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/32669/?format=api
{ "ob_id": 32669, "uuid": "7beeed0bc7fa41feb10be22ee9d10f00", "title": "Adverse Weather Scenarios for Future Electricity Systems", "abstract": "This dataset contains gridded meteorological data associated with challenging periods of weather for highly-renewable UK and European electricity systems of the future collected during the Adverse Weather Scenarios for Future Electricity Systems project. This project is a collaboration between the Met Office, the National Infrastructure Commission and the Climate Change Committee. More details about the project can be found in the associated documentation.\r\n\r\nTwo categories of challenging weather conditions; long duration adverse events and short duration wind ramping events, are provided.\r\n\r\nLong duration events\r\n\r\nThe long duration event component of the dataset provides daily time series at 60 x 60 km spatial resolution, covering a European domain, for surface temperature, 100 m wind speed and net surface solar radiation data, representative of a selection of adverse weather scenarios. Each adverse weather scenario is contained within a time slice of data. For summer-time events, one calendar year (January - December) of data is provided, with the summer-time event occurring in the summer of that year. For winter-time events, two calendar years of data are provided, with the winter-time event occurring in the winter (October-March) intersecting the two calendar years. In all cases, the start date, duration and severity of the adverse weather event, contained within the time slice of data, are given in the NetCDF global ttributes.\r\n\r\nThree types of long-duration adverse weather scenarios are represented: winter-time wind-drought-peak-demand events, summer-time wind-drought-peak-demand events, and summer-time surplus generation events. These are provided at various extreme levels (1 in 2, 5, 10, 20 ,50 and 100-year events); and for a range of current and nominal future climate change warming levels (1.2 [current day, early 2020s], 1.5, 2, 3, and 4 degrees Celsius above pre-industrial level), representative of events impacting either just the UK, or Europe as a whole.\r\n\r\nThe data provided are derived from the Met Office decadal prediction system hindcast (https://www.metoffice.gov.uk/research/approach/modelling-systems/unified-model/climate-models/depresys) according to the climate change impacts identified from UKCP18 (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index).\r\n\r\nShort duration events\r\nThe short duration event component of the dataset provides hourly time series at 4 x 4 km spatial resolution, covering a UK and surrounding offshore area domain, for 100 m wind speed, representative of a selection of wind generation ramping events. Each adverse weather scenario is contained within a time slice of data with up to one week before and one week after the day on which the event occurs (up to 15 days in total) provided. For the majority of events provided, the full 15 days are available, however for a small number of events which occur less than one week from the beginning or end of the underlying data used to derive this dataset, this is not possibly to supply, and these events are listed below. The start date and time along with the direction and magnitude of the ramp (change in wind capacity factor) contained\r\nwithin the time slice of data, are given in the NetCDF global attributes.\r\n\r\nThe short duration wind generation ramping events are representative of events impacting five separate regions of Great Britain and surrounding offshore areas, as defined in the accompanying documentation. These regions are Scotland, the East England, West England and Wales offshore North and offshore South. The events are defined by changes in wind capacity factors occurring over different length time windows (1-hour, 3-hour, 6-hour, 12-hour and 24-hour windows). These are provided at various extreme levels (1 in 2, 5, 10, 20 ,50 and 100-year events) for the 1.2 degrees Celsius above pre-industrial level (I.e. representative of early 2020s climate) and through the analysis outlined in the accompanying documentation are though to also be representative of the 2, 3, and 4 degrees Celsius above pre-industrial level nominal future climate change warming levels.\r\n\r\nThe data provided are derived from the UKCP18 local projections (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index).\r\n\r\nThe methods developed for characterising and representing these adverse weather scenarios, and the approach used to compile the final dataset are presented in the accompanying documentation.\r\n\r\nUse of this data is subject to the terms of the Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/) The following acknowledgment must be given when using the data: © Crown Copyright 2021, Met Office, funded by the National Infrastructure Commission.", "keywords": "Adverse weather scenarios, future electricity systems, adverse weather scenarios for future electricity systems, UK, Europe, weather risk, climate risk, energy system, extreme weather scenarios, electricity system resilience, climate change", "publicationState": "published", "dataPublishedTime": "2021-06-03T14:48:03", "doiPublishedTime": null, "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32670/?format=api", "dataPath": "/badc/deposited2021/adverse_met_scenarios_electricity/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 689690747173, "numberOfFiles": 2624, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8976/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2794/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/2007/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/2008/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6811/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11573/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21675/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21676/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21677/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/21678/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46793/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46794/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46795/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/46796/?format=api" ], "dataLineage": "This dataset has been developed by the Met Office as part of the 'Adverse Weather Scenarios for Future Electricity Systems' project, commissioned by the National Infrastructure Commission, and co-lead by the Climate Change Committee.\r\n\r\nThe data provided are derived from the Met Office decadal prediction system hindcast and UKCP18, according to the climate change impacts identified from UKCP18. Further information about the development of this dataset are presented in the accompanying reports. The data has been sent by the data providers to be archived at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/32671/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145687/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145688/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145689/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145690/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145691/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145692/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145697/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145698/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145699/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145700/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145701/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145702/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32672/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": "any" } ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }