Observation List
Get a list of Observation objects.
### Available end points:
- `/observations/` - Will list all Results in the database
- `/observations.json` - Will return all Results in json format. This can
also be achieved by using the accept header. `application/json`
- `/observations/<object_id>/` - Returns Results object with that id
### Available Methods:
- `GET`
- `HEAD`
### Available filters:
- `title`
- `uuid`
- `keywords`
- `status`
- `result_field`
- `discoveryKeywords`
- `updateFrequency`
- `nonGeographicFlag`
- `publicationState`
- `permissions`
### How to use filters:
These filters can be used like django query filters using __ for related model relationships.
- `/observations/?uuid=d594d53df2612bbd89c2e0e770b5c1a0`
- `/observations/?status=completed`
- `/observations/?results_field__dataPath__startswith=/neodc/esacci`
- `/observations/?discoveryKeywords__name=ESACCI`
- `/observations/?nonGeographicFlag=True`
Filters can be stacked to build an 'AND' relationship. E.g.
- `/observations/?publicationState__in=published,citable&nonGeographicFlag=True`
- `/observations/?publicationState__in=published,citable&discoveryKeyword__name=NDGO0003`
GET /api/v2/observations/?format=api&offset=7100
{ "count": 10256, "next": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=7200", "previous": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=7000", "results": [ { "ob_id": 32395, "uuid": "be30127db24d45c3826367af7d0fcc44", "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 ", "keywords": "Water Vapor, Precipitable Water ", "publicationState": "published", "dataPublishedTime": "2021-04-15T14:05:37.727802", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32396/?format=api", "dataPath": "/neodc/modis/data/MOD06_L2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 173767316505494, "numberOfFiles": 2741816, "fileFormat": "HDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8892/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62241/?format=api", 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"https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64624/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64625/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64626/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64627/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64628/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64629/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64630/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64631/?format=api" ], "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10835/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/10895/?format=api" ], "observationcollection_set": 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"https://api.catalogue.ceda.ac.uk/api/v2/observations/2557/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32397, "uuid": "35bb28eafbaa461db578e1218808c038", "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 ", "keywords": "Climate Change, Land Surface Temperature, Emissivity, Fires ", "publicationState": "published", "dataPublishedTime": "2021-04-15T14:05:49.312383", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32398/?format=api", "dataPath": "/neodc/modis/data/MOD11A1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2773452117017, "numberOfFiles": 1362985, "fileFormat": "HDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8893/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64531/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64532/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64537/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64538/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64539/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64540/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64541/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64542/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64543/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64544/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64545/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64546/?format=api" ], "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10836/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/10895/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/10892/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30129/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144245/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144246/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144247/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144248/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144249/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144251/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144252/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144253/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/25855/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2557/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32399, "uuid": "15f057994f074b08a60daa1f188014e6", "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. 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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 ", "keywords": "Climate Change, Canopy Characteristics, Biomass, Vegetation Index, Plant Phenology, Length of Growing Season ", "publicationState": "published", "dataPublishedTime": "2021-04-15T14:06:07.536427", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32402/?format=api", "dataPath": "/neodc/modis/data/MOD13A2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 527218355189, "numberOfFiles": 57650, "fileFormat": "HDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8895/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64515/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64516/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64517/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64518/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64519/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64520/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64521/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64522/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64523/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64524/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64525/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64526/?format=api" ], "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10838/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/10895/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/10892/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30129/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144263/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144264/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144265/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144266/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144267/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144269/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144270/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144271/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/25855/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2557/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32403, "uuid": "e3ee4b286e97482fb3c979ca9268f228", "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 ", "keywords": "Climate Change, Land Surface Temperature, Fires ", "publicationState": "published", "dataPublishedTime": "2021-04-15T14:06:13.349801", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32404/?format=api", "dataPath": "/neodc/modis/data/MOD14A1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2866, "numberOfFiles": 7, "fileFormat": "HDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8896/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64732/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64733/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64734/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64735/?format=api" ], "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10839/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/10895/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/10892/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30129/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144272/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144273/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144274/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144275/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144276/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144278/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144279/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144280/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/25855/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2557/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32405, "uuid": "2a777ecbac9847639617c053072c4af2", "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. 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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. 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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. 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"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). 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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. 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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. 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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. 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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. 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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. 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"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). 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Ontario, Canada area (CA18_207) (flight reference: 2018_123). 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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.", "keywords": "GB18_56, GB18/56, aircraft, hyperspectral, remote sensing, NERC-ARF, ARSF", "publicationState": "published", "dataPublishedTime": "2021-04-23T10:59:22", "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32449/?format=api", "dataPath": "/neodc/arsf/2018/GB18_56/GB18_56-2018_135b_Methane_Sites", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 42146427847, "numberOfFiles": 219, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8914/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2750/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were collected and processed by the NERC-ARF facility and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32421/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144448/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144449/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144450/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144451/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144452/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144453/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144454/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144455/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/32450/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2522/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32454, "uuid": "1c9d56f23b134c75963a1d85b059059c", "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.", "keywords": "QA4ECV, Albedo", "publicationState": "working", "dataPublishedTime": null, "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32453/?format=api", "dataPath": "/neodc/qa4ecv/data/spectral_albedo", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 44329193570, "numberOfFiles": 2927, "fileFormat": "These data are provided in netCDF file format." }, "timePeriod": null, "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50415/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50417/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50512/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57665/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57666/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57667/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57668/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57669/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57670/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57671/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57672/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57673/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57674/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57675/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57676/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57677/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57678/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57679/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57680/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57681/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57682/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57683/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57684/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57685/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57686/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57687/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57688/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57689/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57690/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57691/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57692/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57693/?format=api" ], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144459/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144460/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144461/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144462/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144463/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144464/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/147573/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2528/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": "any" } ], "discoveryKeywords": [] }, { "ob_id": 32458, "uuid": "ed1bc64e34a14ca28fedd2731735d18a", "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", "keywords": "OpenIFS@home, cyclone, Karl", "publicationState": "citable", "dataPublishedTime": "2021-05-24T09:30:32", "doiPublishedTime": "2021-05-24T11:26:49.891857", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32459/?format=api", "dataPath": "/badc/openifs_at_home/data/tc_karl/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 132390667932, "numberOfFiles": 1969, "fileFormat": "Data are WMO GRIB formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8917/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were generated using ECMWF OpenIFS deployed under the CPDN distributed computing framework and then passed on to the Centre for Environmental Data (CEDA) for archiving.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10891/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32468/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144495/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144496/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144497/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144498/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144499/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144500/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144502/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144503/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144504/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144505/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144506/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144507/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144508/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144509/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144510/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32461/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32464, "uuid": "5565b28f7da0402ca12e20ae9a9e7c24", "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.", "keywords": "NERC, indoor, VOC, population", "publicationState": "published", "dataPublishedTime": "2022-01-18T16:30:07", "doiPublishedTime": null, "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32462/?format=api", "dataPath": "/badc/deposited2021/population_study_indoor_air_19/data/v1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 918471, "numberOfFiles": 8, "fileFormat": "Data are BADC CSV formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8918/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2751/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46622/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46623/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46624/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46625/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46626/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46627/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46628/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46629/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46630/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46631/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46632/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46633/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46634/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46635/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46636/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46637/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46638/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46639/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46640/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46641/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46642/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46643/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46644/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46645/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46646/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46647/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46648/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46649/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46650/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46651/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46652/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46653/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46654/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46655/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46656/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46657/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46658/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46659/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46660/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46661/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46662/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46663/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46664/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46665/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46666/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46667/?format=api" ], "dataLineage": "Data were collected by the University of York in collaboration with Givaudan UK, who provided a cohort of study participants and aided in survey design. Data were then sent for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144512/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144513/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144514/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144515/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144516/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144517/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144519/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144518/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144520/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144521/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144522/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144523/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144524/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144525/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/32463/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32469, "uuid": "9314b7b6417049beb18570632b435e5b", "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.", "keywords": "Unified Model, NWP, South Atlantic", "publicationState": "citable", "dataPublishedTime": "2021-05-11T08:42:08", "doiPublishedTime": "2021-05-12T16:00:00", "updateFrequency": "notPlanned", "status": "final", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32575/?format=api", "dataPath": "/badc/sg-wex/data/um-data/sgwex_Jan2015_nSG_u-ag706", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1444719255896, "numberOfFiles": 1168, "fileFormat": "Data are netCDF formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8941/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2752/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/1314/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6913/?format=api", 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"https://api.catalogue.ceda.ac.uk/api/v2/observations/2522/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32470, "uuid": "fe3cb5120fa74fa7974820c2e2a238a7", "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.", "keywords": "AVISO, Global, Ocean Lagrangian Trajectories, LAMTA, zonal, meridional model, OLTraj_SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047", "publicationState": "citable", "dataPublishedTime": "2021-05-06T09:35:10", "doiPublishedTime": "2021-05-10T15:47:54", "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32471/?format=api", "dataPath": "/neodc/oltraj/data/v2.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1789609906795, "numberOfFiles": 8401, "fileFormat": "NetCDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8690/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2687/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/4385/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/18405/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/18408/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/30129/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/30130/?format=api" ], "dataLineage": "Data were produced by the NCEO Plymouth Marine Laboratory project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10866/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/5002/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30127/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144555/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144556/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144554/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144549/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144550/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144551/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144552/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144553/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144557/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32472/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2528/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32473, "uuid": "c58391ab280746b186d2aa6f3adcc0c7", "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. 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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).", "keywords": "NO, NO2, NOX, SO2, PM2.5, air quality, meteorology, China", "publicationState": "published", "dataPublishedTime": "2021-06-09T15:47:46", "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32505/?format=api", "dataPath": "/badc/deposited2021/nitro-pm/data/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 13933932, "numberOfFiles": 3, "fileFormat": "Data are NASA-Ames formatted" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8929/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2762/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46836/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46837/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46838/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46839/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46840/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46841/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46842/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46843/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46844/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46845/?format=api" ], "dataLineage": "Data were collected, quality controlled and prepared for archiving by the instrument scientists before upload to the Centre for Environmental Data Analysis (CEDA) for long term archiving.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32506/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144721/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144710/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144711/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144712/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144713/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144714/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144715/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144720/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144722/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144723/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144724/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/32507/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32521, "uuid": "4edcd686e1e74e2f8e4cf108eb054cc8", "title": "SG-WEx: Unified Model output for July 2015 over South Georgia, without island orography (run: u-ab978)", "abstract": "This dataset contains modelling output from the u-ab978 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 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 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 results in an overlap between the Met Office data for this site and the 5 minute AWS data within this dataset. \r\n\r\nBoth BADC-CSV and NetCDF formatted versions of the data have been provided to aid greatest usability possible of these data.", "keywords": "surface meteorology, automatic weather station, 5 minunte", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "updateFrequency": "monthly", "status": "pending", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32583/?format=api", "dataPath": "/badc/ness-aws/data/ness-aws", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 0, "numberOfFiles": 0, "fileFormat": "Data are netCDF and BADC-CSV formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8949/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2774/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32584/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145047/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145048/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145049/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145050/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145051/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145052/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145053/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145054/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145076/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145077/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/32581/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32592, "uuid": "653fdd814dba4103a301221955781e35", "title": "NCEO Kenya forest aboveground biomass map 2015 v21.0", "abstract": "The NCEO Kenya forest aboveground biomass map shows aboveground woody biomass (AGB) in Kenyan forests. Forest areas include vegetated wetlands and wooded grassland for the year 2015. The map was generated by combining field inventory plots (KFS) with Advanced Land Observing Satellite (ALOS-2), Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and multispectral optical data (NASA Landsat 8), by means of a Random Forests algorithm within a k-Fold calibration/validation framework. \r\n\r\nThe characterization of carbon stocks and dynamics at the national level is critical for countries engaging in climate change mitigation and adaptation strategies. However, several tropical countries, including Kenya, lack the essential information typically provided by a complete national forest inventory. These data were produced by the National Centre for Earth Observation (NCEO), University of Leicester, in collaboration with the Kenya Forest Service (KFS) with funding from the NCEO ODA Programme. \r\n\r\nKnown Issues: Residual scan line corrector (SLC) effects due to the use of the SLEEK land cover product as a retrieval mask (derived from Landsat imagery) are visible in some areas", "keywords": "NCEO, AGB, Biomass, Kenya, forest, vegetated wetlands, wooded grassland", "publicationState": "published", "dataPublishedTime": "2021-05-14T13:03:44", "doiPublishedTime": null, "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32591/?format=api", "dataPath": "/neodc/nceo_biomass_maps/data/kenya/v21.0/2015/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 575877009, "numberOfFiles": 11, "fileFormat": "GeoTiff \r\nPixel type: unsigned integer \r\nPixel Depth: 16 Bit NoData Value: 65535" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8950/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2775/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/5002/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30127/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145125/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145126/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145127/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145132/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145133/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145123/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145124/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145122/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145134/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145135/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/32596/?format=api", "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32597, "uuid": "c7aa24fb8d5c458daefdf0f4410ba830", "title": "NCEO Manaus plots AGB map 2014 v1.0", "abstract": "The NCEO Manaus plots Above Ground Biomass (AGB) map 2014 v1.0 shows above ground woody biomass in plot sites around the city of Manaus in the state of Amazonas, Brazil. The data supports characterization of carbon stocks and dynamics at the national level, which is critical for countries engaging in climate change mitigation and adaptation strategies. \r\n\r\nThe data consists of AGB for 22 plot sites in the dbf data file. The file is accompanied by shape and metadata files (sbx, shp, shx and prj files) containing plot location information enabling display in GIS applications such as QGIS.", "keywords": "NCEO, AGB, Biomass, Manaus, forest, vegetated wetlands, wooded grassland", "publicationState": "published", "dataPublishedTime": "2025-09-23T14:20:50", "doiPublishedTime": null, "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/44806/?format=api", "dataPath": "/neodc/nceo_biomass_maps/data/manaus/v1.0/2014", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 13925, "numberOfFiles": 7, "fileFormat": "dbf, sbx, shp, shx, prj" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/12634/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/4883/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA). At present only data files and minimal metadata have been provided. We have no information to date on how the data were collected.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/5002/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30127/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145137/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145138/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145139/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145141/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145142/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145143/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/214917/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/214918/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32598, "uuid": "32274aca008b4f7799e8cea69ad3508e", "title": "Yucatan Peninsula and Central Mexico above ground biomass maps 2010 v5.0", "abstract": "This dataset contains the biomass maps for epoch 2: 2010 (GlobBiomass project reference year) for Yucatan peninsula and Central Mexico with a 30m spatial resolution. \r\n\r\nThe dataset contains 4 raster files corresponding to 2 areas in Mexico; the Yucatan Peninsula AGB-MEX_Yucatan2010_v5.tif, AGB_MEX_Yucatan2010_QA_v5.tif, Central Mexico, AGBMEX_Central2010_v5.tif and AGB_MEX_Central2010_QA_v5.tif. \r\n\r\nThe maps show aboveground woody biomass in Mexican forests and were generated by combining the probabilistic outputs. from a Maximum Entropy (MaxEnt) algorithm. Field inventory plots (CONAFOR, INFyS) were used in combination with SAR (JAXA ALOS PALSAR) and optical data (NASA Landsat 7), as well as a digital elevation model (NASA SRTM).,An empirical linear regression model with AGB as dependant variable (Ln-transformed) and SAR backscatter intensity (DN values) of the HV polarization as the independent variable was fitted to estimate AGB over mangrove and other wetland vegetation\r\n\r\nFurther information can be found in the documnetation section and in a read me file archived with the data", "keywords": "NCEO, AGB, Mexico, Yucatan", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32599/?format=api", "dataPath": "/neodc/nceo_biomass_maps/data/mexico/v5.0/2010/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 540158114, "numberOfFiles": 6, "fileFormat": "GeoTIFF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8951/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2776/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/5002/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30127/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145147/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145148/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145149/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145150/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145151/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145152/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145153/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145154/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145155/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/32596/?format=api", "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32600, "uuid": "7b3bddd5af4945c2ac508a6d25537f0a", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Grounding line location for key glaciers, Antarctica, 1994-2020, v2.0", "abstract": "This dataset contains grounding line locations (GLL) for key glaciers in Antarctica, produced as part of the ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci) project. The data have been derived from satellite observations from the ERS-1/2, TerraSAR-X and Copernicus Sentinel-1 satellites, acquired between 1994 and 2020.", "keywords": "Ground line location, Antarctica, ESA, CCI", "publicationState": "published", "dataPublishedTime": "2021-06-17T13:38:20", "doiPublishedTime": null, "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32708/?format=api", "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/grounding_line_locations/key_glaciers/v2.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7999482, "numberOfFiles": 6, "fileFormat": "Shapefiles" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8952/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2777/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/24700/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/24699/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145157/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145158/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145159/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145160/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145162/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145163/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145167/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146440/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145168/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145164/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145165/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145166/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/32678/?format=api", "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2534/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_icesheets_antarctic_terms_and_conditions.pdf", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ] }, { "ob_id": 32601, "uuid": "00fe090efc58446e8980992a617f632f", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly velocity from 2017 to 2020, derived from Sentinel-1, v1", "abstract": "This dataset contains monthly gridded ice velocity maps of the Antarctic Ice Sheet derived from Sentin\r\nel-1 data acquired between 2017-01-01 and 2020-08-31. It was generated by ENVEO, as part of the ESA Antarctic Ice Sheet Climate Change Initiative project (Antarctic_Ice_Sheet_cci).\r\n\r\nThe surface velocity is derived by applying feature tracking techniques using Sentinel-1 synthetic aperture radar (SAR) data acquired in the Interferometric Wide (IW) swath mode. Ice velocity is provided at 200m grid spacing in Polar Stereographic projection (EPSG: 3031). The horizontal velocity components are provided in true meters per day, towards easting and northing direction of the grid. The vertical displacement is derived from a digital elevation model. Provided is a NetCDF file with the velocity components: vx, vy, vz, along with maps showing the magnitude of the horizontal components, the valid pixel count and uncertainty. The product combines all ice velocity maps, based on 6- and 12-day repeats, acquired within a single month in a monthly averaged product.", "keywords": "Antarctic, Ice Sheet Velocity, ESA, CCI", "publicationState": "citable", "dataPublishedTime": "2021-06-17T14:01:35", "doiPublishedTime": "2021-06-28T16:02:08.246398", "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32743/?format=api", "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/ice_velocity/antarctic_ice_sheet/sentinel_1/monthly/v1.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 101295328588, "numberOfFiles": 45, "fileFormat": "Data are in NetCDF format" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8953/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2778/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/12066/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/13204/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/13205/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/13206/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/13207/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50347/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50348/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50349/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50547/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50548/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62645/?format=api" ], "dataLineage": "Data were processed by ENVEO as part of the ESA Antarctic Ice sheet CCI project and are archived on the ENVEO Cryoportal (http://cryoportal.enveo.at) They have been supplied to CEDA in the context of the ESA CCI Open Data Portal Project", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10898/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/24700/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/24699/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145169/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145170/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145171/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145172/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145173/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145174/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145175/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146442/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145176/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145177/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145178/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145179/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/32701/?format=api", "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2534/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_icesheets_antarctic_terms_and_conditions.pdf", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ] }, { "ob_id": 32602, "uuid": "e1dfd0ee655944b8a82ce0479c518747", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly Gravimetric Mass Balance basin product, v3.0, 2002-2020", "abstract": "This dataset contains the Gravimetric Mass Balance (GMB) basin product for the Antarctic Ice Sheet (AIS), generated by TU Dresden as part of the ESA Antarctic Ice Sheet Climate Change Initiatve (Antarctic_Ice_Sheet_cci). \r\n\r\nThe Gravimetric Mass Balance (GMB) product for the Antarctic Ice Sheet (AIS) is based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through July 2020. The GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 187 monthly solutions. The mass change estimation is based on the tailored sensitivity kernel approach developed at TU Dresden. (Groh & Horwath, 2021)\r\n\r\nThe GMB basin product provides time series of integrated mass changes for 26 drainage basins and the aggregations of the Antarctic Peninsula, East Antarctica, West Antarctica and the entire AIS. Based on the GMB basin product, ice mass balance estimates, i.e. linear trend in the change in ice mass, were derived for all drainage basins and aggregations. A gridded GMB product is also available as a separate dataset.\r\n\r\nGroh, A. & Horwath, M. (2021). Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels. Remote Sens., 13(9), 1736. doi:10.3390/rs13091736", "keywords": "ESA CCI, Antarctica, Ice Sheet Mass Balance, GRACE, GRACE-FO", "publicationState": "citable", "dataPublishedTime": "2021-06-17T14:15:03", "doiPublishedTime": "2021-06-28T16:02:54.673524", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32742/?format=api", "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/gravimetric_mass_balance/basin/v3.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 147610, "numberOfFiles": 2, "fileFormat": "Data are in NetCDF format" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8954/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2779/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67712/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67713/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67714/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67715/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67716/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67717/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67718/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67719/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67720/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67721/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/67722/?format=api" ], "dataLineage": "The data were generated by TU Dresden within the ESA Antarctic Ice Sheet CCI project and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving and distribution via the CCI Open Data Portal.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10900/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/24700/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/24699/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146441/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145181/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145182/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145183/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145184/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145185/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145186/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145180/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145188/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145187/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/32698/?format=api", "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2534/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_icesheets_antarctic_terms_and_conditions.pdf", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ] }, { "ob_id": 32605, "uuid": "5b22789f362c43f3b3d1c65bc30c30ee", "title": "Deanhill C-band rain radar dual polar products", "abstract": "Dual-polar products from the Met Office's Deanhill C-band rain radar, Whiteparish, Wiltshire, England. Data include augmented ldr (linear depolarization ratio) and zdr (differential reflectivity) scan data (both long and short pulse). The radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals.", "keywords": "Met Office, NIMROD, rain radar", "publicationState": "published", "dataPublishedTime": "2021-06-02T08:35:56", "doiPublishedTime": null, "updateFrequency": "continual", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32606/?format=api", "dataPath": "/badc/ukmo-nimrod/data/single-site/deanhill/raw-dual-polar/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 710833347529, "numberOfFiles": 652, "fileFormat": "Data are in NIMROD data format. See linked documentation for further details." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8955/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/117/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data are acquired from rain radar network in the UK and Europe by the Met Office's NIMROD system. Single site data are then sent to the BADC by the Met Office's DART operational dissemination system. Raw polar data from single sites are sent through from the RADARNET team at the Met Office. On arrival at the Centre for Environmental Data Analysis (CEDA) the data are ingested after a one day quarantine, having been compressed and then compiled into daily tar balls for each data type.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/5736/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/32603/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/5709/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145225/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145226/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145227/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145228/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145229/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145230/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145219/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145222/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/5741/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2532/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "ukmo_wx", "label": "restricted: ukmo_wx group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": "academic" }, { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2533/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "ukmo_wx_gov", "label": "restricted: ukmo_wx_gov group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement_gov.pdf", "licenceClassifications": "policy" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32607, "uuid": "9252ff9ddeb249a2bd8433e9ae9dfe13", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from TANSAT, generated with the OCFP algorithm, for global land areas, version 1.0", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (CO2), derived from the TANSAT satellite, using the University of Leicester Full-Physics Retrieval Algorithm (UoL-FP, also known as OCFP). This dataset is also referred to as CO2_TAN_OCFP. This version of the dataset provides data globally over land. For further information on the dataset, please see the linked documentation.\r\n\r\nInitially this dataset contains two months of data (June and August 2017), delivered as part of the GHG_cci Climate Research Data Package 6. Additional time periods will be added in the future.\r\n\r\n\r\nThis data has been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, with support from the UK's National Centre for Earth Observation (NCEO).", "keywords": "ESA, CCI, satellite, TANSAT, atmosphere, carbon dioxide, CO2", "publicationState": "published", "dataPublishedTime": "2021-08-06T10:42:35", "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/33016/?format=api", "dataPath": "/neodc/esacci/ghg/data/cci_plus/CO2_TAN_OCFP/v1.0_global_land/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 518692308, "numberOfFiles": 60, "fileFormat": "Data are in NetCDF format" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8956/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50542/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50543/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/55535/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63576/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66452/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66456/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66719/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68622/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68624/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68625/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68626/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68630/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68635/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68636/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68637/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68638/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68639/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68640/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68641/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/68646/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69372/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69373/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69374/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69375/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69629/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69802/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69803/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69804/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/70614/?format=api" ], "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project. This data has been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, with support from the UK's National Centre for Earth Observation (NCEO).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/13295/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/12808/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/30128/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145315/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145319/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145317/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145316/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145313/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145314/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145320/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145318/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145321/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/147415/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/31873/?format=api", "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2564/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ] }, { "ob_id": 32609, "uuid": "b0de069568a141b0b074ca0f7cee004b", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 09", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2), using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm which has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data (v09) was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg)\r\nand got co-funding from the Univ. Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810).\r\n\r\nWhen citing this data, please also cite the following peer-reviewed publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017", "keywords": "ESA, CCI, satellite, CO2", "publicationState": "citable", "dataPublishedTime": "2021-09-02T15:55:52", "doiPublishedTime": "2021-09-08T10:43:16", "updateFrequency": "notPlanned", "status": "superseded", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32610/?format=api", "dataPath": "/neodc/esacci/ghg/data/cci_plus/CO2_OC2_FOCA/v9.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 8044862560, "numberOfFiles": 1790, "fileFormat": "Data are netCDF formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8957/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/1050/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/1635/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/1636/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11820/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11831/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11841/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11842/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11846/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11848/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/23212/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/28592/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/28593/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/28594/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/28595/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/28596/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/28597/?format=api" ], "dataLineage": "This version of the data was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg)\r\nand got co-funding from the Univ. Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810).\r\nData were supplied to CEDA for archiving as part of the ESA CCI Open Data Portal.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10944/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/13295/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/12808/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145327/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145328/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145324/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145323/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145329/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145326/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145322/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145325/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145330/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145331/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145332/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145333/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/33058/?format=api", "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2564/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32612, "uuid": "67a3f8c8dc914ef99f7f08eb0d997e23", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost active layer thickness for the Northern Hemisphere, v3.0", "abstract": "This dataset contains permafrost active layer thickness data produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. It forms part of the second version of their Climate Research Data Package (CRDP v2). It is derived from a thermal model driven and constrained by satellite data. Grid products of CDRP v2 are released in annual files, covering the start to the end of the Julian year. The maximum depth of seasonal thaw is provided, which corresponds to the active layer thickness.\r\n\r\nCase A: This covers the Northern Hemisphere (north of 30°) for the period 2003-2019 based on MODIS Land Surface temperature merged with downscaled ERA5 reanalysis near-surface air temperature data.\r\nCase B: This covers the Northern Hemisphere (north of 30°) for the period 1997-2002 based on downscaled ERA5 reanalysis near-surface air temperature data which are bias-corrected with the Case A product for the overlap period 2003-2019 using a pixel-specific statistics for each day of the year.", "keywords": "Permafrost, CCI, Active layer thickness", "publicationState": "citable", "dataPublishedTime": "2021-06-25T16:58:28", "doiPublishedTime": "2021-06-28T12:35:46", "updateFrequency": "notPlanned", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32613/?format=api", "dataPath": 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"https://api.catalogue.ceda.ac.uk/api/v2/rpis/145372/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145373/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145374/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32737/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2596/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_permafrost_terms_and_conditions.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ] }, { "ob_id": 32614, "uuid": "6e2091cb0c8b4106921b63cd5357c97c", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost extent for the Northern Hemisphere, v3.0", "abstract": "This dataset contains permafrost extent data produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. It forms part of the second version of their Climate Research Data Package (CRDP v2). It is derived from a thermal model driven and constrained by satellite data. Grid products of CDRP v2 are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures (at 2 m depth) which forms the basis for the retrieval of yearly fraction of permafrost-underlain and permafrost-free area within a pixel. A classification according to the IPA (International Permafrost Association) zonation delivers the well-known permafrost zones, distinguishing isolated (0-10%) sporadic (10-50%), discontinuous (50-90%) and continuous permafrost (90-100%).\r\n\r\nCase A: This covers the Northern Hemisphere (north of 30°) for the period 2003-2019 based on MODIS Land Surface temperature merged with downscaled ERA5 reanalysis near-surface air temperature data. \r\nCase B: This covers the Northern Hemisphere (north of 30°) for the period 1997-2002 based on downscaled ERA5 reanalysis near-surface air temperature data which are bias-corrected with the Case A product for the overlap period 2003-2019 using a pixel-specific statistics for each day of the year.", "keywords": "Permafrost, CCI, Permafrost Extent", "publicationState": "citable", "dataPublishedTime": "2021-06-25T16:57:59", "doiPublishedTime": "2021-06-28T12:35:13", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": 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"https://api.catalogue.ceda.ac.uk/api/v2/rpis/145397/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145398/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145399/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145400/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32737/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2596/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_permafrost_terms_and_conditions.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ] }, { "ob_id": 32616, "uuid": "fdb8960260a64c5faf652f8f47c4df81", "title": "APHH: Non-methane volatile organic compound emission inventories from burning studies performed as part of the APHH-INDIA project (DelhiFlux).", "abstract": "This contains gridded non-methane volatile organic compound (NMVOC) emission inventories for India derived as part of burning studies performed during the APHH-INDIA campaign. For data files with more than 1 million rows, NASA AMES metadata headers have been provided as a separate document, which has the identical name of the data it applies to but also includes _metadata.\r\n\r\nFor years 1993, 1994, 1999, 2002, 2005, 2006, 2007, 2010, 2011 and 2016 inventories have been produced in terms of total NMVOC emission from each source sector (kg/km2). There are also two upper limit scenarios of emissions from cow dung cake combustion based on data from PPAC and PPAC supplemented with additional cow dung cake consumption for states now covered by this survey. The speciation factors of NMVOCs released from particular sources are also provided so that these years can be speciated by source simply by multiplying the total emission from each source by the ratio of species released from the source. This allows future users to produce speciated emission inventories for years other than 2011 if they need.\r\n\r\nGridded inventories are also provided for emissions of 21 polycyclic aromatic hydrocarbons for the year 2011 from fuelwood, cow dung cake, charcoal, liquefied petroleum gas and municipal solid waste. These are provided as total PAH emissions from a source with speciation factors also provided to allow speciation should it be required by multiplying the total NMVOC emission from a source by the speciation factors from that source. \r\n\r\nGridded inventories are provided for crop residue burning at 1km2 and 10km2. These were calculated with total agricultural area identified in a state from either NASA MODIS (1 km2) or Ramankutty et al. (2008) (10 km2). A second inventory was produced at 10km2 as it was felt that the NASA data offered little variation within respective states. These have been split into total emissions from each of the 5 emission factors applied, RiceEFyearlyVOCKG (for rice), WheatEFyearlyVOCKG (for wheat, coarse cereal and maize), JowarEFyearlyVOCKG (for Jowar and Bajra), MeanEFyearlyVOCKG (for 9 oilseeds, groundnut, rapeseed, mustard, sunflower, cotton, jute and mesta) and SugarcaneEFyearlyVOCKG (for sugarcane). \r\n\r\nThe inventories were produced using emission factors developed as part of the APHH-INDIA project as well as from a different publication focussed on the burning of crops. The inventories have been developed in the following manner. The emission factors used in this study come from a variety of recently published sources. All emission factors applied in this study included measurement by PTR-ToF-MS, a technique well suited to species released in significant quantities from solid fuel combustion such as small oxygenated species, phenolics and furanics. These species are often missed by GC measurement alone. Preference has been given to emission factors from studies which: (1) have many measurements (n), (2) use samples collected from India or (3) use samples collected from similar countries. Fully speciated emission factors are available from the references given. For residential fuel combustion, the emission factors measured by Stewart et al. (2021a) were used and were developed from 76 combustion experiments of fuel wood, cow dung cake, LPG and MSW samples collected from around Delhi. This study was extremely detailed and measured online, gas-phase, speciated NMVOC emission factors for up to 192 chemical species using dual-channel gas chromatography with flame ionisation detection (DC-GC-FID, n = 51), two-dimensional gas chromatography (GC×GC-FID, n = 74), proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS, n = 75) and solid-phase extraction two-dimensional gas chromatography with time-of-flight mass spectrometry (SPE-GC×GC-ToF-MS, n = 28). Comparison of these emission factors to those obtained in similar studies is provided in Stewart et al. (2021a). The emission factors used as part of this study are larger than those measured by Stockwell et al. (2016), Fleming et al. (2018) and several other studies which were based on gas chromatography techniques alone. The emission factors here measure many more NMVOC species, use techniques which target a range of species which more traditional GC analyses do not detect and make online measurements which minimise loss of intermediate-volatility and semi-volatile organic species, which may be lost through the collection of whole air samples, but have been shown to represent a large proportion of total emissions from biomass burning (Stockwell et al., 2015).\r\n\r\nEmission factors for combustion of crop residues on fields were taken from measurements by Stockwell et al. (2015) made using PTR-ToF-MS of 115 NMVOCs (Stockwell et al., 2015) for wheat straw (n = 6), sugarcane (n=2), rice straw (n=7) and millet (n=2). This study also included the mean crop residue emission factor for 19 food crops, for use when no current emission factor had been comprehensively measured using PTR-ToF-MS. The emission factor applied (38.8 g kg-1) was evaluated against that for crop residues used for domestic combustion in Delhi (37.9 g kg-1). Whilst the values measured by Stockwell et al. (2015) and Stewart et al. (2021a) were comparable, the value from Stockwell et al. (2015) was used as the crop types were more reflective of the crop residues burnt on fields after harvest, compared to those burnt to meet residential energy requirements. The mean emission factor for crop residue combustion on fields was used for specific crop types with smaller levels of cultivation.\r\nEmissions from coal burning were estimated using a mean emission factor from the combustion of bituminous coal from China (n = 14), a neighbouring Asian country, made using PTR-ToF-MS. Whilst the chemical composition of the coal may be more important than the development status of the country, there was overall a low level of reported residential coal use and this estimate was included for completeness. A total of 89 NMVOCs were identified, which represented 90-96% of the total mass spectra (Cai et al., 2019). \r\n\r\nIndian specific PAH emission factors were recently measured in gas- and particle-phases using PTR-ToF-MS and GC×GC-ToF-MS (Stewart et al., 2021). This dataset provided PAH emission factors collected from combustion of fuel wood (n = 16), cow dung cake (n = 3), crop residue from domestic combustion (n = 3), MSW (n = 3), LPG (n = 1) and charcoal (n = 1) samples. \r\n\r\nHigh resolution, gridded population data for India (WorldPop, 2017) was used at a resolution of 1 km2. Officially, urban populations in India are defined as having a population density > 400 people km-2, 75% of men employed in non-agricultural industries and a population of town > 5000 people. Rural populations in India cannot be identified simply by having a population density of < 400 people km-2, as some states such as Uttar Pradesh have an average population density of around 800 people km-2. Rural grid squares were therefore identified by calculating the population density threshold in each state in which the sum of the 1km2 grid squares below this threshold correctly reproduced the rural populations in these states from the 2001 and 2011 censuses (Government of India, 2014). A small uncertainty existed over the exact population of India and we used population statics indicated by the 2011 census. NMVOC and PAH emissions from domestic solid fuel combustion were plotted against this high-resolution population data in the R statistical programming language at 1 km2 for 2001 and 2011, with the population datasets scaled to the percentage changes in Indian population indicated by the World Bank for additional years of interest. \r\n\r\nPreference was given to large fuel usage surveys which included tens to hundreds of thousands of respondents. The Household Consumption of Goods and Services in India survey by the National Sample Survey Office (NSSO, 2007a, 2012a, 2014) gave state-wise kg capita-1 fuel wood, LPG, charcoal and coal burning statistics for rural and urban environments and was used for the years 2004-2005, 2009-2010 and 2011-2012. NMVOC emissions for these years were calculated by multiplying the NMVOC emission factor for the fuel, by the yearly fuel consumption per capita by the population of the grid cell. \r\n\r\n\r\nData were collected from additional large surveys previously conducted. These surveys collected data in terms of the number of households using specific fuels per 1000 households in different Indian states in rural and urban environments. The Fifth Quinquennial Survey on Consumer Expenditure provided data for 1993-1994 (NSSO, 1997), the Energy Sources of Indian Households for Cooking and Lighting provided data for years 2004-2005, 2009-2010 and 2010-2011 (NSSO, 2007b, 2012b, 2015) and the Household Consumer Expenditure and Employment-Unemployment Situation in India for 2002 and 2006-2007 (NSSO, 2003, 2008). The National Family Health Survey presented India-wide fuel use as a percentage of the population. To reflect spatial variation in fuel use, the raw data from these surveys were accessed (from the DHS Programme, U.S. Agency for International Development), extracted through the SPSS statistics software package and processed in the R programming language. This increased fuel usage data availability as the number of households per 1000 households using specific fuels in Indian states and covered the years 1992-1993, 1998-1999, 2005-2006 and 2015-2016 (International Institute for Population Sciences, 1995, 2000, 2007, 2017). These were extensive datasets with 1992-1993, 1998-1999 and 2005-2006 surveying just under 100,000 households and 2015-2016 around 600,000 households.\r\n\r\nTo allow the incorporation of data from years which were based on the number of households using a particular fuel per 1000 households (1993, 1994, 1999, 2002, 2006, 2007 and 2016), a scaling factor was developed. The scaling factor was based on the ratio of fuel use in the state from years where per capita data was available. It was possible to link the Household Consumption of Goods and Services in India and the Energy Sources of Indian Households for Cooking and Lighting surveys for the years 2005, 2010 and 2011. This was done using years where the number of households per 1000 households and kg capita-1 fuel usage statistics were available, as it was possible to calculate the amount of fuel a primary user would use. The fuel use of a primary user here was defined as the amount of fuel a person would burn who was recorded to use a specific fuel type. For example, if the per capita consumption in the Household Consumption of Goods and Services survey in India for fuel wood was 10 kg per capita per 30 days, and the Energy Sources of Indian Households for Cooking and Lighting survey showed 250 households per 1000 households used fuel wood, then the fuel use was estimated to be 40 kg per primary user per 30 days. This was achieved by multiplying the per capita usage for a particular fuel type by the inverse of the ratio of fuel usage in that state in rural or urban environments. The amount of fuel a primary user would use was then used to estimate the amount of fuel consumed per capita in years where only usage per 1000 household statistics were available.\r\n\r\nCow dung cake consumption was only reported as number of households per 1000 in these surveys and the amount of cow dung cake burnt per primary user was determined based on the energy density compared to fuel wood. This was done using calorimetry data which showed that cow dung cake was 1.3-1.9 times less efficient than fuel wood (EPA, 2000; Gadi et al., 2012). For this reason, the amount of fuel per primary user for fuel wood in a state has been multiplied by 1.6 to give the equivalent amount of cow dung cake a user would need to burn for their cooking needs. Upper and lower estimates for cow dung cake consumption were based on the range 1.3-1.9. This was then converted to fuel use per capita in kg per user per 30 days by rearranging E2. This has been evaluated to validate this approach, which estimated Indian cow dung cake consumption to be in the range 25.7-79.7 Tg yr-1 from 1993-2016. This was generally towards the lower end of consumption values previously reported of 35-128 Tg yr-1 (Habib et al., 2004). For this reason, emission inventory estimates were also compared to those produced using cow dung cake consumption based on the TERI Energy Data Directory and Yearbook (TEDDY) 2012/2013 data and a study from the Petroleum Planning & Analysis Cell (PPAC) from 2016 with population indicated at the 2011 level (TEDDY, 2012; PPAC, 2016).\r\n\r\n\r\nThe amount of MSW burnt was estimated using an established approach (IPCC, 2006; Wiedinmyer et al., 2014) with revised inputs for India based on per capita MSW generation from over 300 Indian cities (Annepu et al., 2012), state wise MSW collection figures (CPCB, 2013) as well as estimates of the amount of urban (NEERI, 2010) and rural MSW burnt (World Bank, 2012). This estimate does not include incineration for electrical power generation. \r\n\r\nWiedinmyer et al. (2014) assessed worldwide emissions from MSW burning based on IPCC guidelines (IPCC, 2006). The approach used here was similar, with modifications to the input data which made them more specific to India. The approach split the amount of MSW burnt into the MSW burnt by rural and urban populations in the country. For rural populations this was given by per capita rural MSW generation multiplied by the population of rural grid cell multiplied by the fraction of MSW burnt residentially. Per capita rural MSW generation was set at the lower limit indicated by the World Bank for South Asia of 0.12 kg capita-1 day-1 and evaluated in the range 0.08 kg capita-1 day-1 (Parmar and Pamnani, 2018) to 0.12 kg capita-1 day-1 (World Bank, 2012). The fraction of MSW burnt rurally was set to 0.6 which was the IPCC estimate (IPCC, 2006) and was further supported by a recent study which showed that only around 40% of rural MSW was collected in South Asia (Kaza et al., 2018).\r\n\r\nThe fraction of MSW burnt for an urban population was estimated by the sum of two calculations. The first was for street MSW burning which was calculated by per capita urban MSW generation multiplied by the population of urban grid cell multiplied by the fraction of MSW which was not collected multiplied by the fraction burnt.\r\n\r\nThe weighted per capita urban MSW generation was calculated by averaging per capita MSW generation statistics from 366 Indian cities by state (Annepu et al., 2012). The fraction of MSW which was uncollected was calculated from the Central Pollution Control Board (CPCB), as the difference in the amount of MSW generated and collected (CPCB, 2013). Urban per capita MSW generation was scaled to its estimated change for different years of interest.\r\n\r\nThe second calculation was for the MSW burnt on landfill sites, which was calculated by the MSW per capita produced in urban environments, multiplied by the urban population, multiplied by the fraction collected in an urban environment multiplied by the fraction burnt at the landfill site. The fraction of MSW collected came from CPCB statistics, but was reduced by 17-50% due to the informal recycling sector, based on very limited data from studies focussed on MSW recovery by the informal sector which showed 17% recovery in Delhi (Talyan et al., 2008), 20% recovery at a landfill site in Pune (Annepu et al., 2012), 4% in Pondicherry (Rajamanikam et al., 2014) and up to 40-50% in Mohali (Nandy et al., 2015). This was due to the large contribution of the informal recycling sector to recycling in India, where waste was collected by waste merchants, garbage collectors and waste pickers from highways, waste depots and landfill sites. This was an important consideration in India as studies have shown recovery of between 8.5-80 kg of material per picker per day and large cities such as Delhi having 80,000-100,000 pickers (Nandy et al., 2015). The fraction of waste burnt in a dump (Bfrac,dump) was given by NEERI who estimated that 10% of landfill MSW in Mumbai was burnt (NEERI, 2010). This was reinforced by a further study which examined the amount of waste burnt based on satellite studies of a landfill site in India which showed that approximately 10% of the waste that entered the site each day ended up being burnt (Sharma et al., 2019). Bfrac,dump was notably lower here (0.1) than in Wiedinmyer et al. (2014) (0.6) which was based on the 2006 IPCC Guidelines for National GHG Inventories. The estimate used in this study represented a conservative estimate of NMVOC emissions from landfill fires. Due to lack of reliable data in establishing Bfrac,dump, and the associated uncertainty, the sensitivity of urban landfill burning emissions over the range 0.1-0.6 was evaluated as part of the uncertainty range given in this study. This provided the upper limit to the uncertainty range of the potential amount of landfill waste burnt. This depicts scenarios before the new MSW management rules in 2016. \r\n\r\nNMVOC emissions from crop residue burning on fields in India were estimated to evaluate the relative importance of different burning sources using the most up-to-date input data currently available. A calculation was carried out for 2011, as NMVOC emissions from crop-residue burning on fields showed little year-on-year variation from 1995-2009 (Jain et al., 2014). The residue generated from the cultivation of four main categories of crops was estimated. The amount of crop types produced in each state (Ministry of Agriculture, 2012) was collated for cereals (rice, wheat, coarse cereals, maize, jowar, bajra), oilseeds (groundnut, rapeseed, mustard, sunflower and 9 oilseeds), fibres (cotton, jute and mesta) and sugarcane. The amount burnt was calculated using India specific estimates of the residue to crop ratio, dry matter fraction and fraction burnt (Jain et al., 2014). Emissions were estimated using factors from recent studies of crop residues routinely burnt on fields using PTR-ToF-MS (Stockwell et al., 2015). When the exact residue was measured (e.g., rice straw, wheat straw, sugarcane and millet) the correct emission factor was used. For cases where the exact residue was not measured, the mean reported crop residue emission factor was used. The spatial distribution of croplands was then either indicated using agricultural land identified by the high-resolution 500 m NASA MODIS land use product reduced to 1 km2 resolution or through croplands identified at 10 km2 through evaluation of the distribution of agricultural lands (Ramankutty et al., 2008). The total amount of crop residue burnt in a state was calculated using the approach given in Jain et al. (2014) but with the up-to-date inputs discussed. \r\n\r\nThe inventories were produced by Gareth Stewart at the University of York. Full details of the methodology are provided in the publication associated with these inventories. \r\n\r\nThe inventories provided here cover most of the land mass of India, but may vary slightly compared to those presented in the publication. This is associated with the North of India, particularly around the Pakistan and Chinese borders. This is due to how the boundaries of India were defined in the base data used for this study (WorldPop and GADM) and changes to states in the North of India after the period of interest (i.e. formation of Ladakh in 2019).\r\nAn inventory for coal has not been included due to low total emissions. \r\n\r\nAcronyms\r\n\r\nPAH = Polycyclic aromatic hydrocarbon\r\n\r\nNMVOCs = non-methane volatile organic compounds\r\n\r\nMSW = Municipal solid waste\r\n\r\nCrop = agricultural crop residue \r\n\r\nWood = Fuel wood\r\n\r\nDung = Cow dung cakes\r\n\r\nCharcoal = Charcoal fuel\r\n\r\nCoal = Coal fuel\r\nAPHH-INDIA = Atmospheric Pollution and Human Health in an Indian Megacity project\r\n\r\n\r\nRiceEFyearlyVOCKG = Total NMVOC emission in 2011 from agricultural on field burning of agricultural rice residues\r\n\r\nWheatEFyearlyVOCKG = Total NMVOC emission in 2011 from agricultural on field burning of agricultural wheat, coarse cereal and maize residues\r\n\r\nJowarEFyearlyVOCKG = Total NMVOC emission in 2011 from agricultural on field burning of agricultural jowar and bajra residues\r\n\r\nMeanEFyearlyVOCKG = Total NMVOC emission in 2011 from agricultural on field burning of agricultural 9 oilseeds, groundnut, rapeseed, mustard, sunflower, cotton, jute and mesta residues\r\n\r\nSugarcaneEFyearlyVOCKG (for sugarcane) = Total NMVOC emission in 2011 from agricultural on field burning of agricultural sugarcane residues\r\n\r\nBfracdump = fraction of waste burnt in the dump", "keywords": "APHH, VOC, Delhi, inventories", "publicationState": "citable", "dataPublishedTime": "2021-05-26T10:22:43", "doiPublishedTime": "2021-05-26T10:35:53.775129", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32617/?format=api", "dataPath": "/badc/aphh/data/delhi/delhiflux/york-gcxgc-fid_voc-inventory/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 72624481321, "numberOfFiles": 46, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8960/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2780/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/41999/?format=api" ], "dataLineage": "The data were delivered to the Centre for Environmental Data Analysis (CEDA) for archiving by the data provider.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10892/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/30221/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/32625/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145401/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145402/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145403/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145404/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145405/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145406/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145407/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145408/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145409/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/168360/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/32618/?format=api", "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2522/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32619, "uuid": "b25d4a6174de4ac78000d034f500a268", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost Ground Temperature for the Northern Hemisphere, v3.0", "abstract": "This dataset contains permafrost ground temperature data produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. It forms part of the second version of their Climate Research Data Package (CRDP v2). It is derived from a thermal model driven and constrained by satellite data. Grid products of CDRP v2 are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures and is provided for specific depths (surface, 1m, 2m, 5m , 10m).\r\n\r\nCase A: This covers the Northern Hemisphere (north of 30°) for the period 2003-2019 based on MODIS Land Surface temperature merged with downscaled ERA5 reanalysis near-surface air temperature data.\r\nCase B: This covers the Northern Hemisphere (north of 30°) for the period 1997-2002 based on downscaled ERA5 reanalysis near-surface air temperature data which are bias-corrected with the Case A product for the overlap period 2003-2019 using a pixel-specific statistics for each day of the year.", "keywords": "Permafrost, CCI, Ground Temperature", "publicationState": "citable", "dataPublishedTime": "2021-06-25T16:59:05", "doiPublishedTime": "2021-06-28T12:36:20.964753", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32620/?format=api", "dataPath": "/neodc/esacci/permafrost/data/ground_temperature/L4/area4/pp/v03.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 35291367976, "numberOfFiles": 24, "fileFormat": "Data are netCDF formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8999/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2567/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/27732/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50416/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50547/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50548/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/70621/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/70622/?format=api" ], "dataLineage": "Data have been produced by the ESA CCI Permafrost project as part of ESA's Climate Change Initiative 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"https://api.catalogue.ceda.ac.uk/api/v2/rpis/145437/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145438/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145439/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145440/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32737/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2596/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_permafrost_terms_and_conditions.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ] }, { "ob_id": 32623, "uuid": "f6c384ae730744d2ba929e0fad77160a", "title": "Spectroscopic data for transitions in water (1H 16O2) extending into the near-ultraviolet", "abstract": "This dataset contains spectroscopic data for transitions in water (1H 16O2 (H2O with oxygen 16 and hydrogen 1)) extending into the near-ultraviolet. These data were calculated using a mixture of first principle quantum mechanics and input from the experiment. \r\n\r\nThe data is provided in HITRAN format as described in the associated readme file. The data were collected as part of the NERC grant Short wavelength absorption by water vapour (NE/T000767/1).", "keywords": "NERC, NE/T000767/1, Spectroscopic, UV", "publicationState": "published", "dataPublishedTime": "2021-06-15T13:27:58", "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32621/?format=api", "dataPath": "/badc/deposited2021/WAT-UV296_water_line/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 121029527, "numberOfFiles": 3, "fileFormat": "Data are Hirtan formatted." }, "timePeriod": null, "geographicExtent": null, "nonGeographicFlag": true, "phenomena": [], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32622/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145445/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145446/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145447/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145448/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145449/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145450/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145451/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145452/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145453/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/168961/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145454/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32673/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32669, "uuid": "7beeed0bc7fa41feb10be22ee9d10f00", "title": "Adverse Weather Scenarios for Future Electricity Systems", "abstract": "This dataset contains gridded meteorological data associated with challenging periods of weather for highly-renewable UK and European electricity systems of the future collected during the Adverse Weather Scenarios for Future Electricity Systems project. This project is a collaboration between the Met Office, the National Infrastructure Commission and the Climate Change Committee. More details about the project can be found in the associated documentation.\r\n\r\nTwo categories of challenging weather conditions; long duration adverse events and short duration wind ramping events, are provided.\r\n\r\nLong duration events\r\n\r\nThe long duration event component of the dataset provides daily time series at 60 x 60 km spatial resolution, covering a European domain, for surface temperature, 100 m wind speed and net surface solar radiation data, representative of a selection of adverse weather scenarios. Each adverse weather scenario is contained within a time slice of data. For summer-time events, one calendar year (January - December) of data is provided, with the summer-time event occurring in the summer of that year. For winter-time events, two calendar years of data are provided, with the winter-time event occurring in the winter (October-March) intersecting the two calendar years. In all cases, the start date, duration and severity of the adverse weather event, contained within the time slice of data, are given in the NetCDF global ttributes.\r\n\r\nThree types of long-duration adverse weather scenarios are represented: winter-time wind-drought-peak-demand events, summer-time wind-drought-peak-demand events, and summer-time surplus generation events. These are provided at various extreme levels (1 in 2, 5, 10, 20 ,50 and 100-year events); and for a range of current and nominal future climate change warming levels (1.2 [current day, early 2020s], 1.5, 2, 3, and 4 degrees Celsius above pre-industrial level), representative of events impacting either just the UK, or Europe as a whole.\r\n\r\nThe data provided are derived from the Met Office decadal prediction system hindcast (https://www.metoffice.gov.uk/research/approach/modelling-systems/unified-model/climate-models/depresys) according to the climate change impacts identified from UKCP18 (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index).\r\n\r\nShort duration events\r\nThe short duration event component of the dataset provides hourly time series at 4 x 4 km spatial resolution, covering a UK and surrounding offshore area domain, for 100 m wind speed, representative of a selection of wind generation ramping events. Each adverse weather scenario is contained within a time slice of data with up to one week before and one week after the day on which the event occurs (up to 15 days in total) provided. For the majority of events provided, the full 15 days are available, however for a small number of events which occur less than one week from the beginning or end of the underlying data used to derive this dataset, this is not possibly to supply, and these events are listed below. The start date and time along with the direction and magnitude of the ramp (change in wind capacity factor) contained\r\nwithin the time slice of data, are given in the NetCDF global attributes.\r\n\r\nThe short duration wind generation ramping events are representative of events impacting five separate regions of Great Britain and surrounding offshore areas, as defined in the accompanying documentation. These regions are Scotland, the East England, West England and Wales offshore North and offshore South. The events are defined by changes in wind capacity factors occurring over different length time windows (1-hour, 3-hour, 6-hour, 12-hour and 24-hour windows). These are provided at various extreme levels (1 in 2, 5, 10, 20 ,50 and 100-year events) for the 1.2 degrees Celsius above pre-industrial level (I.e. representative of early 2020s climate) and through the analysis outlined in the accompanying documentation are though to also be representative of the 2, 3, and 4 degrees Celsius above pre-industrial level nominal future climate change warming levels.\r\n\r\nThe data provided are derived from the UKCP18 local projections (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index).\r\n\r\nThe methods developed for characterising and representing these adverse weather scenarios, and the approach used to compile the final dataset are presented in the accompanying documentation.\r\n\r\nUse of this data is subject to the terms of the Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/) The following acknowledgment must be given when using the data: © Crown Copyright 2021, Met Office, funded by the National Infrastructure Commission.", "keywords": "Adverse weather scenarios, future electricity systems, adverse weather scenarios for future electricity systems, UK, Europe, weather risk, climate risk, energy system, extreme weather scenarios, electricity system resilience, climate change", "publicationState": "published", "dataPublishedTime": "2021-06-03T14:48:03", "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32670/?format=api", "dataPath": "/badc/deposited2021/adverse_met_scenarios_electricity/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 689690747173, "numberOfFiles": 2624, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8976/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2794/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/2007/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/2008/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6811/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11573/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21675/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21676/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21677/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21678/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46793/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46794/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46795/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46796/?format=api" ], "dataLineage": "This dataset has been developed by the Met Office as part of the 'Adverse Weather Scenarios for Future Electricity Systems' project, commissioned by the National Infrastructure Commission, and co-lead by the Climate Change Committee.\r\n\r\nThe data provided are derived from the Met Office decadal prediction system hindcast and UKCP18, according to the climate change impacts identified from UKCP18. Further information about the development of this dataset are presented in the accompanying reports. The data has been sent by the data providers to be archived at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32671/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145687/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145688/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145689/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145690/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145691/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145692/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145697/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145698/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145699/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145700/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145701/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145702/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32672/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32688, "uuid": "feb1e0b5426d4f5c80f791909a3a2d37", "title": "High resolution Standardized Precipitation Evapotranspiration Index (SPEI) dataset for Central Asia", "abstract": "This dataset contains high-resolution (5 km) Standardized Precipitation Evaporation Index (SPEI-HR) drought data for Central Asia. There are forty-eight different SPEI time scales and the available period is from 1981 - 2018, the data was produced using Climate Hazards group InfraRed Precipitation with Station’s (CHIRPS) precipitation dataset and Global Land Evaporation Amsterdam Model’s (GLEAM) potential evaporation dataset. The SPEI-HR dataset, over time and space, correlates fairly well with SPEI values estimated from coarse-resolution Climate Research Unit (CRU) dataset. Furthermore, the SPEI-HR dataset, for 6-month timescale, displayed a good correlation of 0.66 with GLEAM root zone soil moisture and a positive correlation of 0.26 with normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modelling System (GIMMS).", "keywords": "SPEI, Central Asia, drought", "publicationState": "citable", "dataPublishedTime": "2021-06-03T08:29:27", "doiPublishedTime": "2022-02-28T13:13:25", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32689/?format=api", "dataPath": "/badc/deposited2021/spei-central-asia/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 54700431523, "numberOfFiles": 51, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8980/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2797/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51981/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60423/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60424/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60425/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60426/?format=api" ], "dataLineage": "Data was prepared for a Masters Thesis at the Chair of Hydrology and River Basin Management and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/11032/?format=api" ], "projects": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145750/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145751/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145752/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145753/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145754/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145755/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145760/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145761/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145762/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/168962/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145763/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145764/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32691/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 32692, "uuid": "36dae49c76f845a18062fa96599be719", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly Gravimetric Mass Balance gridded product, v3.0, 2002 - 2020", "abstract": "This dataset contains the Gravimetric Mass Balance (GMB) gridded product for the Antarctic Ice Sheet (AIS), generated by TU Dresden as part of the ESA Antarctic Ice Sheet Climate Change Initiatve (Antarctic_Ice_Sheet_cci). \r\n\r\nThe Gravimetric Mass Balance (GMB) product for the Antarctic Ice Sheet (AIS) is based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through July 2020. The GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 187 monthly solutions. The mass change estimation is based on the tailored sensitivity kernel approach developed at TU Dresden. (Groh & Horwath, 2021)\r\n\r\nThe GMB gridded product comprises time series of ice mass changes for cells of polar-stereographic grid with a sampling of 50x50 km² covering the entire AIS. A GMB basin product is also available as a separate dataset.\r\n\r\nGroh, A. & Horwath, M. (2021). Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels. 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It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.2, and covers the period from November 2017 - July 2020. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. 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Level-2 data consists of geolocated geophysical products derived from Level-1. Sentinel 1A was launched on 3rd April 2014 and provides continuous all-weather, day and night imaging radar data. The IW mode is the main operational mode. These level 2 OCN products provide Ocean Wind field (OWI) and Surface Radial Velocity (RVL).\r\n\r\nThe OWI component is a ground range gridded estimate of the surface wind speed and direction at 10 m above the surface, derived from IW mode. The OWI component contains a set of wind vectors for each processed Level-1 input product. The norm is the wind speed in m/s and the argument is wind direction in degrees (meteorological convention = clockwise direction from where the wind blows with respect to the North). The spatial resolution of the SAR wind speed is 1 km for IW mode.\r\n\r\nThe RVL surface radial velocity component is a ground range gridded difference between the measured Level-2 Doppler grid and the Level-1 calculated geometrical Doppler. The RVL component provides continuity of the ASAR Doppler grid. 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These runs were part of the NERC funded BBUBL project (Biotelemetry/Bio-aerial-platforms for the Urban Boundary Layer - also known as City Flocks, NERC grant award NE/N003195/1). The domain of the model runs was over the set over Birmingham conurbation for all of 2015. This geo-temporal domain encompasses measurements of the urban boundary layer obtained from instrumentation attached to birds flown around the area. See related dataset.\r\n\r\nThe WRF model set up followed that used by Heaviside et al. (2015) - see linked documentation for details - and was run on the ARCHER UK National Supercomputing Service. Meteorology data from the European Centre for Medium-range Weather Forecasts (ECMWF) ERA-interim reanalysis data for initial and lateral boundary conditions.\r\n\r\nThe WRF v3.6.1 model set up implemented in this study included four nested domains. The domains had grid resolutions of 36 km x 36 km, 12 km x 12 km, 3 km x 3 km and 1 km x 1 km. 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This coupled with the inclusion of consistent calibration using on-board black bodies allows for the collection of extremely radiometrically accurate data. \r\n\r\nThe data are Level1 Ungridded Brightness Temperatures (UBT). The data are in SADIST-2 format and CEDA is the primary archive for this data. 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Sentinel 1A was launched on 3rd April 2014 and provides continuous all-weather, day and night imaging radar data. The SM mode is used only on special request for extraordinary events such as emergency management. The SM mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. \r\n\r\nStripmap SLCs contain one image per polarisation band from one of six overlapping beams. Each beam covers 80.1 km, covering a combined range of 375 km. Pixel spacing is determined, in azimuth by the pulse repetition frequency (PRF), and in range by the radar range sampling frequency, providing natural pixel spacing.\r\n\r\nThese data are available via CEDA to any registered user.", "keywords": "Sentinel, radar, Synthetic Aperture Radar, Stripmap, Single Look Complex", "publicationState": "published", "dataPublishedTime": "2021-06-25T15:50:48", "doiPublishedTime": null, "updateFrequency": "", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32776/?format=api", "dataPath": "/neodc/sentinel1a/data/SM/L1_SLC/IPF_v2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6563765716239, "numberOfFiles": 12131, "fileFormat": "Image data files are in a binary format. Quicklook images are in png format. 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Sentinel 1A was launched on 3rd April 2014 and provides continuous all-weather, day and night imaging radar data. The IW mode is the main operational mode. The IW mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. \r\n\r\nThe IW SLC product contains one image per sub-swath, per polarisation channel, for a total of three or six images. Each sub-swath image consists of a series of bursts, where each burst was processed as a separate SLC image. The individually focused complex burst images are included, in azimuth-time order, into a single sub-swath image, with black-fill demarcation in between\r\n\r\nUnlike SM and WV SLC products, which are sampled at the natural pixel spacing, the images for all bursts in all sub-swaths of an IW SLC product are re-sampled to a common pixel spacing grid in range and azimuth. The resampling to a common grid eliminates the need for further interpolation in case, in later processing stages, the bursts are merged to create a contiguous ground range, detected image.\r\n\r\nThese data are available via CEDA to any registered CEDA user.", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Interferometric Wide, IW, Single Look Complex, SLC", "publicationState": "published", "dataPublishedTime": "2021-06-25T15:00:46", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32781/?format=api", "dataPath": "/neodc/sentinel1a/data/IW/L1_SLC/IPF_v3", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5766391293430236, "numberOfFiles": 5714231, "fileFormat": "Image data files are in a binary format. Quicklook images are in png format. 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Sentinel 3A was launched on the 16th of February 2016. These data contain geo-located bursts of echoes with all calibrations applied. Level 1A (L1A) is an intermediate output of the Synthetic Aperture Radar (SAR) processor. L1A complex waveforms should be fully calibrated (including both instrumental gains and calibration corrections) and aligned in range within each burst. The time tag is given at the surface (that is when the middle of the burst reaches the surface). L1A is the starting point for the SAR processing which provides high-resolution products. Data are provided by ESA and are made available via CEDA to any registered user.", "keywords": "Sentinel, Synthetic Aperture Radar Altimeter, SRAL", "publicationState": "published", "dataPublishedTime": "2022-12-19T15:36:13", "doiPublishedTime": null, "updateFrequency": "continual", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32786/?format=api", "dataPath": "/neodc/sentinel3a/data/SRAL/L1_SRA_A__/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 11349097935027, "numberOfFiles": 13802, "fileFormat": "Data are provided by ESA in zipped SAFE format." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9014/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data collected and prepared by European Space Agency (ESA). 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Sentinel 3A was launched on the 16th of February 2016. These data are fully SAR-processed and calibrated High-Resolution (HR) complex echoes arranged in stacks after slant range correction and prior to echo multi-look (multi-look processing reduces noise by averaging of adjacent pixels, and thereby reduces the standard deviation of the noise level).\r\n\r\nThe L1B-S HR product contains information from Doppler beams data. Hence, it has only been defined for the Synthetic Aperture Radar (SAR) processing chain. The Doppler beams associated with a given surface location (also called stack data) are formed through the selection of all the beams that illuminate a given surface location, and that contribute to each L1B HR waveform. Beams are the result of applying Doppler processing to the waveform bursts, which allows division of the conventional altimeter footprint into a certain number of stripes, thus creating a Delay Doppler Map (DDM). With this, contributions coming from different stripes can be identified and collected separately. When all the contributions from different bursts are collected, a stack is formed. The stack waveforms are provided in In-phase (I) and Quadrature-phase (I/Q) samples (complex waveforms) in the frequency domain. Apart from the Doppler processing, the beams of a stack have also been fully calibrated and range aligned. The L1B-S also includes characterisation parameters about the stack itself. The time tag is given at each surface location (defined throughout the L1 processing chain).\r\n\r\nData are provided by ESA and are made available via CEDA to any registered user.", "keywords": "Sentinel, Synthetic Aperture Radar Altimeter, SRAL, SAR, Sentinel3", "publicationState": "published", "dataPublishedTime": "2021-07-01T16:06:40", "doiPublishedTime": null, "updateFrequency": "continual", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32788/?format=api", "dataPath": "/neodc/sentinel3a/data/SRAL/L1_SRA_BS_/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5415290909817, "numberOfFiles": 9688, "fileFormat": "Data are provided by ESA in zipped SAFE format." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9015/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data collected and prepared by European Space Agency (ESA). 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Level-2 data consists of geolocated geophysical products derived from Level-1. \r\n\r\nFrom WV modes, the OCN product will only contain Ocean Swell Spectra (OSW) and Surface Radial Velocity (RVL). \r\n\r\nThe OSW component is a two-dimensional ocean surface swell spectrum and includes an estimate of wind speed and direction per swell spectrum. The OSW component provides continuity measurement of SAR swell spectra at C-band. OSW is estimated from Sentinel-1 SLC images by inversion of the corresponding image cross-spectra.\r\n\r\nThe OSW is generated from Stripmap and Wave modes only and is not available from the TOPSAR IW and EW modes. For Stripmap mode, there are multiple spectra derived from the Level-1 SLC image. 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Sentinel 1B was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. The SM mode is used only on special request for extraordinary events such as emergency management. The SM mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. \r\n\r\nStripmap SLCs contain one image per polarisation band from one of six overlapping beams. Each beam covers 80.1 km, covering a combined range of 375 km. Pixel spacing is determined, in azimuth by the pulse repetition frequency (PRF), and in range by the radar range sampling frequency, providing natural pixel spacing.\r\n\r\nThese data are available via CEDA to any registered user.", "keywords": "Sentinel, radar, Synthetic Aperture Radar, Stripmap, Single Look Complex", "publicationState": "published", "dataPublishedTime": "2021-07-02T09:51:28", "doiPublishedTime": null, "updateFrequency": "", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32802/?format=api", "dataPath": "/neodc/sentinel1b/data/SM/L1_SLC/IPF_v2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1427172708154, "numberOfFiles": 2336, "fileFormat": "Image data files are in a binary format. Quicklook images are in png format. 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This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2021 by CRU at the University of East Anglia and extends the CRU CY4.04 data to include 2020. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.05 is derived directly from the CRU time series (TS) 4.05 dataset. CRU CY version 4.05 spans the period 1901-2020 for 292 countries.\r\n\r\nTo understand the CRU CY4.05 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.05. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.05 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users.", "keywords": "CRU, CRU CY, CY, climate", "publicationState": "published", "dataPublishedTime": "2021-07-02T11:54:39", "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32823/?format=api", "dataPath": "/badc/cru/data/cru_cy/cru_cy_4.05/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 50992332, "numberOfFiles": 2924, "fileFormat": "The CRU CY data are provided as text files with the extension \".per\", most text editors will open these files. See the linked file formats guide for more information." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9006/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/513/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "The Climatic Research Unit (CRU) CY data are derived directly from the CRU TS data, and version numbering is matched between the two datasets. The CRU CY data are produced by the CRU unit at the University of East Anglia and passed to the Centre for Environmental Data Analysis (CEDA) for long term archival and distribution. 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All versions prior to 4.00 used triangulation routines in IDL. Please see the release notes for full details of this version update. \r\n\r\nThe CRU TS4.05 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.", "keywords": "CRU, CRU TS, 4.05, CRU TS4.05, CRU TS 4, CRU TS 4.05,atmosphere, earth science, climate,", "publicationState": "published", "dataPublishedTime": "2021-07-02T11:41:45", "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32822/?format=api", "dataPath": "/badc/cru/data/cru_ts/cru_ts_4.05", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6911362666, "numberOfFiles": 379, "fileFormat": "Data are provided in ASCII and NetCDF formats." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9011/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/513/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "The CRU TS data are produced by the Climatic Research Unit (CRU) at the University of East Anglia and are passed to the Centre for Environmental Data Analysis (CEDA) for long-term archival and distribution. Previous releases of the CRU TS data include:\r\n\r\nCRU TS 4.05 was provided to CEDA for archival in June 2021.\r\n\r\nCRU TS 4.04 was provided to CEDA for archival in April 2020.\r\n\r\nCRU TS 4.03 was provided to CEDA for archival in May 2019. \r\n\r\nCRU TS 4.02 was provided to CEDA for archival in December 2018. \r\n\r\nCRU TS 4.01 was provided to CEDA for archival in September 2017. \r\n\r\nCRU TS 4.00 was provided to CEDA for archival in March 2017. \r\n\r\nCRU TS 3.24.01 was provided to CEDA for archival in January 2017. This is the latest version available and is a replacement of the withdrawn dataset 3.24, it supersedes all previous data versions (which are available to allow user comparisons)\r\n\r\nCRU TS 3.24 was provided to CEDA for archival in July 2016. This is the latest version available, superseding all previous data versions (which are available to allow user comparisons), v3.24 has been withdrawn.\r\n\r\nCRU TS 3.23 was provided to CEDA in October 2015 by CRU. This is the latest version available, superseding all previous data versions (which are available to allow user comparisons).\r\n\r\nCRU TS 3.22 was provided to CEDA for archival in July 2014 by CRU.\r\n\r\nCRU TS 3.21 was provided to CEDA for archival in July 2013 by CRU.\r\n\r\nCRU TS 3.20 was produced in December 2012.\r\nIn March 2013, CRU TS observation databases for TMP and PRE variables were provided by CRU. Others are in preparation. In july 2013, two errors were found in the PRE and WET variables of CRU TS v3.20. These have been repaired in CRU TS v3.21. Details of the errors found are available in the Release Notes in the archive.\r\n\r\nCRU TS 3.10.01 In July 2012, systematic errors were discovered in the CRUTS v3.10 process. The effect was, in some cases, to reduce the gridded values for PRE and therefore WET. Values of FRS were found to be unrealistic in some areas due to the algorithms used for synthetic generation. The files (pre, frs and wet) were immediately removed from BADC. The corrected run for precipitation, based on the v3.10 precipitation station data, was generated as a direct replacement and given the version number 3.10.01. There were no corrected runs produced for wet and frs.\r\n\r\nCRU TS 3.00 data files acquired directly from CRU in 2007. 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Sentinel 1B was lanched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. The IW mode is the main operational mode. The IW mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. \r\n\r\nThe IW SLC product contains one image per sub-swath, per polarisation channel, for a total of three or six images. Each sub-swath image consists of a series of bursts, where each burst was processed as a separate SLC image. The individually focused complex burst images are included, in azimuth-time order, into a single sub-swath image, with black-fill demarcation in between\r\n\r\nUnlike SM and WV SLC products, which are sampled at the natural pixel spacing, the images for all bursts in all sub-swaths of an IW SLC product are re-sampled to a common pixel spacing grid in range and azimuth. 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They follow the same methods as the UK projections with the exceptions that make use of globally complete GIA estimates and a larger set of GRD fingerprints. The data consist of annual time series of the projected change in the time-mean coastal water level relative to the average value for the period 1986-2005, consistent with the IPCC Fifth Assessment Report (AR5) and the Special Report on the Ocean and Cryosphere in a Changing Climate. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). The 5th, 50th and 95th percentile projections are provided for the total sea level change and the individual components. 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However, the insufficient spatial resolution of the input data is often considered to be a limiting factor when conducting local to regional ecosystem analysis. The elevation models and orthorectified imagery created in this dataset represent the first wall-to-wall digital elevation products of the Kruger National Park (KNP) in South Africa at 25 cm pixel posting. In the light of regular flight campaigns carried out by the South African government, the workflow of the presented data sets can be reused to create height models and orthorectified images of a vulnerable ecosystem in the future. Flight campaigns were carried out by GeoSpace International, Pretoria. Data processing and preparation as well as validation of the final products was carried out by Kai Heckel (Friedrich Schiller University Jena, Germany) with the strong support of all co-authors of the related study.\r\n\r\nThe methodology is described in the following publication:\r\n\r\nHeckel, K.; Urban, M.; Bouffard, J.-S.; Baade, J.; Boucher, P.; Davies, A.; Hockridge, E.G.; Lück, W.; Ziemer, J.; Smit, I.; Jacobs, B.; Norris-Rogers, M.; Schmullius, C. (2021): The first sub-meter resolution digital elevation model of the Kruger National Park, South Africa. 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