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/39500/?format=api
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "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": []
}