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=8800
{ "count": 10253, "next": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=8900", "previous": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=8700", "results": [ { "ob_id": 39111, "uuid": "3cf82303153d47888191d3161ebf186d", "title": "PRIMAVERA: Met Office Hadley Centre (MOHC) HadGEM3-GC31-MM model output for the \"spinup-1950\" experiment", "abstract": "PRIMAVERA Project data from the Met Office Hadley Centre (MOHC) HadGEM3-GC31-MM model output for the \"coupled spinup with fixed 1950s forcings from 1950 initial conditions (with ocean at rest) to provide initial condition for control-1950 and hist-1950\" (spinup-1950) experiment. These are available at the following frequencies: Prim1hr, Prim3hr, Prim3hrPt, Prim6hr, Prim6hrPt, PrimOday, PrimOmon, PrimSIday, Primday, PrimdayPt and PrimmonZ. The runs included the ensemble member: r1i1p1f1.\n\nPRIMAVERA was a European Union Horizon2020 (grant agreement 641727) project.", "keywords": "PRIMAVERA, HighResMIP, climate change, MOHC, HadGEM3-GC31-MM, spinup-1950, Prim1hr, Prim3hr, Prim3hrPt, Prim6hr, Prim6hrPt, PrimOday, PrimOmon, PrimSIday, Primday, PrimdayPt, PrimmonZ", "publicationState": "published", "dataPublishedTime": "2022-11-14T20:42:12.194129", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39112/?format=api", "dataPath": "/badc/cmip6/data/PRIMAVERA/HighResMIP/MOHC/HadGEM3-GC31-MM/spinup-1950", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2080321149133, "numberOfFiles": 1831, "fileFormat": "Data are netCDF formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10839/?format=api", "geographicExtent": 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"https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50468/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50496/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50498/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50568/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50569/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50570/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50577/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50579/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50612/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51186/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51187/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52753/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52755/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/53128/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/53129/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/53139/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54260/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54319/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54895/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54896/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/55174/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57952/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59381/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59382/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59384/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59385/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59387/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59388/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59392/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59393/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59395/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59396/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59397/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59398/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59399/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59400/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59401/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59402/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59403/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59404/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59405/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59406/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59407/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59408/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59409/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59410/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59415/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59425/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59426/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59467/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59468/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59469/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59470/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59471/?format=api" ], "dataLineage": "Data were produced and verified by Met Office Hadley Centre (MOHC) scientists before upload to the Centre for Environmental Data Analysis (CEDA) and publication via the Earth Systems Grid Federation (ESGF).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/39066/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/39102/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189662/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189654/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189655/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189656/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189657/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189658/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189659/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189653/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189661/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189660/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/31069/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2520/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/CMIP6_Terms_of_Use.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 39113, "uuid": "ff4e18e3d6524cdea7fcbd9621640ec2", "title": "PRIMAVERA: Max Planck Institute for Meteorology (MPI-M) MPI-ESM1-2-HR model output for the \"control-1950\" experiment", "abstract": "PRIMAVERA Project data from the Max Planck Institute for Meteorology (MPI-M) MPI-ESM1-2-HR model output for the \"coupled control with fixed 1950's forcing (HighResMIP equivalent of pre-industrial control)\" (control-1950) experiment. These are available at the following frequencies: Prim6hr, PrimOday, PrimOmon, PrimSIday, Primday and PrimdayPt. The runs included the ensemble member: r1i1p1f1.\n\nPRIMAVERA was a European Union Horizon2020 (grant agreement 641727) project.", "keywords": "PRIMAVERA, HighResMIP, climate change, MPI-M, MPI-ESM1-2-HR, control-1950, Prim6hr, PrimOday, PrimOmon, PrimSIday, Primday, PrimdayPt", "publicationState": "published", "dataPublishedTime": "2022-11-14T20:43:49.673999", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39114/?format=api", "dataPath": "/badc/cmip6/data/PRIMAVERA/HighResMIP/MPI-M/MPI-ESM1-2-HR/control-1950", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2985454132191, "numberOfFiles": 4445, "fileFormat": "Data are netCDF formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10840/?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/6021/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6022/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6023/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/29255/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/29256/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/29257/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/29258/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50419/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50468/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50475/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50598/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50612/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52748/?format=api", 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"https://api.catalogue.ceda.ac.uk/api/v2/phenomona/59908/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60324/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60326/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60328/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60351/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60352/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60404/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60405/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62501/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/80064/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/82183/?format=api" ], "dataLineage": "Data were produced and verified by Max Planck Institute for Meteorology (MPI-M) scientists before upload to the Centre for Environmental Data Analysis (CEDA) and publication via the Earth Systems Grid Federation (ESGF).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/38942/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/38945/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189672/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189664/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189665/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189666/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189667/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189668/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189669/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189663/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189671/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/189670/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/31072/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2520/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/CMIP6_Terms_of_Use.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 39115, "uuid": "4a1f060a0f7045828533929de8870e29", "title": "PRIMAVERA: Max Planck Institute for Meteorology (MPI-M) MPI-ESM1-2-HR model output for the \"highres-future\" experiment", "abstract": "PRIMAVERA Project data from the Max Planck Institute for Meteorology (MPI-M) MPI-ESM1-2-HR model output for the \"coupled future 2015-2050 using a scenario as close to CMIP5 RCP8.5 as possible within CMIP6\" (highres-future) experiment. These are available at the following frequencies: Prim6hr, PrimOday, PrimOmon, PrimSIday, Primday and PrimdayPt. The runs included the ensemble member: r1i1p1f1.\n\nPRIMAVERA was a European Union Horizon2020 (grant agreement 641727) project.", "keywords": "PRIMAVERA, HighResMIP, climate change, MPI-M, MPI-ESM1-2-HR, highres-future, Prim6hr, PrimOday, PrimOmon, PrimSIday, Primday, PrimdayPt", "publicationState": "published", "dataPublishedTime": "2022-11-14T20:45:32.218854", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39116/?format=api", "dataPath": "/badc/cmip6/data/PRIMAVERA/HighResMIP/MPI-M/MPI-ESM1-2-HR/highres-future", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1052214997358, "numberOfFiles": 1585, "fileFormat": "Data are netCDF formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10841/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, 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Grid Federation (ESGF).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/39172/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/39182/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190799/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190791/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190792/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190793/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190794/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190795/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190796/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190790/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190798/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190797/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/39186/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2520/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/CMIP6_Terms_of_Use.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 39189, "uuid": "7a7630213de543a9a19c7015dc198970", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 2.38 (v20221115)", "abstract": "Data for Figure 2.38 from Chapter 2 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 2.38 shows indices of multi-decadal climate variability from 1854-2019 based upon several sea surface temperature data products.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\n Gulev, S.K., P.W. Thorne, J. Ahn, F.J. Dentener, C.M. Domingues, S. Gerland, D. Gong, D.S. Kaufman, H.C. Nnamchi, J. Quaas, J.A. Rivera, S. Sathyendranath, S.L. Smith, B. Trewin, K. von Schuckmann, and R.S. Vose, 2021: Changing State of the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson- Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 287–422, doi:10.1017/9781009157896.004.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has two panels with data provided for all panels.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n - AMV.nc contains Atlantic Multidecadal Variability (AMV) index from COBE, ERSST, HADI and KAPL.\r\n - PDV.nc contains PDV index from COBE, ERSST, HADI and KAPL.\r\n \r\n Data acronyms:\r\n COBE [Objective Analyses of Sea-Surface Temperature and Marine Meteorological Variables for the 20th Century using ICOADS and the Kobe Collection].\r\n ERSST [NOAA Extended Reconstructed Sea Surface Temperature].\r\n HADI [Hadley Centre Sea Ice and Sea Surface Temperature data set].\r\n KAPL [Kaplan Extended SST].\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Upper panel:\r\n - Data file: AMV.nc (10-year-filtered, yearly data, 1854-2019)\r\n \r\n Lower panel:\r\n - Data file: PDO.nc (10-year-filtered, yearly data, 1854-2019)\r\n \r\n In all the cases: - Blue line corresponds to COBE data set\r\n - Red correspinds to ERSST data set\r\n - Skyblue corresponds to HADI data set\r\n - Green corresponds to KAPL data set\r\n \r\n All sources in every nc file are arranged in columns 1 to 4, respectively.\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 2)\r\n- Link to the Supplementary Material for Chapter 2\r\n- Link to code for figure (archived on Zenodo)", "keywords": "IPCC-DDC, IPCC, AR6, WG1, WGI, Sixth Assessment Report, Working Group I, Physical Science Basis, Chapter 2, Changing state, Multi-millennial context, pre-industrial, Natural forcing, anthropogenic forcing, Radiative forcing, Large-scale indicators, observed changes, Modes of variability, Figure 2.38, AMV, PDV", "publicationState": "citable", "dataPublishedTime": "2023-05-15T11:55:59", "doiPublishedTime": "2023-07-03T20:22:02.175212", "updateFrequency": "notPlanned", "status": "ongoing", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39190/?format=api", "dataPath": "/badc/ar6_wg1/data/ch_02/ch2_fig38/v20221115", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 10654, "numberOfFiles": 5, "fileFormat": "Data are netCDF formatted" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10870/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3683/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21859/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63530/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63531/?format=api" ], "dataLineage": "Data produced by Intergovernmental Panel on Climate Change (IPCC) authors and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by the Technical Support Unit (TSU) for IPCC Working Group I (WGI).\r\nData curated on behalf of the IPCC Data Distribution Centre (IPCC-DDC).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12621/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32705/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/32717/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190819/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190820/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190821/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190822/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190823/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190824/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190825/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190826/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/39191/?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": 39195, "uuid": "94a315924ed54b08a79e331579fd8c2e", "title": "Surface velocity map of the Afar Rift Zone from 2014-19, geotiff version", "abstract": "This dataset contains a map of ground movements covering the Afar Rift Zone in Ethiopia, Eritrea, and Djibouti for the time period between October 2014 and August 2019. The Afar region is located where three tectonic plates are pulling apart, creating rift segments which are 50-100 km long. Surface deformation on these segments is not constant in time, with episodes of rifting occurring periodically and magma intrusions causing sudden ground movements. We use frequent Sentinel-1 satellite Interferometric Synthetic Aperture Radar (InSAR) observations to measure surface displacements through time across the whole region. We relate these to ground based Global Navigation Satellite Systems (GNSS) observations and combine data from different satellite tracks to produce maps of the average surface velocity in three directions (perpendicular to the rift zone, parallel to the rift zone, and vertical). The continued observation of these time-varying ground movements is important for understanding how continents break up, with data here providing evidence of how tightly focussed extension is around the rift segments and of the subsurface magma movement at several volcanic centres.\r\nThese data have been provided in geotiff format instead of the original netcdf format.", "keywords": "Sentinel-1, InSAR, GNSS, velocity, map", "publicationState": "published", "dataPublishedTime": "2022-11-24T16:17:24", "doiPublishedTime": null, "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39196/?format=api", "dataPath": "/neodc/surface_velocities_afar_rift/geotiff_data/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2592221896, "numberOfFiles": 7, "fileFormat": "These files are provided in Geotiff format." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9093/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2838/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Sentinel-1 Single Look Complex (SLC) data were sourced from the European Space Agency (ESA) Copernicus Hub, and processed using LiCSAR software (Lazecky et al., 2020). Processing and analysis was then performed by the authors (University of Leeds, COMET) in MATLAB to account for atmospheric effects, estimate uncertainties, create deformation time series and average velocity maps, reference surface velocities to the regional GNSS network (King et al., 2019), and convert velocities from the satellite look direction into rift-perpendicular and rift-parallel horizontal and vertical components. Final velocity maps and variance estimates were exported to NetCDF format for archiving. 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/33113/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190831/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190832/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190833/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190834/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190835/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190836/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190837/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190838/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190839/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190840/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190841/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190842/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/33168/?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": 39197, "uuid": "b839ae53abf94e23b0f61560349ccda1", "title": "DCMEX: cloud images from the NCAS Camera 11 from the New Mexico field campaign 2022", "abstract": "This dataset contains cloud images from the NCAS Camera 11, one of two identical cameras (designated as ncas-cam-11 and ncas-cam-12) captured at various sites around the Magdalena Mountains, New Mexico, USA, as part of the Deep Convective Microphysics Experiment (DCMEX). DCMEX examined the formation and development of clouds over mountains during July and August 2022.\r\n\r\nThese cameras were designed to take simultaneous images of the same object while placed a distance apart to create a stereo image, but this was not always possible; on some days only one camera was used or the two cameras were deployed in separate locations.\r\n\r\nThe images from this camera were taken during the duration of the DCMEX campaign of clouds from a range of sites. These are accompanied by similar images from a sibling camera (see connected dataset). Where the two cameras were operated at the same site they were synchronised in terms of camera settings (exposure, etc) and camera pointing directions to facilitate the onward use of images as stereoscopic imagery. For those latter instances files have been marked with stereo-a or stereo-b within the filename to denote where the images form the left of right image for such images. Other images do not contain these additional filename fields to denote when the cameras were used in stand-along mode. Note, due to the nature of coordinating images between the two cameras one was designated as the primary camera from which the settings were then conveyed to the secondary camera by the coordinating software. As a result exact image synchronisation wasn't possible and thus the secondary camera image may have a timestamp that is a second or so later.", "keywords": "DCMEX, Camera, Images, AMOF, stereoscopic", "publicationState": "citable", "dataPublishedTime": "2023-12-15T14:20:20", "doiPublishedTime": "2023-12-15T14:30:29.474163", "updateFrequency": "notPlanned", "status": "final", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/42894/?format=api", "dataPath": "/badc/ncas-mobile/data/ncas-cam-11/20220621_dcmex/v1.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 56752573539, "numberOfFiles": 10093, "fileFormat": "Data are JPG formatted." }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10873/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3686/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were collected by scientists on the DCMEX field campaign, with metadata added in accordance with the NCAS-IMAGE-1.0 metadata standard before archiving.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12791/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/38131/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/38137/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190847/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190848/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190849/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190850/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190851/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190852/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190853/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/200351/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198604/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198605/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198606/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198607/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198608/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198609/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198610/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198611/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198612/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/198613/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/41070/?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": 39198, "uuid": "0b2759059ad6474098e40dad73e0a8ec", "title": "Summary for Policymakers of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure SPM.1 (v20221116)", "abstract": "Data for Figure SPM.1 from the Summary for Policymakers (SPM) of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure SPM.1 shows global temperature history and causes of recent warming.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\n\r\nIPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu and B. Zhou (eds.)]. Cambridge University Press. In Press.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nThe figure has two panels, with data provided for all panels in subdirectories named panel_a and panel_b.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\nPanel a\r\n\r\nThe dataset contains:\r\n\r\n - Estimated temperature during the warmest multi-century period in at least the last 100,000 years, which occurred around 6500 years ago (4500 BCE), multi-centennial average, from AR6 WGI Chapter 2\r\n - Global surface temperature change time series relative to 1850-1900 for 1-2020 from:\r\n• 1-2000 CE reconstruction from paleoclimate archives, decadal smoothed, from PAGES2k Consortium (2019, DOI: 10.1038/s41561-019-0400-0)\r\n• 1850-2020 CE, observations, decadal smoothed, from AR6 WGI Chapter 2 assessed mean\r\n\r\nPanel b:\r\n\r\nThe dataset contains global surface temperature change time series relative to 1850-1900 for 1850-2020 from simulations from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and observations:\r\n\r\n- CMIP6 historical+ssp245 simulations (simulations with human and natural forcing, 1850-2019)\r\n- CMIP6 hist-nat simulations (simulations with natural forcing, 1850-2019)\r\n- Global Surface Temperature Anomalies (GSTA) relative to 1850-1900 from observations assessed in IPCC AR6 WG1 Chapter 2 (1850-2020)\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n---------------------------------------------------\r\nPanel a:\r\n\r\n- panel_a/SPM1_1-2000_recon.csv, 1-2000 time series, decadal smoothed, for years centred on 5-1996 CE [column 1 grey line, columns 2 and 3 grey shading]\r\n- panel_a/SPM1_1850-2020_obs.csv, 1850-2020 time series, decadal smoothed, for years centered on 1855-2016 CE [black line]\r\n- panel_a/SPM1_6500_recon.csv, bar for the warmest multi-century period in more than 100,000 years (around 6500 years ago: 4500 BCE) [grey bar]\r\n\r\nPanel b:\r\n\r\n- panel_b/gmst_changes_model_and_obs.csv. Global surface temperature change time series relative to 1850-1900 for 1850-2020 from:\r\n• CMIP6 historical+ssp245 simulations (1850-2019) [mean, brown line]\r\n• CMIP6 historical+ssp245 simulations (1850-2019) [5% range, brown shading, bottom]\r\n• CMIP6 historical+ssp245 simulations (1850-2019) [95% range, brown shading, top]\r\n• CMIP6 hist-nat simulations (1850-2019) [mean, green line]\r\n• CMIP6 hist-nat simulations (1850-2019) [5% range, green shading, bottom]\r\n• CMIP6 hist-nat simulations (1850-2019) [95% range, green shading, top]\r\n• Global Surface Temperature Anomalies (GSTA) relative to 1850-1900 from observations assessed in IPCC AR6 WG1 Chapter 2 (1850-2020) [black line]\r\n\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\nThe following weblinks are provided in the Related Documents section of this catalogue record:\r\n- Link to the figure on the IPCC AR6 website\r\n- Link to the report webpage, which includes the report component containing the figure (Summary for Policymakers), the Technical Summary (Cross-Section Box TS.1, Figure 1a) and the Supplementary Material for Chapters 2 and 3, which contains details on the input data used in Tables 2.SM.1 (Figure 2.11a) and 3.SM.1 (Figure 3.2c; FAQ 3.1, Figure 1).\r\n- Link to related publication for input data\r\n- Link to the webpage of the WGI report", "keywords": "IPCC-DDC, IPCC, AR6, WG1, WGI, SPM, Sixth Assessment Report, Working Group I, Physical Science Basis, Summary for Policymakers, Figure SPM.1, global surface temperature, pre-industrial temperature, Holocene", "publicationState": "citable", "dataPublishedTime": "2023-02-22T09:28:57", "doiPublishedTime": "2023-07-03T11:51:44.705627", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39202/?format=api", "dataPath": "/badc/ar6_wg1/data/spm/spm_01/v20221116", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 76519, "numberOfFiles": 7, "fileFormat": "csv" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9070/?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/64246/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64247/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64248/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64249/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64250/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64251/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64252/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64253/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64254/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64255/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64256/?format=api" ], "dataLineage": "Data produced by Intergovernmental Panel on Climate Change (IPCC) authors and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by the Technical Support Unit (TSU) for IPCC Working Group I (WGI).\r\nData curated on behalf of the IPCC Data Distribution Centre (IPCC-DDC).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12561/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32705/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/32729/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190859/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190861/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190860/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190854/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190855/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190856/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190857/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190858/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190867/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190862/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190864/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190865/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32911/?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": 39205, "uuid": "1b91153925dd474387bb696d59adbd15", "title": "Summary for Policymakers of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure SPM.5 (v20221116)", "abstract": "Data for Figure SPM.5 from the Summary for Policymakers (SPM) of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure SPM.5 shows changes in annual mean surface temperatures, precipitation, and total column soil moisture.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\n\r\nIPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels with 11 maps. All data is provided, except for panel a1.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n\r\n- Annual mean temperature change (°C) (relative to 1850-1900)\r\n- Annual mean precipitation change (%) (relative to 1850-1900)\r\n- Annual mean soil moisture change (standard deviation of interannual variability) (relative to 1850-1900)\r\n\r\nThe data is given for global warming levels (GWLs), namely +1.0°C (temperature only), +1.5°C, 2.0°C, and +4.0°C.\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\nPanel a:\r\n- Data file: Panel_a2_Simulated_temperature_change_at_1C.nc, simulated annual mean temperature change (°C) at 1°C global warming relative to 1850-1900 (right).\r\n\r\nPanel b:\r\n- Data file: Panel_b1_Simulated_temperature_change_at_1_5C.nc, simulated annual mean temperature change (°C) at 1.5°C global warming relative to 1850-1900 (left).\r\n- Data file: Panel_b2_Simulated_temperature_change_at_2C.nc, simulated annual mean temperature change (°C) at 2.0°C global warming relative to 1850-1900 (center).\r\n- Data file: Panel_b3_Simulated_temperature_change_at_4C.nc, simulated annual mean temperature change (°C) at 4.0°C global warming relative to 1850-1900 (right).\r\n\r\nPanel c:\r\n- Data file: Panel_c1_Simulated_precipitation_change_at_1_5C.nc, simulated annual mean precipitation change (%) at 1.5°C global warming relative to 1850-1900 (left).\r\n- Data file: Panel_c2_Simulated_precipitation_change_at_2C.nc, simulated annual mean precipitation change (%) at 2.0°C global warming relative to 1850-1900 (center).\r\n- Data file: Panel_c3_Simulated_precipitation_change_at_4C.nc, simulated annual mean precipitation change (%) at 4.0°C global warming relative to 1850-1900 (right).\r\n\r\nPanel d:\r\n- Data file: Figure_SPM5_d1_cmip6_SM_tot_change_at_1_5C.nc, simulated annual mean total column soil moisture change (standard deviation) at 1.5°C global warming relative to 1850-1900 (left).\r\n- Data file: Figure_SPM5_d2_cmip6_SM_tot_change_at_2C.nc, simulated annual mean total column soil moisture change (standard deviation) at 2.0°C global warming relative to 1850-1900 (center).\r\n- Data file: Figure_SPM5_d3_cmip6_SM_tot_change_at_4C.nc, simulated annual mean total column soil moisture change (standard deviation) at 4.0°C global warming relative to 1850-1900 (right).\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblink is provided in the Related Documents section of this catalogue record:\r\n- Link to origin of figure (IPCC WG1 Summary for Policy Makers)\r\n- Link to the report webpage, which includes the component containing the figure (Summary for Policymakers), the Technical Summary (Figures TS.3 and TS.5) and the Supplementary Material for Chapters 1, 4 and 11, which contains details on the input data used in Tables 1.SM.1 (Figure 1.14), 4.SM.1 (Figures 4.31 and 4.32) and 11.SM.9 (Figure 11.19).\r\n- Link to the figure on the IPCC AR6 website", "keywords": "IPCC-DDC, IPCC, AR6, WG1, WGI, SPM, Sixth Assessment Report, Working Group I, Physical Science Basis, Summary for Policymakers, Figure SPM.5, global warming level, temperature, precipitation, soil moisture, projection, CMIP6", "publicationState": "citable", "dataPublishedTime": "2023-02-22T12:09:25", "doiPublishedTime": "2023-07-03T12:14:03.061212", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39206/?format=api", "dataPath": "/badc/ar6_wg1/data/spm/spm_05/v20221116", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 35756500, "numberOfFiles": 15, "fileFormat": "net-CDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9027/?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/30956/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46705/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46706/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46707/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46708/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46709/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46711/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50559/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50561/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63529/?format=api" ], "dataLineage": "Data produced by Intergovernmental Panel on Climate Change (IPCC) authors and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by the Technical Support Unit (TSU) for IPCC Working Group I (WGI).\r\nData curated on behalf of the IPCC Data Distribution Centre (IPCC-DDC).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12563/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32705/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/32729/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190886/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190880/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190887/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190881/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190885/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190882/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190883/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190884/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/190888/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32876/?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": 39223, "uuid": "4262e08336404147878b3adeb4e68950", "title": "CCMI-2022: refD1 data produced by the CCSR-NIES MIROC3.2 model at NIES", "abstract": "This dataset contains model data for CCMI-2022 experiment refD1 produced by the CCSR-NIES MIROC3.2 model run by the modelling team at NIES (National Institute for Environmental Studies) in Japan.\r\n\r\nThe refD1 experiment is a hindcast of the atmospheric state, using a prescribed evolution of sea surface temperature and sea ice from observations along with forcings for the extra-terrestrial solar flux, long-lived greenhouse gases and ozone depleting substances, stratospheric aerosols and an imposed quasi-biennial oscillation that approximate the observed variations over the historical period to the fullest extent possible.\r\n\r\nThe CCMI-2022 Chemistry-climate model initiative is a set of model experiments focused on the stratosphere, with the goals of providing updated projections towards the future evolution of the ozone layer and improving our understanding of chemistry-climate interactions from models.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n- Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI)\r\n- A new set of Chemistry-Climate Model Initiative (CCMI) Community Simulations to Update the Assessment of Models and Support Upcoming Ozone Assessment Activities, David Plummer and Tatsuya Nagashima and Simone Tilmes and Alex Archibald and Gabriel Chiodo and Suvarna Fadnavis and Hella Garny and Beatrice Josse and Joowan Kim and Jean-Francois Lamarque and Olaf Morgenstern and Lee Murray and Clara Orbe and Amos Tai and Martyn Chipperfield and Bernd Funke and Martin Juckes and Doug Kinnison and Markus Kunze and Beiping Luo and Katja Matthes and Paul A. 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These are available at the following frequencies: AERday, Amon, Eday, Omon, SImon and day. 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The simulations are described in Berthou et al (2020) and Brogli et al (2022); they include two ECMWF Interim hindcast simulations (one from each model), two GCM-driven simulations (UM-only, present-climate and end-of-century RCP8.5), and one pseudo-global warming simulation (COSMO-only, end-of-century RCP8.5). The tracks are diagnosed using the DYMECS tracking scheme (Stein et al 2014 and Crook et al 2019). The tracking scheme detects all precipitation objects, but only mesoscale convection systems (MCSs) are sub-selected for analysis; MCSs are defined to be tracks with lifetime peak precipitation exceeding 20 mm/h and lifetime peak area exceeding 1000 squared kilometres. Data are in csv files, and are Python and R readable. These data were produced for the NERC-supported FUTURE-STORMS project (grant number: NE/R01079X/1); the underlying climate simulations were produced for the EU Horizon 2020 project European Climate Prediction System (EUCP) project (grant: 776613).", "keywords": "extreme precipitation,convection-permitting models,object tracking", "publicationState": "citable", "dataPublishedTime": "2022-12-02T14:50:45", "doiPublishedTime": "2022-12-06T09:56:46.035257", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39344/?format=api", "dataPath": "/badc/deposited2022/EUCP_UKMO_ETH_MCSs/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 143008084, "numberOfFiles": 6, "fileFormat": "BADC-CSV" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10908/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3699/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64205/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64206/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64207/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64208/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64209/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64210/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64211/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64212/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64213/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64214/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64215/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64216/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64217/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64218/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64219/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64220/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64221/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64222/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64223/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64224/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64225/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64226/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64227/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64228/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64229/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64230/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64231/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64232/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64233/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64234/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64235/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64236/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64237/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64238/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64239/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64240/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64241/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64242/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64243/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/64244/?format=api" ], "dataLineage": "Data is derived from various of 2.2km Europe-wide convection permitting model simulations, which are part of the European Climate Prediction project. A subset of the raw model data will be made publicly available in the futurre through the Earth System Grid Federation nodes. Data were prepared by the project team before archiving at CEDA.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12301/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/39321/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191786/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191787/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191788/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191789/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191790/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191791/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191799/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192483/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191800/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191801/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191802/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191803/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191804/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191805/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/39322/?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": 39323, "uuid": "edd6991e06024f7d9ee06460ec7cd7f6", "title": "Solar-induced Chlorophyll Fluorescence from GOSAT's TANSO-FTS by the University of Leicester (v3.0)", "abstract": "Solar-induced Chlorophyll Fluorescence (SIF) data created from the Greenhouse Gas Observing Satellite (GOSAT) Level 1B data using an adapted version of the University of Leicester Full-Physics retrieval scheme (UoL-FP). These dataset contains both Level 2 and Level 3 S-polarised SIF. The Level 2 data are in daily files and are not averaged, whilst the Level 3 data are averaged spatially and temporally on both a monthly and weekly timescale.\r\n\r\nThe SIF data was derived from L1B data from the TANSO-FTS ( Thermal and Near Infrared Sensor for carbon Observation - Fourier Transform Spectrometer) instrument on the GOSAT satellite. For each GOSAT sounding, the S-polarised spectra have been extracted from two narrow micro-windows outside the Oxygen A-band, at around 755 nm and 772 nm. For more information on the retrieval setup and bias correction, please see \"Novel Methods for Atmospheric Carbon Dioxide Retrieval from the JAXA GOSAT and NASA OCO-2 Satellites - Part II: Remote Sensing of Chlorophyll Fluorescence\" by Peter Somkuti.", "keywords": "Solar Induced Fluorescence, SIF, GOSAT", "publicationState": "citable", "dataPublishedTime": "2022-12-05T14:34:46", "doiPublishedTime": "2022-12-05T14:42:13", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39325/?format=api", "dataPath": "/neodc/uol_gosat_sif/data/v3.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2905224115, "numberOfFiles": 5320, "fileFormat": "NetCDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10915/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2534/?format=api", "nonGeographicFlag": false, "phenomena": [ 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"https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66383/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66384/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66385/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66386/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66387/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66388/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66389/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66390/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66391/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66392/?format=api" ], "dataLineage": "These data were produced by the National Centre for Earth Observation at the University of Leicester using the ALICE High Performance Computing Facility.", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ 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model output for the \"idealized transient global deforestation\" (deforest-globe) experiment. These are available at the following frequencies: Amon, Lmon and Omon. The runs included the ensemble member: r1i1p1f2.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record.\n\nThe the MIROC team team consisted of the following agencies: Atmosphere and Ocean Research Institute (AORI), Centre for Climate System Research - National Institute for Environmental Studies (CCSR-NIES) and Atmosphere and Ocean Research Institute (AORI).", "keywords": "CMIP6, WCRP, climate change, MIROC, MIROC-ES2L, deforest-globe, Amon, Lmon, Omon", "publicationState": "published", "dataPublishedTime": "2022-11-25T11:00:20.509409", "doiPublishedTime": null, "updateFrequency": "asNeeded", "status": "ongoing", "result_field": { "ob_id": 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scientists before publication via the Earth Systems Grid Federation (ESGF) and a copy obtained by the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/28348/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/28736/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191828/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191824/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191825/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191826/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191827/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191831/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191833/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191822/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191823/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191829/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191834/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191832/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/191830/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/39328/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2520/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/CMIP6_Terms_of_Use.pdf", "licenceClassifications": "" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }, { "ob_id": 39329, "uuid": "39229329653949169f7fad906118376a", "title": "WCRP CMIP6: the MIROC team MIROC-ES2L model output for the \"esm-ssp585-ssp126Lu\" experiment", "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the MIROC team MIROC-ES2L model output for the \"emissions-driven SSP5-8.5 with SSP1-2.6 land use\" (esm-ssp585-ssp126Lu) experiment. 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chemistry-climate interactions from models.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n- Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI)\r\n- A new set of Chemistry-Climate Model Initiative (CCMI) Community Simulations to Update the Assessment of Models and Support Upcoming Ozone Assessment Activities, David Plummer and Tatsuya Nagashima and Simone Tilmes and Alex Archibald and Gabriel Chiodo and Suvarna Fadnavis and Hella Garny and Beatrice Josse and Joowan Kim and Jean-Francois Lamarque and Olaf Morgenstern and Lee Murray and Clara Orbe and Amos Tai and Martyn Chipperfield and Bernd Funke and Martin Juckes and Doug Kinnison and Markus Kunze and Beiping Luo and Katja Matthes and Paul A. 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land-sea contrast on convective aggregation", "abstract": "This dataset contains model data for the impact of a land-sea contrast on convective aggregation in radiative-convective equilibrium, Dingley et al., 2022. 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The CALI-01 plot site was situated in the Grove of Old Trees, which is a 48-acre (19 ha) open space reserve woodland of mature coast redwood trees. The grove grows on a broad, flat ridgetop west of Occidental, California,\r\n\r\nThe project scanned all trees in the permanent sample plot (PSP) spanning a range of soil fertility and productivity gradients (24 x 1 ha PSPs in total). The aim of the weighing trees with lasers project is to test if current allometric relationships are invariant across continents or whether they differ significantly and require continental-level models; quantify the impact of assumptions of tree shape and wood density on tropical forest allometry; test hypotheses relating to pan-tropical differences in observed AGB (Above Ground Biomass) from satellite and field data. It also aims to apply new knowledge to assessing retrieval accuracy of forthcoming ESA BIOMASS and NASA GEDI (Global Ecosystem Dynamics Investigation Lidar) missions and providing calibration datasets; In addition to testing the capability of low-cost instruments to augment TLS data, including: UAVs (unmanned aerial vehicle) for mapping cover and canopy height; low-cost lidar instruments to assess biomass rapidly, at lower accuracy.", "keywords": "Terrestrial Laser Scanner, Grove of old trees, California, Redwood", "publicationState": "citable", "dataPublishedTime": "2025-06-19T10:29:33", "doiPublishedTime": "2025-06-26T14:08:41.957706", "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39482/?format=api", "dataPath": "/neodc/tls/data/raw/usa/CALI-01/2017-09-05.001.riproject", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 47010934541, "numberOfFiles": 1768, "fileFormat": "The scan folder contains a number of open and proprietary formats file formats CSV, ASCII, text, PNG , RXP and PAT" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/7312/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3726/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Provided by Andrew Burt UCL to CEDA for publication", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/13432/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/26683/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/26677/?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/192569/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192570/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192571/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192572/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192573/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192574/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192575/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192576/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192577/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192578/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192583/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/39483/?format=api", "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": 1138, "name": "NDGO0003" } ] }, { "ob_id": 39484, "uuid": "7498da3969884bb9a2c7bac20bf5c96d", "title": "Weighing trees with lasers project: terrestrial laser scanner data; The Grove of Old Trees reserve California (Plot CALI-02), September 2017", "abstract": "This dataset is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations, which have been re-surveyed at different times. The CALI-02 plot site was situated in the Grove of Old Trees, which is a 48-acre (19 ha) open space reserve woodland of mature coast redwood trees. The grove grows on a broad, flat ridgetop west of Occidental, California,\r\n\r\nThe project scanned all trees in the permanent sample plot (PSP) spanning a range of soil fertility and productivity gradients (24 x 1 ha PSPs in total). The aim of the weighing trees with lasers project is to test if current allometric relationships are invariant across continents or whether they differ significantly and require continental-level models; quantify the impact of assumptions of tree shape and wood density on tropical forest allometry; test hypotheses relating to pan-tropical differences in observed AGB (Above Ground Biomass) from satellite and field data. It also aims to apply new knowledge to assessing retrieval accuracy of forthcoming ESA BIOMASS and NASA GEDI (Global Ecosystem Dynamics Investigation Lidar) missions and providing calibration datasets; In addition to testing the capability of low-cost instruments to augment TLS data, including: UAVs (unmanned aerial vehicle) for mapping cover and canopy height; low-cost lidar instruments to assess biomass rapidly, at lower accuracy.", "keywords": "Terrestrial Laser Scanner, Grove of old trees, California, Redwood", "publicationState": "citable", "dataPublishedTime": "2025-06-19T10:59:12", "doiPublishedTime": "2025-06-26T14:09:08.773947", "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39486/?format=api", "dataPath": "/neodc/tls/data/raw/usa/CALI-02/2017-09-09.001.riproject", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12937428305, "numberOfFiles": 447, "fileFormat": "The scan folder contains a number of open and proprietary formats file formats CSV, ASCII, text, PNG , RXP and PAT" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10949/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3727/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Provided by Andrew Burt UCL to CEDA for publication", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/13433/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/26683/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/26677/?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/192584/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192585/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192586/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192587/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192588/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192589/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192590/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192591/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192592/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192593/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192594/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/39489/?format=api", "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": 1138, "name": "NDGO0003" } ] }, { "ob_id": 39487, "uuid": "422a95d694bf4963854a2f0ab5d166d6", "title": "Weighing trees with lasers project: terrestrial laser scanner data; The Sea Ranch woods California (Plot CALI-07), September 2017", "abstract": "This dataset is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations, which have been re-surveyed at different times. The CALI-07 plot site was situated in the Sea Ranch Woods near Sonoma California.\r\n\r\nThe project scanned all trees in the permanent sample plot (PSP) spanning a range of soil fertility and productivity gradients (24 x 1 ha PSPs in total). The aim of the weighing trees with lasers project is to test if current allometric relationships are invariant across continents or whether they differ significantly and require continental-level models; quantify the impact of assumptions of tree shape and wood density on tropical forest allometry; test hypotheses relating to pan-tropical differences in observed AGB (Above Ground Biomass) from satellite and field data. It also aims to apply new knowledge to assessing retrieval accuracy of forthcoming ESA BIOMASS and NASA GEDI (Global Ecosystem Dynamics Investigation Lidar) missions and providing calibration datasets; In addition to testing the capability of low-cost instruments to augment TLS data, including: UAVs (unmanned aerial vehicle) for mapping cover and canopy height; low-cost lidar instruments to assess biomass rapidly, at lower accuracy.", "keywords": "Terrestrial Laser Scanner, The Sea Ranch, California, Redwood", "publicationState": "citable", "dataPublishedTime": "2025-06-19T10:45:53", "doiPublishedTime": "2025-06-26T14:09:31.844308", "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39493/?format=api", "dataPath": "/neodc/tls/data/raw/usa/CALI-07/2017-09-18.001.riproject", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 42515072754, "numberOfFiles": 1617, "fileFormat": "The scan folder contains a number of open and proprietary formats file formats CSV, ASCII, text, PNG , RXP and PAT" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10949/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3729/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Provided by Andrew Burt UCL to CEDA for publication", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/13434/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/26683/?format=api" ], "observationcollection_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/26677/?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/192596/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192598/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192599/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192600/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192601/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192602/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192603/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192604/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192605/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192606/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192608/?format=api" ], "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/39485/?format=api", "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": 1138, "name": "NDGO0003" } ] }, { "ob_id": 39495, "uuid": "f4654030223445b0bac63a23aaa60620", "title": "ESA Snow Climate Change Initiative (Snow_cci): Fractional Snow Cover in CryoClim, v1.0", "abstract": "This dataset contains the CryoClim Daily Snow Cover Fraction (snow on ground) product, produced by the Snow project of the ESA Climate Change Initiative programme.\r\n\r\nFractional snow cover (FSC) on the ground indicates the area of snow observed from space on land surfaces, in forested areas compensated for the effect of trees hiding the ground surface snow cover under the forest canopy. The FSC is given in percentage (%) per grid cell. \r\n\r\nThe global snow_cci CryoClim fractional snow cover (FSC) product is available at 0.05° grid size (about 5 km) for all land areas, excluding Antarctica and Greenland ice sheet. The coastal zones of Greenland are included. \r\n\r\nThe CryoClim FSC time series provides daily products for the period 1982 – 2019. \r\n\r\nThe CryoClim FSC product is based on a multi-sensor time-series fusion algorithm combining observations by optical and passive microwave radiometer (PMR) data. The product combines an historical record of AVHRR sensor data with PMR data from the SMMR, SSM/I and SSMIS sensors. \r\n\r\nThe overall aim of the CryoClim FSC climate data record is to provide one of the longest snow cover extent time series available with global coverage and without hindrance from clouds and polar night. This has been achieved by utilising the best features of optical and passive microwave radiometer observations of snow using a sensor-fusion algorithm generating a consistent time series of global FSC products (Solberg et al. 2014, 2015; Rudjord et al. 2015). \r\n\r\nThe snow_cci project has advanced the original CryoClim binary product to an FSC product. The thematic variable represents snow on the ground (SCFG). \r\n\r\nAVHRR sensors aboard the satellites NOAA-7, -9, -11, -14, -16, -18, -19 have been used as the optical data source, and SMMR, SSM/I and SSMIS sensors aboard the Nimbus-7, DMSP F8, DMSP F10, DMSP F11, DMSP F13, DMSP F14, DMSP F15, DMSP F16, DMSP F17 and DMSP F18 satellites, respectively, have been used as PMR data source. To have the best possible input data quality, we have used fundamental climate data records (FCDRs) developed by EUMETSAT CM SAF for AVHRR (Karlson et al. 2020) and PMR (Fenning et al. 2017).\r\n\r\nThe optical algorithm component processes all available swaths from AVHRR GAC. The calculations are based on a Bayesian approach using a set of signatures (instrument channel combinations) and statistical coefficients. For each pixel of the swath, the probabilities for the surface classes snow, bare ground and cloud are estimated. The statistical coefficients are based on pre-knowledge of the typical behaviour of the surface classes in the different parts of the electromagnetic spectrum.\r\n\r\nThe algorithm for PMR is also based on a Bayesian estimation approach. For SSM/I and SSMIS four snow classes were defined to model the snow surface state. For SMMR two classes were considered. The algorithm estimates the probability for each snow class given the PMR measurements. Land cover data are included to improve the performance of the Bayesian algorithm. This made it possible to construct a Bayesian estimator for each land cover regime. \r\n\r\nThe multi-sensor multi-temporal fusion algorithm (Rudjord et al. 2015; Solberg et al. 2017) is based on a hidden Markov model (HMM) simulating the snow states based on observations with PMR and optical sensors. The basic idea is to simulate the states the snow surface goes through during the snow season with a state model. The states are not directly observable, but the remote sensing observations give data describing the snow conditions, which are related to the snow states. The HMM solution represents not only a multi-sensor model but also a multi-temporal model. The sequence of states over time is conditioned to follow certain optimisation criteria.\r\n\r\nThe advancement from binary to fractional snow cover carried out by snow_cci has followed two main paths: First, we introduced more HMM states to be able to classify the snow cover into 10% FSC intervals. However, introducing 100 primary states to obtain 1% FSC intervals would not give a stable model. For obtaining higher precision, we have interpolated between HMM states using a secondary Viterbi sequence. The two probabilities are used as weights to estimate the FSC.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the grid size of the FSC product. Water areas are masked if more than 30% of the grid cell is classified as water, permanent snow and ice areas are masked if more than 50% is identified as such areas in the aggregated map. The product uncertainty for observed land areas is provided as unbiased root mean square error (RMSE) per grid cell in the ancillary variable.\r\n\r\nThe FSC product aims to serve the needs of users working with the cryosphere and climate research and monitoring activities, including the assessment of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nThe Norwegian Computing Center (Norsk Regnesentral, NR) is together with the Norwegian Meteorological Institute (MET Norway) responsible for the FSC product development and generation from satellite data. ENVEO IT GmbH developed and prepared all auxiliary data sets used for the product generation.\r\n\r\nFor the whole time series, there are 27 days with neither optical nor PMR retrieval. These are individual days and not series of days in a row. The multi-sensor time-series algorithm handles this by making a best estimate of snow cover, based on days both prior to and following after the lack of data. This will not reduce the quality of the snow maps much for days without data as long as they are just individual days.\r\nThe algorithm estimating the uncertainty associated with the FSC maps needs observations of covariates from the same day as the time stamp of the FSC product. These covariates are partly based on data from PMR sensors. Hence, estimates of uncertainty could not be produced for days lacking PMR acquisitions. Most days lacking PMR are in the period 1982-1988 (53 days), and there are only two cases after that (in 2008).", "keywords": "ESA, CCI, Snow, Snow Cover Fraction, Snow Cover, Sensor Fusion, AVHRR, SMMR, SSM/I, SSMIS", "publicationState": "citable", "dataPublishedTime": "2023-08-08T13:15:33", "doiPublishedTime": "2023-08-08T13:17:01", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39794/?format=api", "dataPath": "/neodc/esacci/snow/data/scfg/CryoClim/v1.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 32341088431, "numberOfFiles": 13696, "fileFormat": "NetCDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8858/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2614/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6021/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6022/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/32072/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/61130/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/61131/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62643/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62644/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62645/?format=api" ], "dataLineage": "The snow_cci CryoClim FSC products are based on fundamental climate data records (FCDRs) developed by EUMETSAT CM SAF for AVHRR (Karlson et al. 2020) and PMR (Fenning et al. 2017). These have been used to assure having the best possible temporal quality of input data. The FCDRs are based on optical data from AVHRR sensors aboard the satellites NOAA-7, -9, -11, -14, -16, -18, -19, and PMR data from SMMR, SSM/I and SSMIS sensors aboard the DMSP F8, DMSP F11, DMSP F13 and DMSP F17 satellites, respectively. \r\n\r\nThe snow_cci CryoClim FSC processing chain includes retrieval of fractional snow cover per grid cell for all grid cells. Permanent snow and ice areas as well as water bodies are masked in the FSC products using the corresponding classes from the Land Cover CCI map of the year 2000 as auxiliary layers. All FSC products are prepared according to the CCI data standards.\r\n\r\nThe processing chain was developed by Norwegian Computing Center (Norsk Regnesentral, NR) and Norwegian Meteorological Institute (MET Norway), and the processing took place on the Fram supercomputer operated by UNINETT Sigma2 AS (Sigma2, The Norwegian e-infrastructure for Research & Education). \r\n\r\nData were supplied for archiving at the Centre for Environmental Data Analysis (CEDA) as part of the ESA CCI Open Data Portal.\r\n\r\nReferences:\r\n\r\nFennig, K., Schröder, M. and Hollmann, R., 2017. Fundamental Climate Data Record of Microwave Imager Radiances, Edition 3, Satellite Application Facility on Climate Monitoring. https://doi.org/10.5676/EUM_SAF_CM/FCDR_MWI/V003\r\n\r\nKarlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Solodovnik, I., Meirink, J. F., Devasthale, A., Kothe, S., Jääskeläinen, E., Sedlar, J., Benas, N. van Zadelhoff, G.-J., Stein, D., Finkensieper, S., Håkansson, N., Hollmann, R., Kaiser, J., and Werscheck, M. 2020. CLARA-A2.1: CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data - Edition 2.1, Satellite Application Facility on Climate Monitoring. https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V002_01", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12668/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/30229/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192622/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192623/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192624/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192625/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192626/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192627/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192629/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192628/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192630/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192631/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192632/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192633/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192634/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192635/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193176/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193177/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193178/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/39708/?format=api", "procedureComputation": null, "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2571/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_snow_terms_and_conditions.pdf", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1140, "name": "ESACCI" } ] }, { "ob_id": 39499, "uuid": "6b143f0feab14045b91556438b48cceb", "title": "TCOM-CH4: TOMCAT CTM and Occultation Measurements based daily zonal stratospheric methane profile dataset (1991-2021) constructed using machine-learning", "abstract": "This dataset contains daily zonal stratospheric methane profile outputs between 1991-2021 simulated by the TOMCAT model.\r\n\r\nThe TOMCAT simulation is performed at T64L32 resolution that is similar to the one used in Dhomse et al., (2021, 2022) for 1991-2021 time period. \r\n\r\nCollocated methane profiles are divided in five latitude bins: SH polar (90S-50S), SH mid-lat (70S-20S), tropics (40S-40N), NH mid-lat (20N-70N) and NH polar (50N-90N). Initially, differences are calculated for each zonal bins for 46 height levels (15km to 60km). Then separate XGBoost regression models are trained for the methane differences between TOMCAT and measurements at each level for a given latitude bin. \r\n\r\nThe same model is used for all day/night time (2 X11323 days) TOMCAT output sampled at 1.30 am and 1.30 pm local time at the equator. Thus bias corrections for a given model grid are added to the original TOMCAT day and night time profiles. Height resolved data are then interpolated on 28-pressure levels (300 - 0.1hPa). For overlapping latitude bins, we use averages and then calculate daily zonal mean values. For more details regarding this methodology see the associated presentation on Zenodo.\r\n\r\nDataset also includes two files containing daily mean zonal mean methane profiles on height (15-60 km) and pressure (300-0.1 hPa) levels:\r\n\r\n- zmch4_TCOM_hlev_T2Dz_1991_2021.nc – height level data (15 to 60 km)\r\n- zmch4_TCOM_plev_T2Dz_1991_2021.nc – pressure level data (300 to 0.1 hPa)\r\n\r\nThe exact cause of unusual methane variations during 1991-1994 is unknown, however some recent studies argue that it could be due to sudden changes in methane loss processes following Mount Pinatubo eruption as well as significant changes in methane emissions following collapse of the Soviet Union.", "keywords": "stratosphere, methane profiles, satellite, machine-learning", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "updateFrequency": "", "status": "pending", "result_field": null, "timePeriod": null, "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?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/192647/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192648/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192649/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192650/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192651/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192652/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192653/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/39527/?format=api", "permissions": [], "discoveryKeywords": [] }, { "ob_id": 39500, "uuid": "a35f1fba6c1b43579f6ea9f7c0d00314", "title": "TCOM-N2O: TOMCAT CTM and Occultation Measurements based daily zonal stratospheric nitrous oxide profile dataset (1991-2021) constructed using machine-learning", "abstract": "This dataset contains daily zonal stratospheric nitrous oxide profile outputs between 1991-2021 simulated by the TOMCAT model.\r\n\r\nThe TOMCAT simulation is performed at T64L32 resolution that is similar to the one used in Dhomse et al., (2021, 2022) for 1991-2021 time period. Model profile are sample at ACE-FTS (2004-present) measurement collocation, so that model output is at the nearest lat/lon and time. Then collocated N2O profiles are divided in five latitude bins: SH polar (90S-50S), SH mid-lat (70S-20S), tropics (40S-40N), NH mid-lat (20N-70N) and NH polar (50N-90N). Corrections for overlapping latitude are averaged to ensure that mean correction terms do not have sharp edges\r\n\r\nInitially, differences are calculated for each zonal bins for 51 height levels (10km to 60km). Then separate XGBoost regression models are trained for the N2O differences between TOMCAT and measurements at each level for a given latitude bin. Same model is used for all day/night time (2 X11323 days) TOMCAT output sampled at 1.30 am and 1.30 pm local time at the equator. Bias corrections for a given model grid are calculated using XGBoost and are added to the original TOMCAT day and night time profiles. Height resolved data are then interpolated on 28-pressure levels (300 - 0.1hPa). For overlapping latitude bins, we use averages and then calculate daily zonal mean values. For more details see associated presentation on Zenodo.\r\n\r\nDataset also includes two files containing daily mean zonal mean N2O profiles on height (15-60 km) and pressure (300-0.1 hPa) levels:\r\n\r\nzmn2o_TCOM_hlev_T2Dz_1991_2021.nc – height level data (15 to 60 km)\r\nzmn2o_TCOM_plev_T2Dz_1991_2021.nc – pressure level data (300 to 0.1 hPa)\r\n\r\nNote that there is no observational constrain for 1991-2003 time period, hence correction terms assume that there are no significant discontinuities in ERA5 reanalysis fields that are used drive TOMCAT transport.", "keywords": "machine learning, stratosphere, nitrous oxide profiles, chemical model", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "updateFrequency": "", "status": "pending", "result_field": null, "timePeriod": null, "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?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/192659/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192660/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192654/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192655/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192656/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192657/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192658/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/39526/?format=api", "permissions": [], "discoveryKeywords": [] } ] }