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/?format=api&offset=5400
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "count": 10256,
    "next": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=5500",
    "previous": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=5300",
    "results": [
        {
            "ob_id": 26283,
            "uuid": "e8b02bf5b0324ca09c4993b3923e9135",
            "title": "Met Office LIDARNET Loftus Raymetrics LR111-D300 lidar profile data",
            "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at Loftus, North Yorkshire. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives.",
            "keywords": "Met Office, lidar, ash, Raman, backscatter profiles",
            "publicationState": "published",
            "dataPublishedTime": "2019-02-19T10:27:36",
            "doiPublishedTime": null,
            "updateFrequency": "asNeeded",
            "status": "ongoing",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/26265/?format=api",
                "dataPath": "/badc/ukmo-lidarnet/data/loftus/raymetrics-lr111-d300/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 7067620602,
                "numberOfFiles": 14662,
                "fileFormat": "Data are netCDF formatted."
            },
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            "nonGeographicFlag": false,
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/9769/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/9770/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/9773/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/9778/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11526/?format=api",
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                    "label": "restricted: ukmo_wx group",
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                    "licenceClassifications": "academic"
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                    "label": "restricted: ukmo_wx_gov group",
                    "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement_gov.pdf",
                    "licenceClassifications": "policy"
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            ],
            "discoveryKeywords": [
                {
                    "ob_id": 1138,
                    "name": "NDGO0003"
                }
            ]
        },
        {
            "ob_id": 26284,
            "uuid": "17e18421f0304ee3b02a96abf344ebe9",
            "title": "Met Office LIDARNET Portglenone Raymetrics LR111-D300 lidar profile data",
            "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at the Met Office observations enclosure near Portglenone, County Antrim, Northern Ireland. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives.",
            "keywords": "Met Office, lidar, ash, Raman, backscatter profiles",
            "publicationState": "published",
            "dataPublishedTime": "2019-02-19T10:27:46",
            "doiPublishedTime": null,
            "updateFrequency": "asNeeded",
            "status": "ongoing",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/26288/?format=api",
                "dataPath": "/badc/ukmo-lidarnet/data/portglenone/raymetrics-lr111-d300/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 5478403861,
                "numberOfFiles": 11364,
                "fileFormat": "Data are NetCDF formatted."
            },
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        {
            "ob_id": 26285,
            "uuid": "a2e00ed1f3724db2b5ff24f17adf3811",
            "title": "Met Office LIDARNET Rhyl Raymetrics LR111-D300 lidar profile data",
            "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at a Met Office instrument enclosure near Rhyl, Denbighshire, on the North Welsh coast. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives.",
            "keywords": "Met Office, lidar, ash, Raman, backscatter profiles",
            "publicationState": "published",
            "dataPublishedTime": "2019-02-19T10:26:15",
            "doiPublishedTime": null,
            "updateFrequency": "asNeeded",
            "status": "ongoing",
            "result_field": {
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 6313070292,
                "numberOfFiles": 13547,
                "fileFormat": "Data are netCDF formatted."
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        {
            "ob_id": 26290,
            "uuid": "130637c33a27475093552bf76c088150",
            "title": "FAAM C106 ACSIS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The North Atlantic Climate System Integrated Study: ACSIS project.",
            "keywords": "ACSIS, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "dataPublishedTime": "2018-06-21T10:35:18.113581",
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            "status": "ongoing",
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                "volume": 530609607,
                "numberOfFiles": 29,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
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        {
            "ob_id": 26431,
            "uuid": "cfe46deca7324763b8989adaa2607f20",
            "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 2 Preprocessed (L2P) Climate Data Record, version 2.0",
            "abstract": "This v2.0 SST_cci Along-Track Scanning Radiometer (ATSR) Level 2 Preprocessed (L2P) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the ATSR series of satellite instruments.  It covers the period between 11/1991 - 04/2012.  This L2P product provides these SST data on the original satellite swath with a single orbit of data per file.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project (ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .",
            "keywords": "SST. CCI",
            "publicationState": "citable",
            "dataPublishedTime": "2019-08-02T22:00:26",
            "doiPublishedTime": "2019-08-22T12:24:15",
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                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/26432/?format=api",
                "dataPath": "/neodc/esacci/sst/data/CDR_v2/ATSR/L2P/v2.0",
                "oldDataPath": [],
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/7135/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52529/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52531/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52535/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52536/?format=api",
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            "dataLineage": "Data were processed by the ESA CCI SST project team and supplied to the Centre for Environmental Data Analysis (CEDA) for archiving in the context of the ESA CCI Open Data Portal project and the National Centre for Earth Observation (NCEO).",
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            "ob_id": 26433,
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            "title": "ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Grid product, version 5.1",
            "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The MODIS Fire_cci v5.1 grid product described here contains gridded data on global burned area derived from the MODIS instrument onboard the TERRA satellite at 250m resolution for the period 2001 to 2019.  This product supercedes the previously available MODIS v5.0 product. The v5.1 dataset was initially published for 2001-2017, and has later been periodically extended to include 2018 to 2022. \r\n\r\nThis gridded dataset has been derived from the MODIS Fire_cci v5.1 pixel product (also available) by summarising its burned area information into a regular grid covering the Earth at 0.25 x 0.25 degrees resolution and at monthly temporal resolution.   Information on burned area is included in 23 individual quantities: sum of burned area, standard error, fraction of burnable area, fraction of observed area, number of patches and the burned area for 18 land cover classes, as defined by the Land_Cover_cci v2.0.7  product. For further information on the product and its format see the Fire_cci product user guide in the linked documentation.",
            "keywords": "ESA, CCI, GRID, Burned Area, Fire Disturbance, Climate Change, GCOS Essential Climate Variable",
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            "uuid": "58f00d8814064b79a0c49662ad3af537",
            "title": "ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Pixel product, version 5.1",
            "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. These MODIS Fire_cci v5.1 pixel products are distributed as 6 continental tiles and are based upon data from the MODIS instrument onboard the TERRA satellite at 250m resolution for the period 2001-2020.  This product supersedes the previously available MODIS v5.0 product. The v5.1 dataset was initially published for 2001-2017, and has later been periodically extended to include 2018 to 2022.\r\n\r\nThe Fire_cci v5.1 Pixel product described here includes maps at 0.00224573-degrees (approx. 250m) resolution. Burned area(BA) information includes 3 individual files, packed in a compressed tar.gz file: date of BA detection (labelled JD), the confidence level (CL, a probability value estimating the confidence that a pixel is actually burned), and the land cover (LC) information as defined in the Land_Cover_cci v2.0.7 product.\r\n\r\nFiles are in GeoTIFF format using a geographic coordinate system based on the World Geodetic System (WGS84) reference ellipsoid and using Plate Carrée projection with geographical coordinates of equal pixel size. For further information on the product and its format see the Fire_cci Product User Guide in the linked documentation.",
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            "dataPublishedTime": "2018-11-01T13:24:27",
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 60713675075,
                "numberOfFiles": 1680,
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            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9185/?format=api",
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            "nonGeographicFlag": false,
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            "dataLineage": "Data was produced by the ESA Fire CCI team as part of the ESA Climate Change Initiative (CCI) and is being held on the CEDA (Centre for Environmental Data Analysis) archive as part of the ESA CCI Open Data Portal project.",
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            "title": "Global mean annual reconstructed surface temperature anomaly time series for merged land, air and sea-surface",
            "abstract": "This dataset contains global mean annual reconstructed surface temperature anomaly time series for merged land, air and sea-surface. This dataset was produced in 2004 for the period: 1880-2009. The reconstruction is separated into separate low and high-frequency components, which are added for the total reconstruction.  To create the global mean the Northern and Southern Hemisphere averages are computed separately and then they are then averaged together (to stop the better sampled Northern Hemisphere from dominating the Global average). This dataset improved analysis and error estimation methods to analyze both sea surface temperature and land surface temperature anomalies, and to then merge them to form a global analysis.",
            "keywords": "IPCC DDC, temperature, land, sea, air",
            "publicationState": "working",
            "dataPublishedTime": null,
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            "phenomena": [],
            "dataLineage": "These data was delivered to the International Panel for Climate Change Data distribution Centre (IPCC DDC) for archiving.",
            "removedDataTime": null,
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            "language": "English",
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        {
            "ob_id": 26437,
            "uuid": "a39add95a8dc49709f6e984c020c8dbc",
            "title": "MIDAS Open: UK daily temperature data, v201901",
            "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2017. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection.",
            "keywords": "Met Office, MIDAS, UK, meteorology, temperature, diurnal, daily, monthly",
            "publicationState": "citable",
            "dataPublishedTime": "2019-02-12T10:50:04",
            "doiPublishedTime": "2019-03-01T08:04:52",
            "updateFrequency": "notPlanned",
            "status": "superseded",
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                "dataPath": "/badc/ukmo-midas-open/data/uk-daily-temperature-obs/dataset-version-201901/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2005442647,
                "numberOfFiles": 59586,
                "fileFormat": "Data are BADC-CSV formatted."
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        {
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            "title": "Sentinel 5P: Carbon Monoxide (CO) Total Column level 2 data",
            "abstract": "Sentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). TROPOMI on the Sentinel 5 Precursor (S5P) satellite observes the CO global abundance exploiting clear-sky and cloudy-sky Earth radiance measurements in the 2.3 µm spectral range of the shortwave infrared (SWIR) part of the solar spectrum. TROPOMI clear sky observations provide CO total columns with sensitivity to the tropospheric boundary layer. For cloudy atmospheres, the column sensitivity changes according to the light path. Carbon monoxide (CO) is an important atmospheric trace gas for our understanding of tropospheric chemistry. In certain urban areas, it is a major atmospheric pollutant. The main sources of CO are the combustion of fossil fuels, biomass burning, and atmospheric oxidation of methane and other hydrocarbons. Whereas fossil fuel combustion is the main source of CO at Northern mid-latitudes, the oxidation of isoprene and biomass burning play an important role in the tropics.",
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            "abstract": "This dataset contains upper air sounding profiles of temperature, pressure, humidity, wind speed and wind direction measurements from the NCAS Vaisala Sounding Station unit 2 radiosonde lauches. The radiosondes were launched over Greenland and Iceland from the Alliance research ship for the Iceland Greenland seas Project (IGP). \r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)",
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            "title": "EUSTACE:  Coincident daily air temperature estimates and reference measurements, for validation, 1850-2015, v1.0",
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            "title": "Sentinel 5P: TROPOspheric Monitoring Instrument (TROPOMI) level 1b Irradiance product UVN module data.",
            "abstract": "This dataset contains level 1B data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the European Space Agency (ESA) Sentinel 5P satellite. Sentinel 5P was launched on 13th October 2017. This satellite aims to provide atmospheric measurements relating to air quality, climate forcing, ozone and ultraviolet radiation. This data looks to build on the data from GOME, SCIAMACHY and OMI missions. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user.",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111481/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111485/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/168833/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111483/?format=api"
            ],
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                {
                    "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2522/?format=api",
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        {
            "ob_id": 26543,
            "uuid": "bdf2cf5a78554a73bf5e57a853e3bbc0",
            "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Grounding Line Locations for the Ferringo, Pine Island, Thwaites, Smith, Kohler and Pope Glaciers, Antarctica, 1995-2017, v2.0  (CCI subset)",
            "abstract": "Grounding line locations (GLL) data for the Ferringo, Pine Island, Thwaites, Smith, Kohler and Pope Glaciers in Antarctica, produced by the ESA Antarctic Ice Sheet Climate Change Initiative (CCI) project. The grounding lines  have been derived from satellite observations from the ERS-1/2 and Copernicus Sentinel-1 instruments, acquired in the period from 1995-2017.\r\n\r\nAn extended dataset of Grounding line locations for these Glaciers is available on the ENVEO CryoPortal (http://cryoportal.enveo.at/data/)",
            "keywords": "Antarctica, ice sheets, glaciers, grounding line location",
            "publicationState": "published",
            "dataPublishedTime": "2017-04-27T23:00:00",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "superseded",
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                "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/grounding_line_locations/Ferrigno_PineIS_Thwaites_Smith_Pope_Kohler/v2.0_cci_subset/",
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                "storageStatus": "online",
                "volume": 192023,
                "numberOfFiles": 8,
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            "phenomena": [],
            "dataLineage": "Data were produced by DLR in the context of the ESA CCI Antarctic Ice Sheet project team and are archived on the ENVEO Cryoportal (http://cryoportal.enveo.at/data/)  They have been supplied to CEDA in the context of the ESA CCI Open Data Portal Project.\r\n\r\nAn extended dataset is available on the ENVEO Cryoportal (http://cryoportal.enveo.at/data/)",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
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                "https://api.catalogue.ceda.ac.uk/api/v2/projects/24700/?format=api"
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                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/24699/?format=api"
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111538/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111532/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111533/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111534/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111535/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111536/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111537/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111539/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111540/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111531/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111541/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111542/?format=api"
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                    "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_icesheets_antarctic_terms_and_conditions.pdf",
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        {
            "ob_id": 26547,
            "uuid": "858a4b439d7d4466b82ea5215614f135",
            "title": "Freezing temperature laboratory experiments of individual droplets each contained in a well plate using InfraRed-Nucleation by Immersed Particles Instrument (IR-NIPI)",
            "abstract": "This dataset contains freezing temperature laboratory measurements of individual droplets each contained in a well of a 96-well plate using InfraRed-Nucleation by Immersed Particles Instrument (IR-NIPI) instrument. IR-NIPI makes use of InfraRed (IR) emissions to determine the freezing temperature of individual 50μL droplets each contained in a well of a 96-well plate. Using an IR camera allows the temperature of individual aliquots to be monitored. Freezing temperatures are determined by detecting the sharp rise in well temperature associated with the release of heat caused by freezing.",
            "keywords": "Infrared, Freezing temperatures, IR-NIPI",
            "publicationState": "citable",
            "dataPublishedTime": "2018-09-19T14:22:30",
            "doiPublishedTime": "2018-09-21T09:34:24",
            "updateFrequency": "",
            "status": "completed",
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                "storageStatus": "online",
                "volume": 77266,
                "numberOfFiles": 9,
                "fileFormat": "Data are BADC-CSV formatted"
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111546/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/168836/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111554/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111555/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111556/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111557/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111558/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111559/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111560/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111562/?format=api"
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        {
            "ob_id": 26556,
            "uuid": "3ecd1690bab2432db4ecb1de08388cfe",
            "title": "CURBCO2: Coupled Physical-biogeochemical ocean NEMO-HadOCC simulation output forced by CanESM2 atmosphere",
            "abstract": "This dataset contains coupled physical-biogeochemical ocean second generation Canadian Earth System Model (CanESM2) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes.\r\n\r\nJob IDs included in this dataset:\r\n    CanESM2 surface fluxes (started on 18th for first, 21st for second, and on the 19th for other 2):\r\n    RCP85: u-ao419\r\n    RCP26: u-ao519\r\n    Constant atm CO2:\r\n    RCP85: u-ao529\r\n    RCP26: u-ao531  (reduce walltime for nemo to test)\r\n\r\nThis data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015.",
            "keywords": "CURB, CO2, Oceans, alkalinity, temperature, salinity",
            "publicationState": "published",
            "dataPublishedTime": "2019-01-21T14:31:59",
            "doiPublishedTime": null,
            "updateFrequency": "",
            "status": "completed",
            "result_field": {
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                "dataPath": "/badc/deposited2018/curb/data/CanESM2/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 153631250152,
                "numberOfFiles": 406,
                "fileFormat": "Data are netCDF formatted"
            },
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            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50624/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63050/?format=api"
            ],
            "dataLineage": "Simulations were undertaken with the NEMO-HadOCC model ocean at 1 degree with HadOCC biogeochemistry and delivered to the Centre for Environmental Analysis (CEDA) for archiving.",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111589/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111590/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111586/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/168840/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111591/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111592/?format=api"
            ],
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                    "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2522/?format=api",
                    "useLimitation": null,
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                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
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        },
        {
            "ob_id": 26559,
            "uuid": "de6591c3d5d44b08b4d954410f353c6e",
            "title": "A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years",
            "abstract": "We present a continuous land climate reconstruction dataset extending from 60 kyr before present to the pre-industrial period at 0.5deg resolution on a monthly timestep for 0degN to 90degN. It has been generated from 42 discrete snapshot simulations using the HadCM3B-M2.1 coupled general circulation model. We incorporate Dansgaard-Oeschger (DO) and Heinrich events to represent millennial scale variability, based on a temperature reconstruction from Greenland ice-cores, with a spatial fingerprint based\r\n on a freshwater hosing simulation with HadCM3B-M2.1. Interannual variability is also added and derived from the initial snapshot simulations. Model output has been downscaled to 0.5deg resolution (using simple bilinear interpolation) and bias corrected using either the University of East Anglia, Climate Research Unit observational data (for temperature, precipitation, windchill, and minimum monthly temperature), or the EWEMBI dataset (for incoming shortwave energy). Here we provide datasets for; surface air temperature, precipitation, incoming shortwave energy, wind-chill, snow depth (as snow water equivalent), number of rainy days per month,  minimum monthly temperature, and the land-sea mask and ice fractions used in the simulations. The datasets are in the form of NetCDF files. The variables are represented by a set of 24 files that have been compressed into nine folders: temp, precip, down_sw, wind_chill, snow, rainy_days, tempmonmin, landmask and icefrac. Each file represents 2500 years. The landmask and ice fraction are provided annually, whereas the climate variables are given as monthly files equivalent to 30000 months, between the latitudes 0deg to 90degN at 0.5deg resolution. Each of the climate files therefore have the dimensions 180 (lat) x 720 (lon) x 30000 (month). We also provide an example subset of the temperature dataset, which gives decadal averages for each month for 0-2500 years.",
            "keywords": "Climate, Model, HadCM3B, air temperature, precipitation",
            "publicationState": "citable",
            "dataPublishedTime": "2019-09-20T09:04:41",
            "doiPublishedTime": "2019-10-25T07:52:09.713004",
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            "abstract": "This dataset contains concentration measurements of atmospheric species performed at the Weybourne Atmospheric Observatory (WAO) on the North Norfolk coast. Measurements were all performed at ground level. Data was collected from 30th June till the 31st July 2015. This data was collected as part of Integrated Chemistry of Ozone in the Atmosphere (ICOZA) project, which aimed to apply in situ measurements to examine the response of the local atmospheric ozone production rate to NOx and VOC levels. The following instruments measured these species: LOPAP – Nitrous Acid (HONO) FAGE – OH, HO2, total organic RO2 Trace gases - NO, NO2, NOy, O3, SO2 and CO Gas chromatography (GC) - volatile organic compounds The measurements and data processing were performed by researchers from the Universities of Birmingham, East Anglia, Leeds and York. In-situ measurements of the ozone production rate are still in progress.",
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            "abstract": "This dataset contains coupled physical-biogeochemical ocean second generation Geophysical Fluid Dynamics Laboratory (GFDL-ESM2M) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes.\r\n\r\n  Job IDs included in this dataset are:\r\n    GFDL-ESM2M surface fluxes (started on 19th July ~14h):\r\n    RCP85: u-ao541  (copy from u-ao419, change model names, restart + reduce walltime for nemo to test )\r\n    RCP26: u-ao551  (copy from u-ao541 and change rcp26 surface fluxes)\r\n    Constant atm CO2:\r\n    RCP85: u-ao552  (copy from u-ao541 with cst atm changes)\r\n    RCP26: u-ao554 (copy from u-ao551 with cst atm changes)\r\n\r\nThis data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015.",
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            "abstract": "This dataset contains coupled physical-biogeochemical ocean second generation Met Office (HadGEM2-ES) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes.\r\n\r\n  Job IDs included in this dataset are:\r\n    HadGEM2-ES surface fluxes (2099 for rcp85 not resolved yet) (runs started on 26th July)\r\n    RCP85: u-ao789  (nov 2099)(copy from u-ao559,change model name, restart path, and surface fluxes files)\r\n    RCP26: u-ao790  (nov 2099) (copy from u-ao789,change rcp26 surface fluxes)\r\n    Constant atm CO2\r\n    RCP85: u-ao791  (nov 2099) (copy from u-ao789 with cst atm changes)\r\n    RCP26: u-ao793  (nov 2099) copy from u-ao790 with cst atm changes)\r\n\r\nThis data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015.",
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            "title": "CURBCO2: Coupled Physical-biogeochemical ocean NEMO-HadOCC simulation output forced by IPSL-CM5A-LR atmosphere",
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            "title": "20 and 30 year climatologies from CMIP3 climate model output as used in the 2007 IPCC Fourth Assessment Report (AR4)",
            "abstract": "Climatology data used in Climate Change 2007, the Fourth Assessment Report (AR4) of the United Nations Intergovernmental Panel on Climate Change (IPCC) calculated from Coupled Model Intercomparison Project Phase 3 (CMIP3) model output.\r\n\r\nSimulations of global climate models were run by various climate modelling groups coordinated by the World Climate Research Programme (WCRP) on behalf of the IPCC.\r\n\r\nClimatology data was calculated from global climate model simulations of experiments representative of Special Report on Emission Scenarios (SRES) scenarios: A1b, A2, B1, the commitment scenario experiment (COMMIT),  the twentieth century experiment (20C3M), the pre-industrial control (PICTL) and the idealised experiments 1PCTO2X and 1PCTO4X.\r\n\r\nThe AR4 climatologies are 20-year period averages. 30-year period averages have also been calculated for comparison with the IPCC Third Assessment Report (TAR).  The monthly climatology data covers the period from 1850-2100. The climatologies are of global scope and are provided on latitude-longitude grids.\r\n\r\nThe period averages are:\r\n20x: 20-year averages [+20-39, +46-65, +80-99, +180-199] as used in chapter 10 of IPCC 2007, \r\n30a: 30-year averages [+01-30, +31-60, +61-90] as used in the observed climatologies, \r\n30b: 30-year averages [+10-39, +40-69, +70-99] for compatibility with the IPCC 3rd Assessment Report (TAR).\r\n\r\nThe climatology period averages listed above are relative to AD2000 for SRES scenarios A1B, A2, B1, and the commitment scenario COMMIT, relative to AD1900 for the twentieth century run (20C3M) and relative to the start of the experiment for the pre-industrial control (PICTL) and the 1PCTO2X and 1PCTO4X runs.  \r\n\r\nData files are 'tar' files with names of the form [model]_[experiment]_[variable]_{climatology}.tar.  \r\n\r\nThe experiments in this dataset include the SRES future scenarios: \r\nA1B Globalisation with rapid economic growth, \r\nA2 Regionalisation with regionally oriented economic development, \r\nB1 Globalisation with global environmental sustainability.\r\nAlso:\r\nCOMMIT simulation of climate change we are committed to given the current loading of greenhouse gasses and zero future emissions. \r\nPICTL the pre-industrial control. \r\n20C3M the 20th century climate simulaiton. \r\n1PTO2X and 1PTO4X idealised simulaitons where the concentration of atmospheric carbon dioxide (CO2) is increased by 1 percent per year from pre-industrial concentration until reaching 2x and 4x the original concentration.\r\n\r\nThe dataset is comprised of monthly mean surface data for the following atmospheric variables: \r\nspecific humidity, \r\nprecipitation flux, \r\nair pressure at sea level, \r\nsurface downwelling shortwave flux in air, \r\nair temperature, \r\nair temperature daily max, \r\nair temperature daily min, \r\neastward wind, \r\nnorthward wind.",
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            "title": "30 year climatologies from model output as used in the 2001 IPCC Third Assessment Report (TAR)",
            "abstract": "Data used in Climate Change 2001, the Third Assessment Report (TAR) of the United Nations Intergovernmental Panel on Climate Change (IPCC).\r\n\r\nSimulations of global climate models were run by various climate modelling groups coordinated by the World Climate Research Programme (WCRP) on behalf of the United Nations Intergovernmental Panel on Climate Change (IPCC).\r\nClimatology data calculated from global climate model simulations of experiments representative of Special Report on Emission Scenarios (SRES) scenarios: A1F, A1T, A1a, A2a, A2b, A2c, B1a, B2b.\r\nThe climatologies are 30-year averages. Climate anomalies are expressed relative to the period 1961-1990. The monthly climatology data covers the period from 1961-2100. The climatologies are of global scope and are provided on latitude-longitude grids.",
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            "dataLineage": "Climatology data calculated from global climate model simulations for SRES experiments A1F, A1T, A1a, A2a, A2b, A2c, B1a, B2b.\r\nThe climatologies are 30-year averages. Climate anomalies are expressed relative to the period 1961-1990. \r\n\r\nThe Models.\r\nCCCma: The atmospheric component AGCM2 is a spectral model with triangular truncation at wave no. 32 and 10 vertical levels. The ocean model component based on the GFDL MOM 1.1 code with 29 vertical levels and has a isopycnal / eddy stirring parameterization. \r\nCSIRO:  The Mark 2 CSIRO coupled global climate model consists of the atmospheric component which has 9 vertical levels with a R21 horizontal resolution and the ocean component which was based on the GFDL code. \r\nECHAM4: The model consists of the atmospheric component which based on the weather forecast model of ECMWF. The atmosphere component is the standard model version of a 19-level hybrid sigma-pressure coordinate system. The ocean component is a model which computes with isopycnal coordinates.\r\nGFDL: The atmospheric component solves the primitive equations using a spectral transform method, GFDL_R30 means a rhomboidal 30 truncation and the ocean component solves the primitive equation of motion using the Boussinesq, rigid-lid and hydrostatic approximation and based on GFDL Modular Ocean Model version 1.\r\nHadCM3: The Hadley Centre Circulation Model is a 3-dim AOGCM. The atmospheric component has a 19 levels, the horizontal resolution is comparable with a spectral resolution of T42, while the ocean component has a 20 levels resolution. \r\nNIES:  The model developed by the Center for Climate System Resaerch/ National Institute for Enviromental Studies in Tokyo consists of the atmospheric component which has vertical resolution of 20 levels and the triangular truncation at wavenumber 21 (T21). The ocean model has 17 vertical levels and the same resolution. .\r\n\r\nThe SRES Experiments.\r\nA1B Globalisation with rapid economic growth and a balanced emphasis on all energy sources. \r\nA1T Globalisation with rapid economic growth and an emphasis on non-fossil energy sources. \r\nA1FI Globalisation with rapid economic growth and an emphasis on fossil fuels (Fossil Intensive). \r\nA2 Regionalisation with regionally oriented economic development. A2a, A2b and A2c follow the same experiment design and historic and future forcings but start from different initial conditions.\r\nB1 Globalisation with global environmental sustainability.  \r\nB2 Regionalisation with local  environmental sustainability. B2a and B2b follow the same experiment design and historic and future forcings but start from different initial conditions.\r\n\r\nNotes.\r\n * TAR uses CMIP2 simulations.\r\n * Only two models have run all the experiments.",
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            "title": "30 year climatologies from model output as used in the 1995 IPCC Second Assessment Report (SAR)",
            "abstract": "Data used in Climate Change 1995, the Second Assessment Report (SAR) of the United Nations Intergovernmental Panel on Climate Change (IPCC).\r\n\r\nSimulations of global climate models were run by various climate modelling groups coordinated by the World Climate Research Programme (WCRP) on behalf of the United Nations Intergovernmental Panel on Climate Change (IPCC).\r\nClimatology data calculated from global climate model simulations of experiments representative of IPCC Scenarios IS92 a and d.\r\nThe climatologies are 30-year averages. Climate anomalies are expressed relative to the period 1961-1990. The monthly climatology data covers the period from 1961-2100. The climatologies are of global scope and are provided on latitude-longitude grids.",
            "keywords": "IPCC, DDC, SAR, IS92, Climate Change",
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            ],
            "dataLineage": "Climatology data calculated from global climate model simulations for IS92 experiments a and d.\r\nThe climatologies are 30-year averages. Climate anomalies are expressed relative to the period 1961-1990. \r\n\r\nModels: \r\n\r\nCCCma/CGCM1: Canadian Global Coupled Model, CGCM1. A spectral model with triangular truncation at wave number 32 (roughly 3.7ºx3.7º latitude/longitude) and 10 vertical levels. The ocean component is based on the GFDL MOM1.1 with a resolution of approximately 1.8ºx1.8º and 29 vertical levels. \r\n\r\nCCSR/NIES: A coupled ocean-atmosphere model that consists of the CCSR/NIES atmospheric GCM, the CCSR ocean GCM, a thermodynamic sea-ice model, and a river routing model.  The spatial resolution is T21 spectral truncation (roughly 5.6º latitude/longitude) and 20 vertical levels for the atmospheric part, and roughly 2.8º horizontal grid and 17 vertical levels for the oceanic part. \r\n\r\nCSIRO-Mk2b: The CSIRO Atmospheric Research Mark 2b climate model atmosphere has 9 levels in the vertical and horizontal resolution of spectral R21 (roughly 5.6 by 3.2 degrees). The ocean model has the same horizontal resolution with 21 levels. \r\n\r\nECHAM-4: The ECHAM-4 model is a spectral transform model with 19 atmospheric layers and the results used here derive from experiments performed with spatial resolution T42 (roughly 2.8º longitude/latitude).\r\n\r\nGFDL-R15: The model has interactive clouds and seasonally varying solar insolation. The atmospheric component has nine finite difference (sigma) levels in the vertical. This version has a rhomboidal resolution of 15 waves (R15) roughly 4.5º latitude by 7.5º longitude. The model has global geography consistent with its computational resolution and seasonal (but not diurnal) variation of insolation.\r\n\r\nHadCM2: HadCM2 has a spatial resolution of 2.5° x 3.75° (latitude by longitude) and the representation produces a grid box resolution of 96 x 73 grid cells. This produces a surface spatial resolution of about 417km x 278 km reducing to 295 x 278km at 45 degrees North and South (comparable to a spectral resolution of T42).\r\n\r\nNCAR-DoE: The NCAR-DoE global coupled model (sometimes referred to as the Washington-Meehl coupled model) used in these experiments has an atmospheric component with rhomboidal 15 (R15) resolution (roughly 4.5º latitude by 7.5º longitude) with 9 levels, mass flux convection and a cloud albedo feedback scheme; a global 1º by 1º 20-level ocean; and dynamic and thermodynamic sea ice.\r\n\r\nExperiments: \r\n\r\n1% per annum forcing greenhouse gases only \"GG\",  1% per annum forcing greenhouse gasses and sulphates \"GS\" - equivalent to scenario IS92a: Population rises to 11.3 billion by 2100 and economic growth averages 2.3 % per annum between 1990 and 2100, with a mix of conventional and renewable energy sources being used. \r\n\r\n0.5% per annum forcing greenhouse gases only \"GG\",  0.5% per annum forcing greenhouse gasses and sulphates \"GS\" - equivalent to scenario IS92d: Population rises to 7.6 billion in 2025 then falls to 6.4 billion by 2100 and economic growth averages 2.0% per annum between 1990 and 2100 with increasing use of renewable energy.",
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            "title": "IPCC AR5 Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP3 and CMIP5",
            "abstract": "Projected regional average change in seasonal and annual mean temperature and precipitation for the IPCC SREX regions for CMIP5 and CMIP3.  The data were produced in 2014 by the Intergovernmental Panel on Climate Change (IPCC) Working Group II (WGII) Chapter 21 author team for the IPCC Fifth Assessment Report (AR5). \r\n\r\nRegional average seasonal and annual mean temperature and precipitation for the period 2071-2100 are compared to a baseline of 1961-1990 for CMIP5 and CMIP3 General Circulation Model (GCM) projections.\r\nThe data compare the range of projections from 35 Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble under four Representative Concentration Pathway (RCP) scenarios compared with GCM projections from 22 CMIP3 ensemble under three Special Report on Emission Scenarios (SRES) scenarios. \r\n\r\nRegional averages are based on SREX regions defined by the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (IPCC, 2012: also known as \"SREX\").",
            "keywords": "IPCC AR5 IPCC-DDC regional CMIP CMIP3 CMIP5 SREX RCP25 RCP45 RCP60 RCP85 A1B A2 B1",
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            "title": "Along Track Scanning Radiometers Arctic combined Surface Temperature (AAST) daily mean Level 3 (L3S) dataset, v2.1",
            "abstract": "The AAST L3S Combined Surface Temperature (CST) products here primarily provide data on surface temperatures in the Arctic, across all Arctic surfaces, and their associated uncertainties. This dataset consists of CSTs with uncertainty estimates produced from the ATSR-2 and AATSR  instruments on ESA's ERS-2 and Enivsat satellite respectively. The CSTs in this dataset are surface temperatures across ocean, snow/ice and land surfaces in the Arctic region, where the Arctic is defined as the area at, or north of, 60°N. Please note, the data here provide daily temperature data, not daily mean data as indicated by the dataset title. For more information see the paper linked under the details tab The data were produced for ATSR Satellite Dataset project, which was funded by The UK Dept. for Business, Energy & Industrial Strategy.\r\n\r\nIce (and snow) Surface Temperatures (ISTs) and Land Surface Temperatures (LSTs) used to produce this dataset are sourced from the GlobTemperature Level 2 LST V2.1 product. Sea Surface Temperature (SSTs) are from the ATSR SST L2P V3.0 product. This version of the CST dataset is v2.1, with an earlier version previously provided via the GlobTemperature data portal.  ATSR data was sourced from the GlobTemperature data portal and the CEDA archive. It consists of a complete set of CST and accompanying auxiliary (AUX) datafiles for the ATSR-2 and AATSR  instruments separately. ATSR-2 data are available for 01/08/1995  - 22/06/2003 while AATSR data are available for 20/05/2002 – 08/04/2012.",
            "keywords": "Arctic, Surface Temperature, ATSR-2, AATSR",
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            "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Upernavik glacier from ERS-1, ERS-2, Envisat and PALSAR data for 1992-2010, v1.2",
            "abstract": "This dataset contains a time series of ice velocities for the Upernavik glacier in Greenland, derived from intensity-tracking of ERS-1, ERS-2 and Envisat and PALSAR data aquired between 02/01/1992 and 22/08/2010.  The data provides components of the ice velocity and the magnitude of the velocity, and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing.  The image pairs used have a repeat cycle between 1 and 35 days.  The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NOTHING(y) directions of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided. \r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland).",
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            "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series  for the Jakobshavn glacier from ERS-1, ERS2 and ENVISAT data for 1992-2010, v1.2",
            "abstract": "This dataset contains time series of ice velocities for the Jakobshavn Glacier in Greenland, which have been derived from intensity-tracking of ERS-1, ERS-2 and Envisat data acquired between between 1992 and 2010.  It provides components of the ice velocity and the magnitude of the ice velocity and has been produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe dataset contains two time series: 'Greenland_Jakobshavn_TimeSeries_2002_2010' contains an older version of the time series kept for completeness and also to ensure the best temporal coverage.  It is based on data from the ASAR instrument on ENVISAT, acquired between 10/11/2002 and 23/09/2010 and contains 47 maps of ice velocity.  \r\n\r\nThe second time series 'greenland_jakobshavn_timeseries_1992_2010' contains the latest version of the time serives based on ERS-1, ERS-2 and Envisat data acquired between 27/01/1992 and 13/06/2010 and contains 120 maps.\r\n\r\nThe data is provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. The image pairs have a repeat cycle between 1 and 35 days.\r\nThe horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.\r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland) and ENVEO (Earth Observation Information Technology GmbH).",
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            "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Surface Elevation Change from Cryosat-2, v2.2",
            "abstract": "This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from Cryosat 2 satellite radar altimetry, for the time period between 2010 and 2017.\r\n \r\nThe surface elevation change data  are provided as 2-year means (2011-2012, 2012-2013, 2013-2014, 2014-2015, 2015-2016, and 2016-2017), and five-year means are also provided (2011-2015, 2012-2016, 2013-2017), along with their associated errors.   Data are provided in both NetCDF and gridded ASCII format, as well as png plots.\r\n\r\nThe algorithm used  to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. Sørensen, Remote Sensing of the Environment, 190,pp.207-216, doi:10.1016/j.rse.2016.12.012",
            "keywords": "Greenland Ice Sheet, ESA, CCI",
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            "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Grounding Line Locations from SAR Interferometry,  v1.3",
            "abstract": "This dataset contains grounding lines for 5 North Greenland glaciers, derived from generated from ERS -1/-2 and Sentinel-1 SAR (Synthetic Aperture Radar) interferometry.  This version of the dataset (v1.3) has been extended with grounding lines for 2017. Data was produced as part of the ESA Greenland Ice Sheets Climate Change Initiative (CCI) project by ENVEO, Austria. \r\n\r\nThe grounding line is the separation point between the floating and grounded parts of the glacier. Processes at the grounding lines of floating marine termini of glaciers and ice streams are important for understanding the response of the ice masses to changing boundary conditions and for establishing realistic scenarios for the response to climate change. The grounding line location product is derived from InSAR data by mapping the tidal flexure and is generated for a selection of the few glaciers in Greenland, which have a floating tongue. In general, the true location of the grounding line is unknown, and therefore validation is difficult for this product.\r\n\r\nRemote sensing observations do not provide direct measurement on the transition from floating to grounding ice (the grounding line). The satellite data deliver observations on ice surface features (e.g. tidal deformation by InSAR, spatial changes in texture and shading in optical images) that are indirect indicators for estimating the position of the grounding line. Due to the plasticity of ice these indicators spread out over a zone upstream and downstream of the grounding line, the tidal flexure zone (also called grounding zone).",
            "keywords": "Greenland, Ice Sheet, CCI, ESA",
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            "dataPublishedTime": "2018-11-28T16:54:15",
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                "volume": 283357,
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