Observation Instance
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/37532/?format=api
{ "ob_id": 37532, "uuid": "12f0d7db5ed747d2940210e52211ed6a", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.40 (v20220614)", "abstract": "Data for Figure 3.40 from Chapter 3 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 3.40 shows the observed and simulated Atlantic Multidecadal Variability (AMV).\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\nEyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on 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. 423–552, doi:10.1017/9781009157896.005.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has six panels. Files are not separated according to the panels.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n amv.obs.nc contains\r\n - Observed SST anomalies associated with the AMV pattern\r\n - Observed AMV index time series (unfiltered)\r\n - Observed AMV index time series (low-pass filtered)\r\n - Taylor statistics of the observed AMV patterns\r\n \r\n amv.hist.cmip6.nc contains\r\n - Statistical significance of the observed SST anomalies associated with the AMV pattern\r\n - Simulated SST anomalies associated with the AMV pattern\r\n - Simulated AMV index time series (unfiltered)\r\n - Simulated AMV index time series (low-pass filtered)\r\n - Taylor statistics of the simulated AMV patterns\r\n \r\n based on CMIP6 historical simulations.\r\n \r\n amv.hist.cmip5.nc contains\r\n - Simulated SST anomalies associated with the AMV pattern\r\n - Simulated AMV index time series (unfiltered)\r\n - Simulated AMV index time series (low-pass filtered)\r\n - Taylor statistics of the simulated AMV patterns\r\n based on CMIP5 historical simulations.\r\n \r\n amv.piControl.cmip6.nc contains\r\n - Simulated SST anomalies associated with the AMV pattern\r\n - Simulated AMV index time series (unfiltered)\r\n - Simulated AMV index time series (low-pass filtered)\r\n - Taylor statistics of the simulated AMV patterns\r\n based on CMIP6 piControl simulations.\r\n \r\n amv.piControl.cmip5.nc contains\r\n - Simulated SST anomalies associated with the AMV pattern\r\n - Simulated AMV index time series (unfiltered)\r\n - Simulated AMV index time series (low-pass filtered)\r\n - Taylor statistics of the simulated AMV patterns\r\n based on CMIP5 piControl simulations.\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - amv_pattern_obs_ref in amv.obs.nc: shading\r\n - amv_pattern_obs_signif (dataset = 1) in amv.obs.nc: cross markers\r\n \r\n Panel b:\r\n - Multimodel ensemble mean of amv_pattern in amv.hist.cmip6.nc: shading, with their sign agreement for hatching\r\n \r\n Panel c:\r\n - tay_stats (stat = 0, 1) in amv.obs.nc: black dots\r\n - tay_stats (stat = 0, 1) in amv.hist.cmip6.nc: red crosses, and their multimodel ensemble mean for the red dot\r\n - tay_stats (stat = 0, 1) in amv.hist.cmip5.nc: blue crosses, and their multimodel ensemble mean for the blue dot\r\n \r\n Panel d:\r\n - Lag-1 autocorrelation of amv_timeseries_raw in amv.obs.nc: black horizontal lines in left\r\n . ERSSTv5: dataset = 1\r\n . HadISST: dataset = 2\r\n . COBE-SST2: dataset = 3\r\n - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.piControl.cmip5.nc: blue open box-whisker in the left\r\n - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.piControl.cmip6.nc: red open box-whisker in the left\r\n - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.hist.cmip5.nc: blue filled box-whisker in the left\r\n - Multimodel ensemble mean and percentiles of lag-1 autocorrelation of amv_timeseries_raw in amv.hist.cmip6.nc: red filled box-whisker in the left\r\n - Lag-10 autocorrelation of amv_timeseries in amv.obs.nc: black horizontal lines in right\r\n . ERSSTv5: dataset = 1\r\n . HadISST: dataset = 2\r\n . COBE-SST2: dataset = 3\r\n - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.piControl.cmip5.nc: blue open box-whisker in the right\r\n - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.piControl.cmip6.nc: red open box-whisker in the right\r\n - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.hist.cmip5.nc: blue filled box-whisker in the right\r\n - Multimodel ensemble mean and percentiles of lag-10 autocorrelation of amv_timeseries in amv.hist.cmip6.nc: red filled box-whisker in the right\r\n \r\n Panel e:\r\n - Standard deviation of amv_timeseries_raw in amv.obs.nc: black horizontal lines in left\r\n . ERSSTv5: dataset = 1\r\n . HadISST: dataset = 2\r\n . COBE-SST2: dataset = 3\r\n - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.piControl.cmip5.nc: blue open box-whisker in the left\r\n - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.piControl.cmip6.nc: red open box-whisker in the left\r\n - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.hist.cmip5.nc: blue filled box-whisker in the left\r\n - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries_raw in amv.hist.cmip6.nc: red filled box-whisker in the left\r\n - Standard deviation of amv_timeseries in amv.obs.nc: black horizontal lines in right\r\n . ERSSTv5: dataset = 1\r\n . HadISST: dataset = 2\r\n . COBE-SST2: dataset = 3\r\n - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.piControl.cmip5.nc: blue open box-whisker in the right\r\n - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.piControl.cmip6.nc: red open box-whisker in the right\r\n - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.hist.cmip5.nc: blue filled box-whisker in the right\r\n - Multimodel ensemble mean and percentiles of standard deviation of amv_timeseries in amv.hist.cmip6.nc: red filled box-whisker in the right\r\n \r\n Panel f:\r\n - amv_timeseries in amv.obs.nc: black curves\r\n . ERSSTv5: dataset = 1\r\n . HadISST: dataset = 2\r\n . COBE-SST2: dataset = 3\r\n - amv_timeseries in amv.hist.cmip6.nc: 5th-95th percentiles in red shading, multimodel ensemble mean and its 5-95% confidence interval for red curves\r\n - amv_timeseries in amv.hist.cmip5.nc: 5th-95th percentiles in blue shading, multimodel ensemble mean for blue curve\r\n\r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSST stands for Sea Surface Temperature.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Multimodel ensemble means and percentiles of historical simulations of CMIP5 and CMIP6 are calculated after weighting individual members with the inverse of the ensemble size of the same model. ensemble_assign in each file provides the model number to which each ensemble member belongs. This weighting does not apply to the sign agreement calculation.\r\n\r\n\r\npiControl simulations from CMIP5 and CMIP6 consist of a single member from each model, so the weighting is not applied.\r\n\r\n\r\nMultimodel ensemble means of the pattern correlation in Taylor statistics in (c) and the autocorrelation of the index in (d) are calculated via Fisher z-transformation and back transformation. \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 report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1\r\n - Link to the code for the figure, archived on Zenodo\r\n - Link to the figure on the IPCC AR6 website", "keywords": "IPCC-DDC, IPCC, AR6, WG1, WGI, Sixth Assessment Report, Working Group 1, Physical Science Basis, Atlantic Multidecadal Variability, modes of variability, CMIP5, CMIP6", "publicationState": "citable", "dataPublishedTime": "2022-06-27T10:42:28", "doiPublishedTime": "2023-02-08T19:32:03.240091", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/37533/?format=api", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig40/v20220614", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 43817985, "numberOfFiles": 8, "fileFormat": "Data are netCDF formatted" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10363/?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/46697/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46959/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46960/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46966/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52664/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52665/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60438/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63643/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63644/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63645/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63646/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63647/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63648/?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\n Data 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/12386/?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/32718/?format=api" ], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179191/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179192/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179193/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179194/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179195/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179196/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179197/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179198/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179199/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179200/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179201/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/37534/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2528/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }