Observation Instance – Django REST framework

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/39666/?format=api

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 39666,
    "uuid": "31a23a7fbb2c40828e8af2fd479b683e",
    "title": "Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): Met Office Unified Model data and associated Cloudnet outputs (UM_RA2M_Cloudnet)",
    "abstract": "Met Office Unified Model single-site (Oden) output during MOCCHA. These model and observation data are used in McCusker et al.: Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System, Atmospheric Chemistry and Physics, 2023. \r\n\r\n Model data from the Met Office Unified Model are in directory 'um_model_data/'. Data are hourly data taken from grid box closest to ship location. Where the ship covers more than one grid box within an hour period, data are averaged from all grid boxes crossed. All data files are in a netCDF format, with one file per day. Rose suite ID: u-cc568. Model options include: \r\n Cloud microphysics: Smith (1990) but includes a cloud/precipitation microphysical scheme with prognostic ice (Wilson and Ballard, 1999), based on Rutledge and Hobbs (1983). \r\n Extended boundary layer diagnostic list. \r\n Updated revision of suite u-bg610. \r\n U and V wind components interpolated on to common vertical grid. \r\n\r\n Model data from um_model_data/ are subsequently passed through the Cloudnet algorithm to produce calibrated model data that may be used for direct comparisons with observations. Cloudnet combines cloud radar, ceilometer, microwave radiometer, and radiosonde profiles averaged to a common grid at the cloud radar resolution to derive a set of retrieved cloud properties. The Cloudnet products are designed to be used for evaluation of weather forecast models as well as fundamental process studies of cloud. From a modelling perspective, Cloudnet converts liquid and ice mass mixing ratios to the respective cloud water contents for direct comparison with observations, as well as filtering ice water contents for values that would be unobservable by radar. Note that the latitude/longitude relevant for each date in question can be found in these Cloudnet files. \r\nIn directories:\r\n iwc-Z-T-metum-grid/ - data include ice water content and total ice water path for observations and model. \r\n lwc-scaled-metum-grid/ - data include cloud liquid water content and liquid water path for observations and model. \r\n cloud-fraction-metum-grid/ - data include cloud fractions by volume for observations and model.",
    "keywords": "MOCCHA, Met Office, Unified Model, Cloudnet, Oden, cloud microphysics, aerosol",
    "publicationState": "citable",
    "dataPublishedTime": "2023-03-07T11:42:24",
    "doiPublishedTime": "2023-03-07T12:01:08.094405",
    "updateFrequency": "notPlanned",
    "status": "ongoing",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39667/?format=api",
        "dataPath": "/badc/deposited2023/moccha_UM_RA2M_Cloudnet",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 21803802,
        "numberOfFiles": 126,
        "fileFormat": "Data are netCDF formatted"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10985/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3757/?format=api",
    "nonGeographicFlag": false,
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    ],
    "dataLineage": "Model data were generated using the Met Office Unified Model (UM) at 1.5km horizontal resolution over a 500x500 domain centred on 86.625N, 30E. Data has been converted to netCDF by Gillian Young McCusker (G.Y.McCusker@leeds.ac.uk) using Python (Iris/netCDF4), then passed on to the CEDA for long-term archiving. Cloudnet data were generated by Jutta Vuellers (j.vuellers@leeds.ac.uk)",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12415/?format=api"
    ],
    "projects": [
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/29975/?format=api"
    ],
    "observationcollection_set": [
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    ],
    "responsiblepartyinfo_set": [
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    ],
    "procedureAcquisition": null,
    "procedureCompositeProcess": null,
    "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/39669/?format=api",
    "permissions": [
        {
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            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "public",
            "accessRoles": null,
            "label": "public: None group",
            "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf",
            "licenceClassifications": "unstated"
        }
    ],
    "discoveryKeywords": []
}