global cloudiness is essential to the MODIS mission for two reasons. First, clouds play a critical role in the radiative balance of the Earth and must be accurately described to assess climate and potential climate change. Second, the presence of cloudiness must be accurately determined to properly retrieve many atmospheric and surface parameters. For many of these retrieval algorithms even thin cirrus represents contamination.\n\nCloud mask validation will be conducted using MODIS Airborne Simulator (MAS) data from several field campaigns, all-sky cameras, and comparison with NOAA operational instruments and possibly ASTER.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates. \"\n\nShortname: MOD35_L2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 250 m, 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE03 , File Naming Convention: MOD35_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Ackerman, S., et al., 2015. MODIS Atmosphere L2 Cloud Mask Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MOD35_L2.061 , Keywords: Cloud Fraction, Climate Change, Atmospheric Correction " }, "onlineresource_set": [] }, { "ob_id": 32408, "uuid": "17a7aaa68b24412e82ffebebd5d0abcd", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD021KM", "numberOfFiles": 2478522, "volume": 272449524400264, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32407, "uuid": "121756ef259340b0a0ac0f50e39a5220", "short_code": "ob", "title": "MYD021KM - Level 1B Calibrated Radiances - 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD021KM\n\n\n\n\n\n\"The MODIS Level-1B data set contains calibrated and geolocated at-aperture radiances for 36 discrete bands located in the 0.4 µm to 14.4 µm region of the electromagentic spectrum. These data are generated from MODIS Level-1A scans of raw radiance, and in the process are converted to geophysical units of W/(m2µm sr). In addition, the Bidirectional Reflectance Distribution Function (BRDF) may be determined for the solar reflective bands (1-19, 26) through knowledge of the solar irradiance (e.g., determined from MODIS solar diffuser data, and from the target illumination geometry). Additional data are provided including quality flags, error estimates and calibration data.\n\nVisible, shortwave infrared, and near infrared measurements are only made during the daytime, while radiances for the thermal infrared region (bands 20-25, 27-36) are measured continuously.\n\nThe resolution of channels 1 and 2 is 250 m, channels 3 through 7 are 500m resolution, and the rest are 1 km resolution. However, for the MODIS L1B 1 km product, the 250 m and 500 m band radiance data and their associated uncertainties have been aggregated to 1 km resolution. Thus, the entire channel data set is referenced to the same spatial and geolocation scales. Separate L1B products are available for just the 250 m channels (MYD02QKM) and the 500 m channels (MYD02HKM) that preserve the original resolution of the data.\n\nSpatial resolution for pixels at nadir is 1 km, degrading to 4.8 km in the along-scan direction at the scan extremes. However, thanks to the overlapping of consecutive swaths and the respective pixels there, the resulting resolution at the scan extremes is about 2 km. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330 km orbital swath width with global coverage every one to two days. A single MODIS Level-1B granule will nominally contain a scene built from 203 scans (or swaths) sampled 1354 times in the cross-track direction, corresponding to approximately 5 minutes worth of data. Since an individual MODIS scan (or swath) will contain 10 along-track spatial elements, the scene will be composed of 1354 by 2030 pixels, resulting in a spatial coverage of 2330 km by 2030 km. Due to the MODIS scan geometry, there will be increasing overlap occurring beyond about a 25 degree scan angle.\n\nUsers requiring the full-resolution geolocation and solar/satellite geometry can obtain the separate MODIS Level-1 Geolocation product (MYD03) from LAADS.\"\n\nShortname: MYD021KM , Platform: Aqua , Instrument: MODIS , Processing Level: Level-1B , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE02 , File Naming Convention: MYD021KM.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time YYYYDDD = Year and Day of Year of acquisition , Citation: MODIS Characterization Support Team (MCST), 2017. MODIS 1km Calibrated Radiances Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD021KM.061 , Keywords: Climate Change, Radiance " }, "onlineresource_set": [] }, { "ob_id": 32410, "uuid": "ce185ac9258143fabf1fb6f7222cfb14", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD04_L2", "numberOfFiles": 1358202, "volume": 3269775529851, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32409, "uuid": "1f4e19c154e64d2489d6516d5fd19f91", "short_code": "ob", "title": "MYD04_L2 - MODIS/Aqua Aerosol 5-Min L2 Swath 10km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD04_L2\n\n\n\n\n\n\"The MODIS Aerosol Product monitors the ambient aerosol optical thickness over the oceans globally and over a portion of the continents. Further, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents. Daily Level-2 data are produced at the spatial resolution of a 10x10 1-km pixel array (at nadir).\n\nPrior to MODIS, satellite measurements were limited to reflectance measurements in one (GOES, METEOSAT) or two (AVHRR) channels. There was no real attempt to retrieve aerosol content over land on a global scale. Algorithms had been developed for use only over dark vegetation. The blue channel on MODIS, not present on AVHRR, offers the possibility to extend the derivation of optical thickness over land to additional surfaces. The algorithms use MODIS bands 1 through 7 and 20 and require prior cloud screening using MODIS data. Over the land, the dynamic aerosol models are derived from ground-based sky measurements and used in the net retrieval process.\n\nOver the ocean, three parameters that describe the aerosol loading and size distribution are retrieved. Pre-assumptions on the general structure of the size distribution are required in the inversion of MODIS data, and the volume-size distribution is described with two log-normal modes: a single mode to describe the accumulation mode particles (radius < 0.5 µm) and a single coarse mode to describe dust and/or salt particles (radius > 1.0 µm).\n\nThe quality assurance control of these products will be based on comparison with ground stations and climatology.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates. \"\n\nShortname: MYD04_L2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 10 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE04 , File Naming Convention: MYD04_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Levy, R., Hsu, C., et al., 2015. MODIS Atmosphere L2 Aerosol Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD04_L2.061 , Keywords: Climate Change, Atmospheric Correction, Aerosol Optical Depth/Thickness " }, "onlineresource_set": [] }, { "ob_id": 32412, "uuid": "0373369fe1664532941f29947a344ff0", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD06_L2", "numberOfFiles": 2513681, "volume": 146077385085823, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32411, "uuid": "b5e81b4a2be145b990ae3b8e198f9266", "short_code": "ob", "title": "MYD06_L2 - MODIS/Aqua Clouds 5-Min L2 Swath 1km and 5km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD06_L2\n\n\n\n\n\nThe MODIS Level-2 Cloud product consists of cloud optical and physical parameters. These parameters are derived using remotely sensed infrared, visible and near infrared solar reflected radiances. MODIS infrared channel radiances are used to derive cloud top temperature, cloud top height, effective emissivity, cloud phase (ice vs. water, opaque vs. non-opaque), and cloud fraction under both daytime and nighttime conditions. MODIS visible radiances are used to derive cloud optical thickness and effective particle radius and cloud shadow effects. Near-infrared solar reflected radiance provides additional information for the retrieval of cloud particle phase (ice vs. water, clouds vs. snow). The shortname for this Level-2 MODIS cloud product is MYD06_L2. MYD06_L2 consists of parameters at a spatial resolution of either 1km or 5km (at nadir). Each MYD06_L2 product file covers a 5-minute time interval. This means that for 5km resolution parameters, the output grid is 270 pixels wide by 406 pixels in length. Every tenth granule has an output grid size of 270 by 408 pixels. For 1-km resolution parameters, the output grid is 1354 pixels in width by 2030 pixels in length and every tenth granule has an output grid size of 1354 by 2040 pixels.\n\nMYD06_L2 product files are stored in Hierarchical Data Format (HDF-EOS). All gridded cloud parameters are stored as Scientific Data Sets (SDS) within the file, except two (band number and statistics). These are stored as Vdata (table arrays). Approximately 288 files are produced daily. Nighttime files are smaller than their daytime counterparts since only the cloud top properties are retrieved at night.\n\nThe MODIS Cloud Product will be used to investigate seasonal and inter-annual changes in cirrus (semi-transparent) global cloud cover and cloud phase with multispectral observations at 1km spatial resolution.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates.\n\nShortname: MYD06_L2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE06 , File Naming Convention: MYD06_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Platnick, S., Ackerman, S., King, M., et al., 2015. MODIS Atmosphere L2 Cloud Product (06_L2). NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD06_L2.061 , Keywords: Water Vapor, Precipitable Water " }, "onlineresource_set": [] }, { "ob_id": 32414, "uuid": "877a548ee6bb485da01804c0207d91c5", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD11A1", "numberOfFiles": 1305863, "volume": 2663764927081, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32413, "uuid": "56b3282c25604434bc1417ab70ba9c79", "short_code": "ob", "title": "MYD11A1 - MODIS/Aqua Land Surface Temperature/Emissivity Daily L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD11A1\n\n\n\n\n\nThe MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based to grid-based global products. The MODIS/Aqua LST/E Daily L3 Global 1 km SIN Grid,(Short name: MYD11A1), is a gridded version of the L2 Daily LST/E data set, whose LSTs are retrieved by the split-window algorithm.\n\nThe Collection-4 (C4) LST/E L3 MYD11A1 product inputs include the MODIS L1B calibrated and geolocated radiances, geolocation, cloud mask, atmospheric profiles, land and snow cover. The band 31 and 32 emissivities are estimated by a classification-based emissivity method, which relies on the pixel's land cover type as determined by the land and snow cover inputs. Until June 2001, the AVHRR-based IGBP land cover product was used. Following that time, MODIS-derived land cover product was used. The estimated emissivities in arid and semi-arid areas are potentially uncertain, and users are advised to exercise caution in their applications. The day/night alogorithm extracts average temperatures (in Kelvin) and applies them to a pair of MODIS daytime and nighttime observations. This method yields 1 K accuracy for materials with known emissivities. The V4 MYD11A1 product has a temporal acquisition range of February 24, 2000 (2000-055) until January 3, 2007 (200-003). The C4 collection remains consistent with C41, and users may combine the two collections in a time-series analysis.\n\nThe MODIS/Aqua Collection 41 (C41) products use a modified Collection-4 (C4) LST algorithm and Collection-5 (C5) data inputs. The C41 products primarily address underestimation problems in the C5 Climate Modeling Grid (CMG) products. Recent validation activities reveal that the C5 CMG products underestimate LSTs up to 6K especially in desert and semi-arid regions. The availability of this collection starts with MODIS/Aqua data acquisition on January 1, 2007 (2007-001). This date is driven by the availability of the MODIS C5 data inputs (level-1B radiance data, geolocation data, cloud mask, atmospheric profiles, and land and snow cover data).\n\nThe MODIS/Aqua C5 LST/E L3 Global 5 km Grid product incorporates 1-km pixels, which are produced daily using the generalized split-window LST algorithm. This algorithm is optimally used to separate ranges of atmospheric column water vapor and lower boundary air surface temperatures into tractable sub-ranges. The surface emissivities in bands 31 and 32 are estimated from land cover types. The C5 MYD11_L2 product's acquisition range started March 5, 2000 (2000-065) and will continue until some time after the C6 reprocessing is complete.\n\nThe C41 and C5 MODIS/Aqua LST/E products, including the MYD11A1, are validated to Stage-2 with well-defined uncertainties over a range of representative conditions. Further details regarding MODIS land product validation for the LST/E products are available from the MODIS land team validation site referenced under 'Val Status' section.\n\nThe C41 LST products from 2007-001 will remain consistent with similar products from C4, and hence are amenable to combine them in a time-series analysis. Users should exercise caution, and not mix the C4.x (i.e., C4 and C41) and C5 LST products in their analyses.\n\nShortname: MYD11A1 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: daily , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE16M , File Naming Convention: MYD11A1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Zhengming Wan - University of California Santa Barbara, Simon Hook, Glynn Hulley - JPL and MODAPS SIPS - NASA. (2015). MYD11A1 MODIS/Aqua Land Surface Temperature and the Emissivity Daily L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MYD11A1.006 , Keywords: Climate Change, Land Surface Temperature, Emissivity, Fires " }, "onlineresource_set": [] }, { "ob_id": 32416, "uuid": "4e9b42786ae442eaada5627fa7c2ee73", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD11A2", "numberOfFiles": 97627, "volume": 380310356946, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32415, "uuid": "dfa34fb44ba649bf91397ff5a3eeae49", "short_code": "ob", "title": "MYD11A2 - MODIS/Aqua Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD11A2\n\n\n\n\n\nThe level-3 MODIS Land Surface Temperature and Emissivity (LST/E) 8-day data products are composed of data from the daily 1-kilometer LST product (MYD11A1) and stored on a 1-km Sinusoidal grid as the average values of clear-sky LSTs during an 8-day period.\n\nMYD11A2 is comprised of daytime and nighttime LSTs, quality assurance assessment, observation times, view angles, bits of clear sky days and nights, and emissivities estimated in Bands 31 and 32 from land cover types.\n\nCollection-5 MODIS/Aqua Land Surface Temperature/Emissivity products are validated to Stage 2, which means that their accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Further details regarding MODIS land product validation for the LST/E products are available from the following URL: http://landval.gsfc.nasa.gov/ProductStatus.php?ProductID=MYD11.\n\nShortname: MYD11A2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: 8 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE31 , File Naming Convention: MYD11A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Zhengming Wan - University of California Santa Barbara, Simon Hook, Glynn Hulley - JPL and MODAPS SIPS - NASA. (2015). MYD11A2 MODIS/Aqua Land Surface Temperature and the Emissivity 8-Day L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MYD11A2.006 , Keywords: Climate Change, Land Surface Temperature, Emissivity, Fires " }, "onlineresource_set": [] }, { "ob_id": 32418, "uuid": "a806d66490b541f9843cb49b41e597f8", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD13A2", "numberOfFiles": 42205, "volume": 389452185266, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32417, "uuid": "f10420bececd447eb1b74db9d66ef12a", "short_code": "ob", "title": "MYD13A2 - MODIS/Aqua Vegetation Indices 16-Day L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD13A2\n\n\n\n\n\nGlobal MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared reflectances, centered at 469-nanometers, 645-nanometers, and 858-nanometers, respectively, are used to determine the MODIS daily vegetation indices.\n\nThe MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's Advanced Very High Resolution Radiometer (AVHRR) NDVI products providing continuity for time series applications over this rich historical archive. MODIS also includes a new Enhanced Vegetation Index (EVI) product that minimizes canopy background variations and maintains sensitivity over dense vegetation conditions. The EVI also uses the blue band to remove residual atmosphere contamination caused by smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI products are computed from atmospherically-corrected bi-directional surface reflectances that have been masked for water, clouds, heavy aerosols, and cloud shadows.\n\nGlobal MYD13A2 data are provided every 16 days at 1-kilometer spatial resolution as a gridded level-3 product in the Sinusoidal projection. Vegetation indices are used for global monitoring of vegetation conditions and are used in products displaying land cover and land cover changes. These data may be used as input for modeling global biogeochemical and hydrologic processes and global and regional climate. These data also may be used for characterizing land surface biophysical properties and processes, including primary production and land cover conversion.\n\nCollection-5 MODIS/Aqua Vegetation Indices products are Validated at Stage 2, meaning that accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Although there may be later improved versions, these data are ready for use in scientific publications.\n\nShortname: MYD13A2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: 16 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE35 , File Naming Convention: MYD13A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Kamel Didan - University of Arizona, Alfredo Huete - University of Technology Sydney and MODAPS SIPS - NASA. (2015). MYD13A2 MODIS/Aqua Vegetation Indices 16-Day L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MYD13A2.006 , Keywords: Climate Change, Canopy Characteristics, Biomass, Vegetation Index, Plant Phenology, Length of Growing Season " }, "onlineresource_set": [] }, { "ob_id": 32420, "uuid": "6c98efae783b45e4ab2766a69f8dd6f7", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD35_L2", "numberOfFiles": 2484689, "volume": 19455990088840, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32419, "uuid": "bac493ecc5f14b4d809f35f89eceb834", "short_code": "ob", "title": "MYD35_L2 - MODIS/Aqua Cloud Mask and Spectral Test Results 5-Min L2 Swath 250m and 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD35_L2\n\n\n\n\n\n\"\nThe MODIS Cloud Mask product is a Level-2 product generated at 1-km and 250-m (at nadir) spatial resolutions. The algorithm employs a series of visible and infrared threshold and consistency tests to specify confidence that an unobstructed view of the Earth's surface has been observed. An indication of shadows affecting the scene is also provided. The 250-m cloud mask flags are based on visible channel data only. Radiometrically-accurate radiances are required, thus holes in the Cloud Mask will appear wherever the input radiances are incomplete or of poor quality assurance. There are two MODIS Cloud Mask data product files: MOD35_L2, containing data collected from the Terra platform; and MYD35_L2, containing data collected from the Aqua platform.\n\nThe MODIS cloud mask algorithm employs a battery of spectral tests, which use methodology applied in the AVHRR Processing scheme Over cLoudy Land and Ocean (APOLLO), International Satellite Cloud Climatology Project (ISCCP), CLoud Advanced Very high resolution Radiometer (CLAVR), and the Support of Environmental Requirements for Cloud Analysis and Archive (SERCAA) algorithms to identify cloudy FOVs. From these, a clear-sky confidence level (high confident clear, probably clear, undecided, cloudy) is assigned to each FOV. For inconclusive results, spatial- and temporal-variability tests are applied. The spectral tests rely on radiance (temperature) thresholds in the infrared and reflectance thresholds in the visible and near-infrared. Thresholds vary with surface type, atmospheric conditions (moisture, aerosol, etc.), and viewing geometry. In addition to the MYD02 calibrated radiances, a 1-km land/water mask, DEM, ecosystem analysis, snow/ice cover map, NCEP analysis of surface temperature and wind speed, and an estimate of precipitable water are required as inputs.\n\nA determination of the presence of global cloudiness is essential to the MODIS mission for two reasons. First, clouds play a critical role in the radiative balance of the Earth and must be accurately described to assess climate and potential climate change. Second, the presence of cloudiness must be accurately determined to properly retrieve many atmospheric and surface parameters. For many of these retrieval algorithms even thin cirrus represents contamination.\n\nCloud mask validation will be conducted using MODIS Airborne Simulator (MAS) data from several field campaigns, all-sky cameras, and comparison with NOAA operational instruments and possibly ASTER.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates. \"\n\nShortname: MYD35_L2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 250 m, 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE03 , File Naming Convention: MYD35_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Ackerman, S., et al., 2017. MODIS Atmosphere L2 Cloud Mask Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD35_L2.061 , Keywords: Cloud Fraction, Climate Change, Atmospheric Correction " }, "onlineresource_set": [] }, { "ob_id": 32423, "uuid": "da87bfa7e3bf4a78a0dc110d6d61aeb3", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD09A1", "numberOfFiles": 105629, "volume": 6727043429785, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32422, "uuid": "05a18921d3a44c89a9158809fd813eb3", "short_code": "ob", "title": "MOD09A1 - MODIS/Terra Surface Reflectance 8-Day L3 Global 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD09A1\n\n\n\n\n\nShortname: MOD09A1 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: 8 day , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE21 " }, "onlineresource_set": [] }, { "ob_id": 32425, "uuid": "3d58c11264e9464db025b18df87e6037", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MOD09GA", "numberOfFiles": 1511216, "volume": 156024160299121, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32424, "uuid": "4bc9628787174d9198f0d4dc153b15c4", "short_code": "ob", "title": "MOD09GA - MODIS/Terra Surface Reflectance Daily L2G Global 1km and 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD09GA\n\n\n\n\n\nShortname: MOD09GA , Platform: Terra , Instrument: MODIS , Processing Level: Level-2 Tiled , Spatial Resolution: 500 m, 1 km , Temporal Resolution: daily , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE13 " }, "onlineresource_set": [] }, { "ob_id": 32427, "uuid": "9bffaecdbdc243d1b5a2088de62928fe", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD09A1", "numberOfFiles": 117935, "volume": 7105777769771, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32426, "uuid": "9dc47e606d50479bbe81872308679ca4", "short_code": "ob", "title": "MYD09A1 - MODIS/Aqua Surface Reflectance 8-Day L3 Global 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD09A1\n\n\n\n\n\nShortname: MYD09A1 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: 8 day , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE21 " }, "onlineresource_set": [] }, { "ob_id": 32429, "uuid": "670ff525d3fd424bae0a953f5f02fc68", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD09GA", "numberOfFiles": 1477621, "volume": 149596701852414, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32428, "uuid": "b8cb8a5d02b143fc8257d030f81bcf76", "short_code": "ob", "title": "MYD09GA - MODIS/Aqua Surface Reflectance Daily L2G Global 1km and 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD09GA\n\n\n\n\n\nShortname: MYD09GA , Platform: Aqua , Instrument: MODIS , Processing Level: Level-2 Tiled , Spatial Resolution: 500 m, 1 km , Temporal Resolution: daily , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE13 " }, "onlineresource_set": [] }, { "ob_id": 32431, "uuid": "08403316936b4258b90cbd71489fd70d", "short_code": "result", "curationCategory": "C", "dataPath": "/neodc/modis/data/MYD03", "numberOfFiles": 2478753, "volume": 76712329151168, "fileFormat": "HDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32430, "uuid": "692a3e1b71f24d8cbfc359eba26a7754", "short_code": "ob", "title": "MYD03 - Geolocation - 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD03\n\n\n\n\n\nThe MYD03 product inculdes the geolocation fields that are calculated for each 1 km MODIS Instantaneous Field of Views (IFOV) for all orbits daily. The locations and ancillary information correspond to the intersection of the centers of each IFOV from 10 detectors in an ideal 1 km band on the Earth's surface. A digital terrain model is used to model the Earth's surface. The main inputs are the spacecraft attitude and orbit, the instrument telemetry and the digital elevation model. The geolocation fields include geodetic Latitude, Longitude, surface height above the geoid, solar zenith and azimuth angles, satellite zenith and azimuth angles, and a land/sea mask for each 1 km sample. Additional information is included in the header to enable the calculation of the approximate location of the center of the detectors for any of the 36 MODIS bands. This product is used as input by a large number of subsequent MODIS products, particularly those produced by the Land team.\n\nShortname: MYD03 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-1A , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE01 , File Naming Convention: MYD03.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time YYYYDDD = Year and Day of Year of acquisition , Citation: MODIS Characterization Support Team (MCST), 2017. MODIS Geolocation Fields Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD03.061 " }, "onlineresource_set": [] }, { "ob_id": 32433, "uuid": "4961d382a2ca4b60afa161ec1d058b71", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2018/CA18_207/CA18_207-2018_123_Rothamsted", "numberOfFiles": 0, "volume": 0, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 32437, "uuid": "28141eebd4f8456c8aa579549921829b", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2018/CA18_207/CA18_207-2018_123_Rothamsted", "numberOfFiles": 0, "volume": 0, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 32441, "uuid": "90371e6cc2214345985df3dfe76121a8", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2018/GB18_56/GB18_56-2018_135a_Methane_Sites", "numberOfFiles": 141, "volume": 25296536893, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32440, "uuid": "212f2ed8d9df42e38e5786683c486c48", "short_code": "ob", "title": "NERC-ARF Flight 2018_135a - for GB18_56: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 15 May 2018 by the Natural Environment Research Council Airborne Research Facility (NERC-ARF) onboard the British Antarctic Survey (BAS) Twin-Otter aircraft for the NERC-ARF GB18_56 Project: Methane emission sources, UK (GB18_56)(flight reference: 2018_135a). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager and hyperspectral data collected using a Specim Aisa OWL imager.\r\n\r\nData were collected over the Harwell, UK area." }, "onlineresource_set": [] }, { "ob_id": 32445, "uuid": "9530c422e15b4cc8aaa2d50c462bb710", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2018/CA18_207/CA18_207-2018_123_Rothamsted", "numberOfFiles": 316, "volume": 104845641381, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32444, "uuid": "0f49c8eb20bb4a0fa20f1f1b2670ba4c", "short_code": "ob", "title": "NERC-ARF Flight 2018_123 - for CA18_207: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 03 May 2018 by the Natural Environment Research Council Airborne Research Facility (NERC-ARF) onboard the British Antarctic Survey (BAS) Twin-Otter aircraft for the NERC-ARF CA18_207 Project: Canadian Wildfire Observations with SLSTR and Aircraft. Ontario, Canada area (CA18_207) (flight reference: 2018_123). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager and digital photography data collected using a Leica RCD105 camera.\r\n\r\nData were collected over the Rothamsted, UK area prior to a detachment to Ontario, Canada." }, "onlineresource_set": [] }, { "ob_id": 32449, "uuid": "bae513a44eac4741878ec8dcd8dec6cc", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/arsf/2018/GB18_56/GB18_56-2018_135b_Methane_Sites", "numberOfFiles": 219, "volume": 42146427847, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32448, "uuid": "932bf0c7937345d7af5be9d018da2a07", "short_code": "ob", "title": "NERC-ARF Flight 2018_135b - for GB18_56: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 15 May 2018 by the Natural Environment Research Council Airborne Research Facility (NERC-ARF) onboard the British Antarctic Survey (BAS) Twin-Otter aircraft for the NERC-ARF GB18_56 Project: Methane emission sources, UK (GB18_56) (flight reference: 2018_135b). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager and hyperspectral data collected using a Specim Aisa OWL imager.\r\n\r\nData were collected over various locations in the UK." }, "onlineresource_set": [] }, { "ob_id": 32452, "uuid": "2d98ecda6af0437c8ceeffb5b6039451", "short_code": "result", "curationCategory": "", "dataPath": "/badc/capeverde/data/mp-oa-icos/", "numberOfFiles": 1200, "volume": 69509840, "fileFormat": "BADC-CSV", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32023, "uuid": "7f7f7056fdc049bb9bb575c18290bd68", "short_code": "ob", "title": "Cape Verde Atmospheric Observatory: High-precision long-term atmospheric measurements of greenhouse gases (CO, CO2, N2O and CH4 ) using Off-Axis Integrated-Cavity Output Spectroscopy (OA-ICOS) (2011 onwards).", "abstract": "Data from observations made at the Cape Verde Atmospheric Observatory (CVAO) which exists to advance understanding of climatically significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data. \r\n\r\nThe observatory is based on Calhau Island of São Vicente, Cape Verde at 16.848N, 24.871W, in the tropical Eastern North Atlantic Ocean, a region which is data poor but plays a key role in atmosphere-ocean interactions of climate-related and biogeochemical parameters including greenhouse gases. It is an open-ocean site that is representative of a region likely to be sensitive to future climate change, and is minimally influenced by local effects and intermittent continental pollution. \r\n\r\nSince November 2011, real-time N2O (Nitrous Oxide) and CO (Carbon Monoxide) concentrations have been simultaneously and continuously measured using an Off-Axis Integrated-Cavity Output Spectroscopy (OA-ICOS) analyser (Los Gatos Inc). In November 2012, a Greenhouse Gas Analyser (GGA) using the same fundamental measuring technique was added and placed in series to measure CO2 (Carbon Dioxide) and CH4 (Methane) concentrations. Both devices are configured to sample at a frequency of 1Hz and both have the precision and accuracy to conform to measurement recommendations as defined by Global Atmosphere Watch (GAW). \r\n\r\nThe dataset contains hourly measurements of CO, CO2, N2O and CH4. Data were collected by collaboration between the University of Exeter and the Max Planck Institute for Biogeochemistry." }, "onlineresource_set": [] }, { "ob_id": 32453, "uuid": "28cc9edb7a014140b1b0aea149c36592", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/qa4ecv/data/spectral_albedo", "numberOfFiles": 2927, "volume": 44329193570, "fileFormat": "These data are provided in netCDF file format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32454, "uuid": "1c9d56f23b134c75963a1d85b059059c", "short_code": "ob", "title": "QA4ECV spectral albedo", "abstract": "The QA4ECV Spectral Albedo product produced by UCL (MSSL and Geography) and Brockmann Consult has achieved an Advanced status for the Product details and Traceability chain; Intermediate status for Assessment against Standards; and Basic status for Quality Flags, uncertainty assessment, and validation." }, "onlineresource_set": [] }, { "ob_id": 32459, "uuid": "74ca1a0fd60c438789e0be518f807cc1", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/openifs_at_home/data/tc_karl/", "numberOfFiles": 1969, "volume": 132390667932, "fileFormat": "Data are WMO GRIB formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32458, "uuid": "ed1bc64e34a14ca28fedd2731735d18a", "short_code": "ob", "title": "OpenIFS@home: ensemble of forecast simulations from Ex-tropical cyclone Karl case study", "abstract": "This dataset contains the 2000-member original validation test case for OpenIFS@home as presented in Sparrow et al 2021, GMD.\r\n\r\nThese are results from an ensemble of forecast simulations of the tropical cyclone Karl from September 2016, studied during the NAWDEX field campaign. This cyclone underwent extratropical transition and intensified in mid-latitudes to give rise to an intense jet-streak near Scotland and heavy rainfall over Norway.\r\n\r\nThe OpenIFS@Home data comprises output from the European Centre for Medium Range Weather Forecasts (ECMWF) OpenIFS model run under the BOINC framework and managed by http://climateprediction.net/ at the University of Oxford. OpenIFS is derived from ECMWF's IFS operational forecast model. The dataset consists of a 2000 member ensemble of the ECMWF OpenIFS cycle 40 release 1 model, run on the OpenIFS@home volunteer framework. The spatial resolution of the dataset is approximately 125km at the equator (corresponding to a spectral resolution of T159) with 60 vertical levels\r\n\r\nThe model output data format is WMO GRIB. Single level parameters and surface fields use GRIB-1 format whilst multi-level upper air fields use GRIB-2 format\r\n\r\nTo work with GRIB files requires the ECMWF ecCodes package. This software provides command line tools for linux/macOS for inspecting the contents of these files, such as listing parameters and meta-information\r\n\r\nThe model output files are on the native IFS grid, the so-called reduced Gaussian grid, rather than a regular latitude-longitude grid commonly used in plotting. The ECMWF metview application can be used to produce plots directly from the model output files without the need to interpolate first. Other applications exist, such as the Climate Data Operators (CDO) that can be used to first convert the GRIB model output files to netCDF for use in other plotting packages. \r\n\r\nThe data is arranged into subdirectories (one per ensemble member), each containing a zip file of the output GRIB data for that simulation. These follow the standard OpenIFS output format and represent 6 hourly snapshots throughout the forecast. The number in the filename denotes the hour of the forecast contained in each respective GRIB file" }, "onlineresource_set": [] }, { "ob_id": 32462, "uuid": "23a8b6a25be340a19ebb0156e73c036d", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2021/population_study_indoor_air_19/data/v1/", "numberOfFiles": 8, "volume": 918471, "fileFormat": "Data are BADC CSV formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32464, "uuid": "5565b28f7da0402ca12e20ae9a9e7c24", "short_code": "ob", "title": "Indoor air population study: Volatile Organic Compounds (VOC) concentrations", "abstract": "This dataset contains Volatile Organic Compounds (VOC) concentrations taken from a large, population-scale study, which was conducted for a total of 19 weeks during the winter and summer of 2019. VOC concentration data were collected for 39 VOC species across 60 houses in Ashford, United Kingdom. Samples were collected in evacuated stainless-steel canisters over 72 hours using restricted flow inlets. A number of houses were randomly selected to also collect an outdoor sample. Each household, per campaign, was associated with at least three canister IDs and some with an additional outdoor sample. \r\n\r\nThis dataset contains information on all VOCs collected, listing in which season each sample was taken, the associated canister ID and the analytical instrument with which each VOC was measured. Household, demographic, and product use information is available, as is a logbook outlining further sample information." }, "onlineresource_set": [] }, { "ob_id": 32465, "uuid": "eb9592d7d46045acb26ccb6e6fc1d51b", "short_code": "result", "curationCategory": "", "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH-marine/mon/HadISDHTable/r1/v1-1-0-2020f/", "numberOfFiles": 9, "volume": 236914881, "fileFormat": "Data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32372, "uuid": "c928ef392244426b9473af92a16b0daf", "short_code": "ob", "title": "HadISDH marine: gridded global monthly ocean surface humidity data version 1.1.0.2020f", "abstract": "This is the HadISDH marine 1.1.0.2020f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH-marine s a near-global gridded monthly mean marine surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships. The observations have been quality controlled and bias-adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2020.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the 1.0.0.2019f version to the end of 2020 and constitutes a minor update to HadISDH due to change in method for calculating gridbox monthly means. All other processing steps for HadISDH remain identical. Users are advised to read the update document in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775." }, "onlineresource_set": [] }, { "ob_id": 32466, "uuid": "86a6ebeca6c04aaeb4f838d64b4afc59", "short_code": "result", "curationCategory": "", "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH/mon/HadISDHTable/r1/v4-3-1-2020f/", "numberOfFiles": 30, "volume": 368861414, "fileFormat": "The data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32371, "uuid": "82b0164a4d06467ab450ff67006729c1", "short_code": "ob", "title": "HadISDH land: gridded global monthly land surface humidity data version 4.3.1.2020f", "abstract": "This is the HadISDH land 4.3.1.2020f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH-land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2020. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the 4.2.0.2019f version to the end of 2020 and constitutes a minor update to HadISDH due to changing some of the code base from IDL and Python 2.7 to Python 3, detecting and fixing a bug in the process, and retrieving the missing April 2015 station data. These have led to small changes in regional and global average values and coverage. All other processing steps for HadISDH remain identical. Users are advised to read the update document in the Docs section for full details.\r\n\r\nAs in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.1.2.202101p, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, "onlineresource_set": [] }, { "ob_id": 32467, "uuid": "052cc8af5816432ea2ec736121ec454a", "short_code": "result", "curationCategory": "", "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH-blend/mon/HadISDHTable/r1/v1-1-1-2020f/", "numberOfFiles": 9, "volume": 162435645, "fileFormat": "The data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32373, "uuid": "8e90b16ddd2a484897ab9737c46d6204", "short_code": "ob", "title": "HadISDH blend: gridded global monthly land and ocean surface humidity data version 1.1.1.2020f", "abstract": "This is the HadISDH blend 1.1.1.2020f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH-blend is a near-global gridded monthly mean surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships and weather stations. The observations have been quality controlled and homogenised / bias adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2020.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the 1.0.0.2019f version to the end of 2020. It combines HadISDH.land.4.3.1.2020f and HadISDH.marine.1.1.0.2020f and therefore their respective update notes. Users are advised to read the update documents in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775.\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, "onlineresource_set": [] }, { "ob_id": 32471, "uuid": "aa879706f895450985af871d4b70cd60", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/oltraj/data/v2.0", "numberOfFiles": 8401, "volume": 1789609906795, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32470, "uuid": "fe3cb5120fa74fa7974820c2e2a238a7", "short_code": "ob", "title": "Global Ocean Lagrangian Trajectories based on AVISO velocities, v2.0, 1998-2018", "abstract": "The National Centre for Earth Observation (NCEO) Long Term Science Single Centre (LTSS) Global Ocean Lagrangian Trajectories (OLTraj) provides 30-day forward and backward Lagrangian trajectories based on AVISO (Satellite Altimetry Data project) surface velocities. Each trajectory represents the path that a water mass would move along starting at a given pixel and a given day. OLTraj can be thus used to implement analyses of oceanic data in a Lagrangian framework. The purpose of OLTraj is to allow non-specialists to conduct Lagrangian analyses of surface ocean data.\r\n\r\nThe dataset has global coverage and spans 1998-2018 with a daily temporal resolution. The trajectories were generated starting from zonal and meridional model velocity fields that were integrated using the LAMTA (6-hour time step - part of ) as described in Nencioli et al., 2018 and SPASSO (Software package for and adaptive satellite-based sampling for ocean graphic cruises containing LAMTA) software user guide. Please see the documentation section below for further information." }, "onlineresource_set": [] }, { "ob_id": 32474, "uuid": "76b12291814c46d0b2acc170d2a5570f", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/igp/data/twinotter/flight292_20180228", "numberOfFiles": 3, "volume": 71216690, "fileFormat": "MASIN data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32473, "uuid": "c58391ab280746b186d2aa6f3adcc0c7", "short_code": "ob", "title": "BAS-MASIN flight 292 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 292 on 28 February 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area." }, "onlineresource_set": [] }, { "ob_id": 32479, "uuid": "7c2b823aa7654545b4b48f424d73ca93", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/igp/data/twinotter/flight293_20180301", "numberOfFiles": 3, "volume": 62041090, "fileFormat": "MASIN data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32478, "uuid": "4c506d968f40478382dcc2f5b9f073fc", "short_code": "ob", "title": "BAS-MASIN flight 293 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 293 on 01 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project.\r\n\r\nThis dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA).\r\nData were collected over the Iceland and Greenland Sea area." }, "onlineresource_set": [] }, { "ob_id": 32483, "uuid": "b6995317c31d4e488caa8e0ac5329da5", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/igp/data/twinotter/flight294_20180301", "numberOfFiles": 3, "volume": 83633130, "fileFormat": "MASIN data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32482, "uuid": "59e9e7ae4f9040d38d9f203a4aae96e2", "short_code": "ob", "title": "BAS-MASIN flight 294 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 294 on 01 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project.\r\nThis dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA).\r\nData were collected over the Iceland and Greenland Sea area." }, "onlineresource_set": [] }, { "ob_id": 32488, "uuid": "759da51bbf9548cda7a96741947058ec", "short_code": "result", "curationCategory": "", "dataPath": "/badc/aphh/data/delhi/delhiflux/ceh-hr-tof-ams/", "numberOfFiles": 3, "volume": 2581629, "fileFormat": "Data are NASA Ames formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32487, "uuid": "5631c55a2caa4cd2bcdf1bf75365bcc8", "short_code": "ob", "title": "APHH: High Resolution Time of Flight Mass Spectrometer measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) site during the DelhiFlux field campaigns", "abstract": "This dataset contains Organic aerosols, NO3-, SO4=, Cl- and NH4+ submicron concentrations in µg m-3 measured with High Resolution Time of Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and Organic aerosol factors (Cooking Organic Aerosol (COA), Nitrogen-rich Hydrocarbon-like Organic Aerosol (NHOA), Solid-Fuel Organic Aerosol (SFOA), Hydrocarbon-like Organic Aerosol (HOA), Semi-Volatility Biomass Burning Organic Aerosol (SVBBOA), Low-Volatility Oxygenated Organic Aerosol (LVOOA), Semi-Volatility Oxygenated Organic Aerosol (SVOOA)) identified using positive matrix factorization. The instrument was located at the Indira Gandhi Delhi Technical University for Women (IGDTUW) from May to Nov 2018. The instrument sampled initially at 7 m above ground level, then was moved to 35 m above ground on the 5th of November 2018.\r\n\r\nThe data were collected as part of the DelhiFlux project under the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme, and the UKCEH’s SUNRISE programme delivering National Capability to NERC." }, "onlineresource_set": [] }, { "ob_id": 32505, "uuid": "b62445b0f3d64df5a703c6def7c39dcd", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2021/nitro-pm/data/", "numberOfFiles": 3, "volume": 13933932, "fileFormat": "Data are NASA-Ames formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32504, "uuid": "723f7b8c12b046de94436f74c6d260cc", "short_code": "ob", "title": "Air quality and meteorological measurements taken from Guangzhou Institute of Geochemistry (GIG), China (31/07/2019 -31/12/2019)", "abstract": "This dataset contains ozone, NO, NO2, NOX, SO2 and PM2.5 air quality and meteorological measurements from two campaigns undertaken in Guangzhou, China in 2019. NO, NO2 and NOX were measured by Chemiluminescence with a Thermo scientific 42i-TL. Ozone were measured via UV with a Thermo scientific 49i. PM2.5 were measured by a continuous particulate monitor (BAM-1020, Met One instruments Inc). SO2 were measured via Pulsed fluorescence with a Thermo scientific 43i-TLE. \r\nThis data were collected as part of the NERC project Investigating the large source of particulate mass from nitrophenols observed in Beijing during winter haze events (NITRO-PM)." }, "onlineresource_set": [] }, { "ob_id": 32511, "uuid": "1e891ecc2060453f9bb2e6781ff86aa2", "short_code": "result", "curationCategory": "", "dataPath": "/badc/cru/data/cru_cy/cru_cy_3.24", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are ascii formated.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 32523, "uuid": "550253fa03204300ab849f971622bcee", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/sg-wex/data/um-data/sgwex_June2015_nSG_u-af015", "numberOfFiles": 1274, "volume": 1532126175650, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32522, "uuid": "a945f294d03143d8b5197e65f8005915", "short_code": "ob", "title": "SG-WEx: Unified Model output for June-July 2015 over South Georgia, without island orography (run: u-af015)", "abstract": "This dataset contains modelling output from the u-af015 run of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the Met Office Unified Model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period June-July 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. 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This run was for the time period July 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. These runs also coincided with radiosonde campaigns launched from the island.\r\n\r\nTechnical details regarding the configuration of these runs is described Vosper (2015, doi:10.1002/qj.2566). Further information and science results can be found in Jackson et al. (2018, doi:10.1175/BAMS-D-16-0151.1) and Hindley (2021, doi:10.5194/acp-21-7695-2021). 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This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area." }, "onlineresource_set": [] }, { "ob_id": 32572, "uuid": "88a4cf596877408dbd7be54b908925ab", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/igp/data/twinotter/flight305_20180318", "numberOfFiles": 3, "volume": 98974187, "fileFormat": "MASIN data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32571, "uuid": "378139c15c784477bfdd7bd8c204c0f6", "short_code": "ob", "title": "BAS-MASIN flight 305 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 305 on 18 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area." }, "onlineresource_set": [] }, { "ob_id": 32575, "uuid": "b1f32567f1ac4b308d8f5b89de69652d", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/sg-wex/data/um-data/sgwex_Jan2015_nSG_u-ag706", "numberOfFiles": 1168, "volume": 1444719255896, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32469, "uuid": "9314b7b6417049beb18570632b435e5b", "short_code": "ob", "title": "SG-WEx: Unified Model output for January 2015 over South Georgia, without island orography (run: u-ag706)", "abstract": "This dataset contains modelling output from the u-ag706 run of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the Met Office Unified Model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period January 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. These runs also coincided with radiosonde campaigns launched from the island.\r\n\r\nTechnical details regarding the configuration of these runs is described Vosper (2015, doi:10.1002/qj.2566). Further information and science results can be found in Jackson et al. (2018, doi:10.1175/BAMS-D-16-0151.1) and Hindley (2021, doi:10.5194/acp-21-7695-2021). See online resources linked to this record for further details." }, "onlineresource_set": [] }, { "ob_id": 32577, "uuid": "d69bb7b84f7e4f2188957be2966078a3", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2021/nitrates_metoffice-um/data/", "numberOfFiles": 192, "volume": 114355323714, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 32576, "uuid": "0613b74ecc574fa7b6ac8a22838c5f81", "short_code": "ob", "title": "Exploring the sensitivity of atmospheric nitrate concentrations to nitric acid uptake rate using the Met Office’s Unified Model: nitrate and nitric acid simulation data", "abstract": "This dataset contains nitrate and nitric acid simulation data to explore the sensitivity of atmospheric nitrate concentrations to nitric acid uptake rate using the Met Office’s Unified Model.\r\n\r\nThe files are seperated into directories by simulation name - 1. A control simulation with no nitrate aerosol (CNTL); 2. A simulation with NH4·NO3 reaching equilibrium instantaneously (INSTANT); 3. A simulation with the HNO3 uptake rate set to 0.193 (FAST); and 4. A simulation with the HNO3 uptake rate 0.001 (SLOW). All simulations are performed with the Met Office Unified Model (UM or MetUM) in an N96L85 resolution." }, "onlineresource_set": [] } ] }