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/38003/?format=api
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 38003,
    "uuid": "0ca27ce794324ec086d6a6c60d5567ac",
    "title": "Chapter 6 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 6.22 and Figure 6.24 (v20220824)",
    "abstract": "Input data for figures 6.22 and 6.24 from Chapter 6 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 6.22 shows time evolution of the effects of changes in short-lived climate forcers (SLCFs) and hydrofluorocarbons (HFCs) on global surface air temperature (GSAT) across the WGI core set of Shared Socio-economic Pathways (SSPs). \r\n\r\nFigure 6.24 shows effects of changes in short-lived climate forcers (SLCFs) and hydrofluorocarbons (HFCs) on global surface air temperature (GSAT) across the WGI core set of Shared Socio-economic Pathways (SSPs).\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\nSzopa, S., V. Naik, B. Adhikary, P. Artaxo, T. Berntsen, W.D. Collins, S. Fuzzi, L. Gallardo, A. Kiendler-Scharr, Z. Klimont, H. Liao, N. Unger, and P. Zanis, 2021: Short-Lived Climate Forcers. 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. 817–922, doi:10.1017/9781009157896.008.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\nFigure 6.22 has 1 panel, with input data provided for this panel.\r\n\r\nFigure 6.24 has 2 subpanels, with input data provided for both panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n\r\n- Effects of net aerosols, methane, tropospheric ozone and hydrofluorocarbons (HFCs; with lifetimes <50years), and the sum of these, relative to the year 2019 and to the year 1750. \r\n\r\n- The GSAT changes are based on the assessed historic and future evolution of effective radiative forcing (ERF; Section 7.3.5). The temperature responses to the ERFs are calculated with an impulse response function with an equilibrium climate sensitivity of 3.0°C for a doubling of atmospheric CO2 (feedback parameter of –1.31 W m–2 °C–1, see Cross-Chapter Box 7.1). The vertical bars to the right in each panel show the uncertainties (5–95% ranges) for the GSAT change between 2019 and 2100. \r\n\r\nFurther details on data sources and processing are available in the chapter data table (Table 6.SM.3).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figures\r\n ---------------------------------------------------\r\n Data provided in relation to figures 6.22 and 6.24:\r\n \r\n - Data file: AR6_ERF_1750-2019.csv: ERF derived from FAiR\r\n - Data file: AR6_ERF_minorGHGs_1750-2019.csv: ERF derived from FAiR\r\n - Data file: recommended_irf_from_2xCO2_2021_02_25_222758.csv: Impulse response function (IRF) from AR6\r\n\r\nThe folder SSPs (SSP scenario ERF from FAIR) contains the following file formats:\r\n\r\nERF_${scenario}$_${component}$_1750-2500.csv, with:\r\n\r\n- $(scenario): the name of the scenario : ssp119, ssp126, ssp245, ssp334, ssp370, ssp370-low-nTCF-aerchemmip, ssp370-low-nTCF-gidden, ssp434, ssp460, ssp534-over, ssp585\r\n- $(component): blank, or 'minor GHGs'\r\n\r\nThe folder slcf_warming_ranges (uncertainties in dGSAT from FAIR) contains the following file formats:\r\n\r\nslcf_warming_ranges_${scenario)_$(uncertainty).csv, with:\r\n\r\n- ${scenario}: the name of the scenario : ssp119, ssp126, ssp245, ssp334, ssp370, ssp370-lowNTCF-aerchemmip, ssp370-lowNTCF-gidden, ssp434, ssp460, ssp534-over, ssp585\r\n- ${uncertainty}: percentiles of warming: p05, p16, p50, p84, p95\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figures from the provided data\r\n ---------------------------------------------------\r\nPanels were plotted using Python and the code has been embedded in Jupyter notebooks for reproducibility - code is available in the GitHub repository linked in the documentation.\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 Figure 6.22 on the IPCC AR6 website\r\n - Link to Figure 6.24 on the IPCC AR6 website\r\n - Link to the report component containing the figures (Chapter 6)\r\n - Link to the Supplementary Material for Chapter 6, which contains details on the input data used in Table 6.SM.3\r\n - Link to the GitHub repository containing the Jupyter notebooks used to run the code associated with these figures.\r\n - Link to the code for the figures, archived on Zenodo.",
    "keywords": "IPCC-DDC, IPCC, AR6, WG1, WGI, Sixth Assessment Report, Working Group 1, Physical Science Basis, scenario warming, short-lived climate forcers, aerosol, methane, ozone, HFCs",
    "publicationState": "citable",
    "dataPublishedTime": "2023-05-10T15:13:03",
    "doiPublishedTime": "2023-07-03T14:42:39.190510",
    "updateFrequency": "",
    "status": "ongoing",
    "result_field": {
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        "dataPath": "/badc/ar6_wg1/data/ch_06/inputdata_ch6_fig22/v20220824",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 5507225,
        "numberOfFiles": 82,
        "fileFormat": "CSV, txt"
    },
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    "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).",
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