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/37906/?format=api
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 37906,
    "uuid": "3069833ab06a4968a90fa9f649b87ed7",
    "title": "Chapter 7 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 7.7 (v20220721)",
    "abstract": "Input Data for Figure 7.7 from Chapter 7 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 7.7 shows the contribution of forcing agents to 2019 temperature change relative to 1750 produced using the two-layer emulator (Supplementary Material 7.SM.2), constrained to assessed ranges for key climate metrics described in Cross-Chapter Box 7.1.\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\nForster, P., T. Storelvmo, K. Armour, W. Collins, J.-L. Dufresne, D. Frame, D.J. Lunt, T. Mauritsen, M.D. Palmer, M. Watanabe, M. Wild, and H. Zhang, 2021: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity. 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. 923–1054, doi:10.1017/9781009157896.009.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 1 panel, with data provided for this panel in the master GitHub repository linked in the documentation.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Contribution of forcing agents to 2019 temperature change relative to 1750 produced using the two-layer emulator (Supplementary Material 7.SM.2), constrained to assessed ranges for key climate metrics described in Cross-Chapter Box 7.1. The forcing agents represented are the following:\r\n  - carbon dioxide\r\n  - other well-mixed greenhouse gases (WMGHGs)\r\n  - ozone\r\n  - stratospheric water vapour\r\n  - surface albedo\r\n  - contrails and aviation-induced cirrus\r\n  - aerosols\r\n  - solar\r\n  - volcanic\r\n  - total\r\n\r\nThe results are from a 2237-member ensemble. \r\nSolid bars represent best estimates, and very likely (5–95%) ranges are given by error bars. Dashed error bars show the contribution of forcing uncertainty alone, using best estimates of ECS (3.0°C), TCR (1.8°C) and two-layer model parameters representing the CMIP6 multi-model mean. \r\nSolid error bars show the combined effects of forcing and climate response uncertainty using the distribution of ECS and TCR from Tables 7.13 and 7.14, and the distribution of calibrated model parameters from 44 CMIP6 models. \r\nNon-CO2 WMGHGs are further broken down into contributions from methane (CH4), nitrous oxide (N2O) and halogenated compounds. \r\nSurface albedo is broken down into land-use changes and light-absorbing particles on snow and ice. \r\nAerosols are broken down into contributions from aerosol–cloud interactions (ERFaci) and aerosol–radiation interactions (ERFari). \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 7.SM.14).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 7.7:\r\n \r\n - Data file: AR6 FGD assessment time series - GMST and GSAT.xlsx\r\n\r\nECS stands for Equilibrium Climate Sensitivity.\r\nTCR stands for Transient Climate Response.\r\nERFaci stands for Effective Radiative Forcing of aerosol-cloud interaction.\r\nERFari stands for Effective Radiative Forcing of aerosol-radiation interaction.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nData and figures are produced by the Jupyter Notebooks that live inside the notebooks directory. Also listed on the 'master' GitHub page linked in the documentation of this catalogue record are external GitHub repositories and locations within the contributed directory where code for figures have been supplied by other authors. These are provided \"as-is\" and are not guaranteed to be reproducible within this environment. For external GitHub locations, check out the relevant repository READMEs.\r\n\r\nWithin the processing chain, every notebook is prefixed by a number. To reproduce all results in the chapter, the notebooks should be run in numerical order, because some later things depend on earlier things (historical temperature attribution requires a constrained ensemble of the two layer climate model, which relies on the generation of the radiative forcing time series). This being said, most notebooks should run standalone, as input data is provided where the datasets are small enough (see the 'master;' GitHub page for these).\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 7)\r\n - Link to the Supplementary Material for Chapter 7, which contains details on the input data used in Table 7.SM.1 to 7.SM.7.\r\n- Link to the code for the figure, archived on Zenodo.",
    "keywords": "IPCC-DDC, IPCC, AR6, WG1, WGI, Sixth Assessment Report, Working Group 1, Physical Science Basis, temperature, anthropogenic, natural, greenhouse gases, aerosols",
    "publicationState": "working",
    "dataPublishedTime": null,
    "doiPublishedTime": null,
    "updateFrequency": "",
    "status": "ongoing",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/38062/?format=api",
        "dataPath": "/badc/ar6_wg1/data/ch_07/inputdata_ch7_fig07/v20220721",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 304000,
        "numberOfFiles": 2,
        "fileFormat": "XLSX, txt"
    },
    "timePeriod": null,
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [],
    "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": [],
    "projects": [
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/32705/?format=api"
    ],
    "observationcollection_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/32722/?format=api"
    ],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180980/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180981/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180982/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180983/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180984/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180985/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180986/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/180987/?format=api"
    ],
    "procedureAcquisition": null,
    "procedureCompositeProcess": null,
    "procedureComputation": null,
    "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": []
}