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/44159/?format=api
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 44159,
    "uuid": "8cce78e3a2814276a8680226c01a8bc6",
    "title": "British Isles weather radar gridded composite time series data, including 3D reflectivity, dual-polarisation, and derived 2D quantities (June-August 2023)",
    "abstract": "This dataset consists of 3D spatial grids of weather radar reflectivity, which have 5-minute temporal, 1km horizontal, and 500m vertical resolution. They are constructed from UK weather radar network scans, provided by 16 radars in England, Scotland, Wales, Northern Ireland, and the Channel Islands.\r\n\r\nIn addition to the 3D, there are some 2D grids of fields derived from the vertical grid columns, including maximum column dBZ and vertically integrated liquid water. Please see descriptions below.\r\n\r\nNote – this dataset contains non-operational data products, with this time-limited dataset provided primarily to aid use within the ParaChute research programme.\r\n\r\nThe interpolation method used to arrive at the multi-radar gridded values is similar to that described in Zhang (2005). The reasons for choosing this method over another more recent one (Scovell and al-Sakka, 2016) can be found in Stein et al. (2020).\r\n\r\nThe horizontal domain spans X=[-405000, 1320000], Y=[-625000, 1550000] metres on the UK National Grid (EPSG:27700) projection. This is regularly spaced, with 2175 rows x 1725 columns, and is the same as the “Nimrod” grid used by RadarNet (Harrison et al., 2009). Grid points are located at the centres of each grid box (at X/Y coordinates ending in 500). The vertical is comprised of 24 evenly spaced 500m height levels in the range h=[250,11750] metres AMSL, with the first at 250m AMSL.\r\n\r\nThe data are temporally continuous, at 5-minute resolution, from 2023-06-01 00:00 UTC to 2023-08-31 23:55 UTC. An exception being for two periods of network outage, which are 2023-06-12 17:00-19:00 UTC, and 2023-08-14 08:00-09:00 UTC.\r\n\r\nThe 3D radar grids are formed using scan data following the operational scanning strategy of the UK. This favours low elevation angles, to aid with surface quantitative precipitation estimation. Thus, at higher altitudes, coverage can be sparse (Scovell and al-Sakka, 2016) and the observations are of relatively poor quality, being at long range. No 3D grid point has a data value that has been extrapolated beyond 2.5km range horizontally. Thus, there are large data voids ~10km, at the highest altitude levels. Smaller gaps can appear at lower altitudes. At the lowest levels, and at long range from a radar site, there may sometimes be no coverage. This is unavoidable, due to the curvature of the Earth.\r\n\r\nDATASETS\r\nThe data are stored in an HDF5 file format, with the standard HDF5-native gzip compression. The stored attributes and datasets are based on, but do not strictly adhere to, the ODIM data model specification (Michelson et al., 2008). \r\nThe following ODIM quantities encoded:\r\n•\tDBZH: 3D reflectivity composite\r\n•\tZDR: 3D ZDR composite\r\n•\tRHOHV: 3D Fisher-Z (arctanh) -transformed RHOHV composite\r\n•\tMAXDBZ: 2D “column maximum” , derived from DBZH. In numpy these are computed with np.max ( reflectivity, axis = 0)\r\n•\tVIL: 2D Vertically Integrated Liquid water, as in Green and Clarke (1972) \r\n•\tTOP45, TOP18: echo top heights (highest height level) for DBZH > 45/18\r\n•\tPOH: Probability of Hail; equal to f * ( TOP45 – height of T=0C isotherm ), as in DeLobbe and Holleman (2003). \r\n•\tVII, CRIT_IND: Vertically Integrated Ice and (lightning) Criterion Index, as defined in Mosier et al. (2011), and Haklander (2014).\r\n•\tSHI, POSH, MEHS: these are hail and lightning indices derived from formulae in Witt et al. (c. 1998)\r\nThe following caveats apply to the ODIM formatting:\r\n•\tUnofficial non-compliant ODIM attributes have been added to allow storage of 3D information in the ODIM HDF5 format.\r\n•\tThe metadata describing the 3D grids are not complete.\r\n\r\nSee the online resources section for full citations used on this record.",
    "keywords": "Met Office, weather radar, 3D radar, ParaChute",
    "publicationState": "published",
    "dataPublishedTime": "2025-05-01T07:33:43",
    "doiPublishedTime": null,
    "updateFrequency": "notPlanned",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/44202/?format=api",
        "dataPath": "/badc/woest/data/mo-rain-radar/2023_JJA_3d_radar_parachute/",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 768148237713,
        "numberOfFiles": 186,
        "fileFormat": "Data are HDF5 formatted"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/12336/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/721/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75925/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75926/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75927/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75928/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75929/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75930/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75931/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75932/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75933/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75934/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75935/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75936/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75937/?format=api"
    ],
    "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [],
    "projects": [
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/5736/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/44236/?format=api"
    ],
    "observationcollection_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/43875/?format=api"
    ],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211183/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211184/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211185/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211186/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211187/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211188/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211189/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211192/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211191/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211193/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211194/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/211199/?format=api"
    ],
    "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/11595/?format=api",
    "procedureCompositeProcess": null,
    "procedureComputation": null,
    "permissions": [
        {
            "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2532/?format=api",
            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "restricted",
            "accessRoles": "ukmo_wx",
            "label": "restricted: ukmo_wx group",
            "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf",
            "licenceClassifications": "academic"
        },
        {
            "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2533/?format=api",
            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "restricted",
            "accessRoles": "ukmo_wx_gov",
            "label": "restricted: ukmo_wx_gov group",
            "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement_gov.pdf",
            "licenceClassifications": "policy"
        }
    ],
    "discoveryKeywords": []
}