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=5300
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=5400",
    "previous": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=5200",
    "results": [
        {
            "ob_id": 25941,
            "uuid": "38296ae73f3b44f5b8d66dcc3ed398bd",
            "title": "QA4ECV Polar sea-ice spectral albedo (2000-2016)",
            "abstract": "The Quality Assurance for Essential Climate Variables (QA4ECV) project produced four daily polar sea-ice products, each with a different averaging time window (24 hours, 7 days, 15 days, 31 days). For each time window, the number of samples, mean and standard deviation of Multi-angle Imaging SpectroRadiometer (MISR) cloud-free sea ice albedo was calculated. These products are on a predefined polar stereographic grid at three spatial resolutions (1 km, 5 km, 25 km). The time span of the generated sea ice albedo covers the months between March and September of each year from 2000 to 2016 inclusive.\r\n\r\nIf publishing results based on this dataset, please cite the following: S. Kharbouche and J.-P. Muller, “Sea Ice Albedo from MISR and MODIS: Production, Validation, and Trend Analysis,” Remote Sensing, vol. 11,no. 1, p. 9, Dec. 2018. DOI: 10.3390/rs11010009. URL:http://www.mdpi.com/2072-4292/11/1/9",
            "keywords": "Albedo, Polar, Climate, Sea Ice, Radiometer",
            "publicationState": "citable",
            "dataPublishedTime": "2019-01-18T13:01:13",
            "doiPublishedTime": null,
            "updateFrequency": "",
            "status": "completed",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/26911/?format=api",
                "dataPath": "/neodc/qa4ecv/data/sea_ice/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2224562524077,
                "numberOfFiles": 39313,
                "fileFormat": "These data are in NetCDF format"
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/7010/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api",
            "nonGeographicFlag": false,
            "phenomena": [
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24786/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24787/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24788/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24789/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24790/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24791/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24792/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24793/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24794/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24795/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24796/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24797/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24798/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24799/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24800/?format=api"
            ],
            "dataLineage": "Data are provided by the QA4ECV project for archival with CEDA. Data are in NetCDF format.\r\n\r\nIf publishing results based on this dataset, please cite the following: S. Kharbouche and J.-P. Muller, “Sea Ice Albedo from MISR and MODIS: Production, Validation, and Trend Analysis,” Remote Sensing, vol. 11,no. 1, p. 9, Dec. 2018. DOI: 10.3390/rs11010009. URL:http://www.mdpi.com/2072-4292/11/1/9",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10211/?format=api"
            ],
            "projects": [
                "https://api.catalogue.ceda.ac.uk/api/v2/projects/25937/?format=api"
            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25940/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25978/?format=api"
            ],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/112952/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108433/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/112951/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108435/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108436/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/112953/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113178/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/112954/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108434/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108437/?format=api"
            ],
            "procedureAcquisition": null,
            "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/26906/?format=api",
            "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": [
                {
                    "ob_id": 1138,
                    "name": "NDGO0003"
                }
            ]
        },
        {
            "ob_id": 25942,
            "uuid": "bd2ad818ebec44748078fefa5161bd83",
            "title": "QA4ECV Europe Spectral albedo (1998-2000, 2005-2006)",
            "abstract": "European spectral albedo data of the land surface is produced from data from 1998-200 and 2005-2006 from European and US satellites daily and monthly with estimated uncertainties for every pixel. The spectral albedo is calculated at the first 6 of the MODIS spectral bands.",
            "keywords": "",
            "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 provided ",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [],
            "projects": [
                "https://api.catalogue.ceda.ac.uk/api/v2/projects/25937/?format=api"
            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25940/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25978/?format=api"
            ],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108450/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108451/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204956/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204957/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204958/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204959/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108452/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204955/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108453/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108454/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108449/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108455/?format=api"
            ],
            "procedureAcquisition": null,
            "procedureCompositeProcess": null,
            "procedureComputation": null,
            "permissions": [],
            "discoveryKeywords": []
        },
        {
            "ob_id": 25944,
            "uuid": "050ab7126ebe4300b7a3dc9fce18b054",
            "title": "QA4ECV LAI",
            "abstract": "The Leaf Area Index (LAI) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product). he definition of LAI in this product is half the total canopy area per unit ground area (m2 / m2) for a homogeneous canopy of infinitesimally small Lambertian surfaces, akin to a turbid medium.",
            "keywords": "",
            "publicationState": "working",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "updateFrequency": "",
            "status": "pending",
            "result_field": null,
            "timePeriod": null,
            "geographicExtent": null,
            "nonGeographicFlag": false,
            "phenomena": [],
            "dataLineage": "These data",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [],
            "projects": [
                "https://api.catalogue.ceda.ac.uk/api/v2/projects/25937/?format=api"
            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25943/?format=api"
            ],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108458/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204846/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204847/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204848/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204849/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204850/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108460/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204845/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108459/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108461/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108462/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108463/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108464/?format=api"
            ],
            "procedureAcquisition": null,
            "procedureCompositeProcess": null,
            "procedureComputation": null,
            "permissions": [],
            "discoveryKeywords": []
        },
        {
            "ob_id": 25945,
            "uuid": "fb1df8ff08564616818d71d78db03f51",
            "title": "QA4ECV BHR-TIP FAPAR/ effective LAI (1982-2016)",
            "abstract": "The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product). The definition of FAPAR in this product is the simulated absorption of the photosynthetically active radiation (estimated for the visible band) by a homogeneous canopy of infinitesimally small Lambertian surfaces, akin to a turbid medium.",
            "keywords": "",
            "publicationState": "preview",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "updateFrequency": "",
            "status": "pending",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/27070/?format=api",
                "dataPath": "/neodc/qa4ecv/data/BHR-TIP/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 874878676097,
                "numberOfFiles": 25991,
                "fileFormat": "These data are in netCDF file format."
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/7018/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api",
            "nonGeographicFlag": false,
            "phenomena": [
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/53130/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/53131/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69393/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69394/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69395/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69396/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69397/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69398/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69399/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69400/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69401/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/69402/?format=api"
            ],
            "dataLineage": "These data",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [],
            "projects": [
                "https://api.catalogue.ceda.ac.uk/api/v2/projects/25937/?format=api"
            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25943/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25978/?format=api"
            ],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108465/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108466/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143622/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143623/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143624/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143625/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143626/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143621/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108467/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108468/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108469/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108470/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108471/?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": []
        },
        {
            "ob_id": 25947,
            "uuid": "5587614793674fa680a8e6e5b93c6bff",
            "title": "QA4ECV DHR-FAPAR (1982-2006)",
            "abstract": "The Joint Research Centre (JRC) are currently producing a new Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product which ingests Advanced Very High Resolution Radiometer (AVHRR) data. The estimation of a state variable from the signals measured by a given sensor is constructed from sensor-specific simulated data sets, representative of various land surfaces, using radiative transfer models of the coupled surface atmosphere system. This approach defines a large number of simulated radiance fields, which can be sampled by a virtual instrument similar to the actual one in terms of the spectral and angular observing schemes. Similarly, the corresponding FAPAR values for the various terrestrial systems under investigation can be simultaneously estimated. The simulations of FAPAR values have been made by assuming that the spectral properties of leaves and soil correspond to the Photosynthesis Active Radiation (PAR) region which is between 400 nm and 700 nm. In this case, simulations are made with a homogeneous canopy model (Gobron et al. 1997) representing land surfaces.",
            "keywords": "",
            "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": "These data",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [],
            "projects": [
                "https://api.catalogue.ceda.ac.uk/api/v2/projects/25937/?format=api"
            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25946/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25978/?format=api"
            ],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108474/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108475/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/200395/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/200396/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/200397/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/200398/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/200399/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/200400/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108481/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108482/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108483/?format=api"
            ],
            "procedureAcquisition": null,
            "procedureCompositeProcess": null,
            "procedureComputation": null,
            "permissions": [],
            "discoveryKeywords": []
        },
        {
            "ob_id": 25950,
            "uuid": "a3e0f0848a144484bdea833ef01ec834",
            "title": "Arctic Cloud Summer Expedition (ACSE): carbon dioxide and water vapour measurements from the University of Leeds LI-COR Li-7500 gas analyzer on board Icebreaker Oden",
            "abstract": "This dataset contains carbon dioxide and water vapour concentration measurements from the University of Leeds' LI-COR LI-7500 open path gas analyser mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe instrument's sensing head was located on the foremast of Icebreaker Oden, approximately 1 m forward of the sonic anemometer. Note the LiCOR LI-7500 CO2 data are generally not suitable for flux measurements at sea. Only the water vapour signal has been used for flux analysis.\r\n\r\nData times were truncated to match those from the sonic anemometer and the internal lag was corrected for.\r\n\r\nUsers should also note that the instrument's temperature and pressure measurements are made inside the interface box. Temperature is thus likely to be high due to solar heating of box, and pressure will be biased low (box is ~3 m below sensor) and may be subject to dynamic pressure fluctuations resulting from airflow around pressure inlet.\r\n\r\nMeasurements are made at 20 Hz frequency.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.",
            "keywords": "CO2, H2O, water vapour, carbon dioxide",
            "publicationState": "citable",
            "dataPublishedTime": "2018-04-14T12:59:52",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "final",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/25949/?format=api",
                "dataPath": "/badc/acse/data/leeds-licor-7500",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
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            "title": "Arctic Cloud Summer Expedition (ACSE): turbulence wind and sonic temperature measurements from the University of Leeds Metek USA-100 sonic anemometer on board Icebreaker Oden",
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            "title": "Arctic Cloud Summer Expedition (ACSE): University of Leeds Mobotix camera imagery on board Icebreaker Oden",
            "abstract": "This dataset contains digital imagery from the University of Leed's three 'Mobotix MX-M24M IP' cameras mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These imagery were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe three camera units were mounted pointing in the following directions:\r\n\r\n - Camera 1: pointing to starboard,\r\n - Camera 2: pointing to bow,\r\n - Camera 3: pointing to port.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).",
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            "abstract": "This dataset contains high resolution attitude and motion measurements of the Icebreaker Oden ship's motion by the University of Leeds' XSENS MTi-G-700 attitude and heading reference system during the Arctic Cloud Summer Expedition (ACSE). The ACSE cruise took place in the Arctic during summer 2014. These data were obtained to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (Swedish-Russian-US Investigation) holdings - see online resources linked to this record.\r\n\r\nMeasurements were made at 40Hz for inertial measurements and 4Hz for GPS measurements. Though the inertial measurements were used at 20Hz when merged with sonic anemometer, 20 minute final fluxes (see related data within the parent data collection).\r\n\r\nThe XSens MTi-G-700 measures 3-axis accelerations, rotation rates, and magnetic field components as well as GPS position. Internal algorithm calculate 3-axis velocity, tilt angles and heading.  However, users of these data should note that it is often not possible to calibrate magnetic field for local platform induced distortions (soft iron and hard iron corrections) resulting in errors in magnetic field and calculated outputs. Additionally, the heading measurements were found to unreliable on the ship.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).",
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            "title": "Arctic Cloud Summer Expedition (ACSE): surface temperature measurements from the University of Leeds Heitronics KT15.85 infra red radiative temperature sensor on board Icebreaker Oden",
            "abstract": "This dataset contains surface temperature measurements from the University of Leeds' two Heitronics KT15.85 infra red radiative temperature sensors mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nBoth instruments were mounted to point to starboard, but instrument 1 pointing 45 degrees forward and instrument 2 pointing 45 degrees aft, taking raw measurements at 1Hz. The data contain both the raw measured temperature (t_meas) and a corrected value, adjusted for reflection of thermal radiation from surface. The correction follows that developed by Phil Hignett for a similar sensor on the UK Met Office C130 aircraft : MRF Tech note 28, 1988.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.",
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            "abstract": "This dataset contains surface air temperature (T) and relative humidity (RH) measurements from the Meteorologiska Institutionen Stockholms Universitet (MISU) Rotronic T/RH sensor mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nMeasurements were made at 1 Hz frequency and this dataset was prepared for archiving by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.",
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            "title": "HadISDH: gridded global monthly land surface humidity data version 4.0.0.2017f",
            "abstract": "This is the 4.0.0.2017f version of the HadISDH land data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2017. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 3.0.0.2016p version to the end of 2017 and constitutes a major update to HadISDH due to a change to using the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. Users are advised to read the update document in the docs section for full details. This version now uses the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. \r\n\r\nAdditionally, there has been a small methodological change. Stations with large adjustments made during homogenisation are removed based on thresholds for q (>3g/kg), RH (>15%rh), T (>5degC) and Td (>5degC) rather than just T and Td. This results in 54 stations being removed as opposed to 29 last year. All other processing steps for HadISDH remain identical. \r\n\r\nThe new version of HadISD2 (2.0.2.2017p) has pulled through some historical changes to stations which are passed on to HadISDH. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data. \r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013.",
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            "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2017, v2.0.2.2017f",
            "abstract": "This is version 2.0.2.2017f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v2.0.1.2016p to include 2017 and so spans 1931-2017, it replaces the preliminary version (v2.0.2.2017p) as the ISD data for 2017 are now finalised.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20171231_v2-0-2-2017f.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nFor a more detailed description of precipitation see: http://hadisd.blogspot.co.uk/2018/03/precipitation-in-hadisd.html\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014.",
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            "abstract": "This dataset contains surface meteorological measurements including air temperature, relative humidity, surface irradiation and wind measurements from the Meteorologiska Institutionen Stockholms Universitet (MISU) weather station on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThese data came from an automatic weather station installed on the 7th deck of the Icebreaker Oden, approximately 25m above the surface, measuring at 1 Hz frequency. The system was operated by Joe Sedlar who also undertook data quality control and there are several flag variables for T/RH and radiation measurements documenting known data issues - notably when primary measurements have been replaced with those from other sensors, or corrections applied. This version of the dataset was then prepared for archiving with the Centre for Environmental Data Analysis by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.",
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            "title": "APHH: Chemical composition measurements of PM2.5 particles made at the IAP-Beijing site during the  winter campaign",
            "abstract": "This dataset contains chemical composition measurements of PM2.5 particles made at the Institute of Atmospheric Physics land station (IAP), Beijing  site during the winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nDaily fine particles were collected on the PTFE (Polytetrafluoroethylene) filters using the Partisol samplers. The filters were then analysed for metals using X-ray fluorescence (XRF) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and for ion species using Ion Chromatography. Quartz filters were collected by Tisch high vol, samplers and then were analysed for organic and elemental carbons using the DRI Model 2015 Multiwavelength Thermal/Optical Carbon Analyser, and organic tracers using Gas chromatography–mass spectrometry (GC-MS).",
            "keywords": "PM2.5, China, pollution, APHH",
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            "title": "APHH: Particle number size distribution measurements made at the IAP-Beijing site during the summer campaign",
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            "title": "Arctic Cloud Summer Expedition (ACSE): composite flux data for Icebreaker Oden",
            "abstract": "This dataset contains provides the final best estimates of fluxes, mean environmental variables and derived transfer coefficient estimates, along with asociated quality control flags, during the Icebreaker Oden voyage durning the Arctic Cloud Summer Expedition (ACSE) in summer 2014. These were calculated based on instrumentation data from the University of Leeds' Metek sonic anemometer, Licor LI-7500 gas analyzer and XSENS MTi-G-700 motion pack, plus mean surface meteorology data provided from the automatic weather station operated on board by the Department of Meteorology, Stockholm University (MISU).\r\n\r\nOther data from the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.\r\n\r\nThe document \"ACSE_turbulent_fluxes_readme.txt\" in the archive contains fuller details of the flux calculations. The final data, prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds, contain:\r\n\r\n1) The final quality controlled best estimates of 20-min averaged dynamic fluxes, associated mean environmental variables (10m wind, etc), transfer coefficients, and quality control flags.\r\n\r\n2) The raw kinematic fluxes, etc that go into generating (1), along with the quality control variables used in generating the QC flags, and the QC flags.\r\n\r\n3) Other environmental variables (in some cases with duplicates from multiple different sensors) averaged onto the same time base as the flux estimates.\r\n\r\nThe authors note that in all cases a lot of work has been done on quality control and applying suitable corrections to raw measurements. In many cases other choices could have been made, and additional QC measures may need to be applied.\r\n\r\nMost of the work on the flux data processing has been done by John Prytherch, with additional input from Ian Brooks and Dominic Salisbury. Additional work on ancillary data was undertaken by other members of the ACSE science team.",
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            "title": "Arctic Cloud Summer Expedition (ACSE): composite cloud layer data for Icebreaker Oden",
            "abstract": "This dataset contains derived cloud layer measurements of Icebreaker Oden utilising data from the National Centre for Atmospheric Science's Atmospheric Measurement Facility's (NCAS AMF) Halo Doppler lidar and NOAA cloud radar on board Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe data provide altitudes of cloud base and top for the first two cloud layers. Cloud base was established from the laser ceilometer (base of liquid cloud) whist he cloud top was established from the cloud radar data. \r\n\r\nWhere fog was detected, the fog top altitude from the radar data is given. Note: it was possible for the radar to detect a cloud top where the laser ceilometer was not able to detecte a cloud base.\r\n\r\nThese data were prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.",
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            "title": "EUSTACE/GlobTemperature:  Global clear-sky land surface temperature data from MODIS Terra on the satellite swath with estimates of uncertainty components, v2.1, 2000-2016",
            "abstract": "This dataset consists  of Land Surface Temperature (LST) data with uncertainty estimates, from the MODIS instrument on NASA's Terra satellite.   It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.  \r\n\r\nThe Level 2 Land Surface Temperature data in this dataset has been retrieved from MODIS Collection 6 L1B calibrated radiances,  in the context  of the GlobTemperature project, but new uncertainty estimates have been added as part of the EUSTACE project.    This version of the LST dataset is v2.1 of the GT_MOG_2P product, with earlier versions produced under the GlobTemperature project.  It consists of a complete set of LST and accompanying auxiliary (AUX) datafiles for the MODIS-Terra mission for the period 2000 to 2016.  An equivalent dataset is also available for MODIS-Aqua.",
            "keywords": "eustace, land surface temperature, LST",
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            "title": "CRUTEM3 Global mean monthly temperature time series from the historical land-only surface temperature",
            "abstract": "This dataset contains CRUTEM3 Global mean monthly temperature time series from the historical land-only surface temperature, produced in 2006 for the period: 1850-2010. The global temperature is calculated as the mean of the Northern and Southern Hemisphere time series (to stop the better sampled Northern Hemisphere from dominating the average).  Data represent temperature anomalies with respect to the 1961-1990 mean. \r\n\r\nA new version of the CRUTEM data set, CRUTEM3, has been produced, benefiting from improvements to the station records which provide the land temperature data. CRUTEM3 no longer infills missing grid box values using data from surrounding grid boxes but rather attributes an uncertainty to each grid box value. \r\n",
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            "title": "DEEP-C: Derived surface net downward energy and absorbed radiation",
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            "dataLineage": "Data produced by Diagnosing Earth's Energy Pathways in the Climate system (DEEP-C) and delivered to the Centre for Environmental Data Analysis (CEDA) for archiving.",
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            "title": "Envelope field of Northern hemispheric upper tropospheric (300 hPa) quasi-stationary waves (June 1979 to August 2015)",
            "abstract": "This dataset comprises 12 hourly data of the envelope field of Northern hemispheric upper tropospheric (300 hPa) quasi-stationary waves calculated between1979-06-01 and 2015-08-31.  The data were derived as part of the NERC funded ODYSEA project (Ocean Dynamics as Driver of Seasonal to Decadal European Atmospheric variability).\r\n\r\nThe envelope field in this dataset is a phase-independent measure of the wave amplitude and is derived from the meridional wind at 300 hPa of the ERA-Interim reanalysis data. To remove the faster transient signals a 15-day lowpass filter was applied to the meridional wind and then subtracted from a daily climatology.  The envelope field allows for the identification of a slowly evolving stationary or slowly moving wave packet.\r\n\r\nFull details of the method are described in the methodology statement that can be found in the docs section.",
            "keywords": "quasi-stationary waves, wave packet, NE/M006107/1",
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            "keywords": "ECMWF, ERA, ERA, Interim, reanalysis, surface, model, Gaussian, N256, analysis, pressure level, monthly-mean",
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            "title": "Re-analysis ERA-20C European winter extra-tropical cyclone tracks 1900-2010",
            "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from the ERA-20C (1900-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)",
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            "uuid": "421688bf376b41b884246b34bd274356",
            "title": "Re-analysis ERA-Interim European winter extra-tropical cyclone tracks 1979-2010",
            "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from the ERA-Interim (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)",
            "keywords": "extra-tropical, cyclone, European, track, tracks, ETC, storm, storms",
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            "title": "Re-analysis NCEP-CFS European winter extra-tropical cyclone tracks 1979-2010",
            "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from NCEP-CFS (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)",
            "keywords": "extra-tropical, cyclone, European, track, tracks, ETC, storm, storms",
            "publicationState": "citable",
            "dataPublishedTime": "2018-06-15T13:11:57",
            "doiPublishedTime": null,
            "updateFrequency": "",
            "status": "completed",
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                "dataPath": "/badc/deposited2018/robust-storm-track/data/ncep-cfs",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 307311552,
                "numberOfFiles": 5,
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/7049/?format=api",
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            "dataLineage": "Data delivered to the Centre for Environmental Data Analysis (CEDA) for archiving by the project team.",
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                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/26096/?format=api"
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109291/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109287/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109285/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109286/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109293/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109288/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109289/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109292/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109290/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/168804/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109294/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109295/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109296/?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": 26102,
            "uuid": "cf97ccc802d348ec8a3b6f2995dfbbff",
            "title": "Daily MODIS (MODerate Imaging Spectroradiometer) derived cloud droplet number concentration global dataset for 2003-2015",
            "abstract": "Daily global cloud droplet number concentrations (Nd) have been calculated at 1x1 degree resolution from pixel-level MODIS (MODerate Imaging Spectroradiometer) Collection 5.1 Joint Level-2 (Aqua satellite) optical depth (tau) and the 3.7 micron effective radius (reff) data (and other supporting data) using the adiabatic cloud assumption (liquid water content increases linearly with height, Nd is constant throughout the cloud depth and the ratio of the volumne mean radius to the effective radius is assumed constant). \r\n\r\nThe Nd data is contained in separate NetCDF files for each year for the period 2003-2015. Nd is contained in the \"Nd\" variable and has units of cm^{-3}. This is a 360x180xNdays (lon x lat x Ndays) sized array, where Ndays is the number of days in the year. The lon x lat grid is a regular 1x1 degree grid. The time is provided as both a 1D array of size Ndays (\"time\") with units of days since 1st Jan, 1970 and an array of size Ndays x 3 (\"time_vec\") that contains numbers for the year month and day for each of the Ndays entries.\r\n \r\nA number of filters have been applied to the data in order to remove retrievals that are likely to be problematic, or to violate the adiabatic cloud assumptions. Data is only included if:\r\n\r\n    1) Pixels are determined to be liquid pixels by MODIS.\r\n    2) The 1x1 degree mean cloud top height (calculated using the MODIS cloud top temperature and the sea surface temperature) is below 3.2km.\r\n    3) The 1x1 degree liquid cloud fraction was larger than 80%.\r\n    4) The 1x1 degree mean solar zenith angle was 65 degrees or less to avoid biases at high angles (Grosvenor and Wood, 2014).\r\n\t\t\t\t\t\t\r\n  Note, that the filtering is different to that described in Grosvenor, AMTD, 2018 in the following ways :-\r\n\r\n    1) 1km resolution tau and reff are used to calculate Nd, which is then aggregated to 1x1 degree resolution (rather than using 1x1 degree tau and reff).\r\n    2) Only Nd based on the 3.7 micron reff retrieval is provided here.\r\n    3) No filtering for the presence of sea-ice is done here - it is recommended that this is done if using for high latitudes.\r\n    4) The data here is not restricted to tau>5.\r\n\t\t\t\t\t\t\t\t\t\t\t\t\r\nAlso note that the vertical penetration bias correction described in Grosvenor, AMTD, 2018 is NOT applied here. In addition, as described in the latter paper, further pixel-level screening is performed in order to select high quality data.\r\n\r\nDetails on the reasons for restricting to low solar zenith angles can be found in Grosvenor and Wood, ACP, 2014. Information on the pixel level filtering applied can be found in Grosvenor et al., AMTD, 2018 (noting the differences explained above). A comparison of this dataset with others can be found in Grosvenor et al., Reviews of Geophysics, 2018.\r\n\r\nThis dataset calculates a product that is not provided as standard by MODIS. It uses improved optical depth and effective radius data compared to the standard MODIS Level-3 data since situations (e.g., high solar zenith angles, broken clouds) that have been shown to cause retrieval issues have been filtered out at the Level-2 stage before being averaged into Level-3 droplet concentration data.\r\n",
            "keywords": "",
            "publicationState": "published",
            "dataPublishedTime": "2018-05-23T15:54:22",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "completed",
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2461071312,
                "numberOfFiles": 14,
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/24303/?format=api"
            ],
            "dataLineage": "The data upon which this dataset was based was downloaded in the form of Collection 5.1 Joint Level-2 cloud product swaths (MYDATML files) from the MODIS-Aqua satellite instrument via the MODIS FTP service. They were then processed using Matlab following the methods described above onto a regular 1x1 degree grid with separate values stored for each overpass of a given gridbox. Overpasseses with a solar zenith angles larger than 65 degrees were not included in the subsequent averaging to daily values.\r\n",
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            "language": "English",
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            "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/26034/?format=api",
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            "ob_id": 26112,
            "uuid": "9f8dfaf790644dbcb2c3f69f409a70d6",
            "title": "UKCP18 Probabilistic Projections on a 25km grid over the UK for 1961-2100",
            "abstract": "This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline periods 1961-1990, 1981-2000 and 1981-2010, and cover the period 1 Dec 1960 to 30 Nov 2099. Gridded data on a 25km grid over the United Kingdom, the Isle of Man and the Channel Islands is provided. Further information on this dataset and UKCP18 can be found under UK Climate Projections (UKCP18) guidance and reports in the documentation section.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to under UK Climate Projections News in the documentation section.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to under UK Climate Projections News in the documentation section.",
            "keywords": "UK, Climate, Projections, UKCP18, Probabilistic, Uncertainty",
            "publicationState": "published",
            "dataPublishedTime": "2018-11-26T09:00:00",
            "doiPublishedTime": null,
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            "status": "ongoing",
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                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 7260791807012,
                "numberOfFiles": 93036,
                "fileFormat": "Data are NetCDF formatted"
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            "dataLineage": "Data provided by the UK Met Office",
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        {
            "ob_id": 26114,
            "uuid": "8eca5b80ee244d9486162e699c5197f5",
            "title": "UKCP18 Probabilistic Projections by Administrative Regions over the UK for 1961-2100",
            "abstract": "\"This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 16 administrative regions in the UK is provided. Further information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to under UK Climate Projections (UKCP18) news in the documentation section.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to under UK Climate Projections (UKCP18) news in the documentation section.",
            "keywords": "UK, Climate, Projections, UKCP18, Probabilistic, Uncertainty",
            "publicationState": "published",
            "dataPublishedTime": "2018-06-06T11:00:00",
            "doiPublishedTime": null,
            "updateFrequency": "asNeeded",
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                "dataPath": "/badc/ukcp18/data/land-prob/uk/region",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 56654336542,
                "numberOfFiles": 3981,
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            "abstract": "The data are simulated 21st century trends in the one-year return level (i.e. the location parameter) of skew surge due to simulated atmospheric storminess change only. No mean sea level  change is included. The data were produced to investigate the magnitude of this component of extreme sea level change and to  give an estimate of the minimum uncertainty in this component. To produce the data,  atmospheric storminess data from five CMIP5 models was downscaled by the Swedish Meteorological and Hydrological Institute regional climate model RCA4 and used to drive the National Oceanography Centre/Met Office storm surge model CS3. The 5 largest simulated skew surges in each year were identified and a 4-parameter joint probability distribution (including a linear trend in location parameter over time) was fitted. The data given here are the trends in the location parameter from 2007 to 2099.  By construction the scale parameter does not change and so the same trend applies to all return periods. The data covers the UK coast.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.",
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            "title": "UKCP18 exploratory extended time-mean sea level projections around the UK for 2007-2300",
            "abstract": "The UKCP18 exploratory extended time-mean sea level projections are provided as spatially a continuous dataset around the UK coastline for the period 2007-2300. These exploratory projections have been devised to be used seamlessly with the UKCP18 21st Century projections and provide very similar values for the period up to 2100. Users should be aware that post-2100 projections have a far greater degree of uncertainty than the 21st Century projections and should therefore be treated as illustrative of the potential future changes. Note that we cannot rule out substantially larger sea level rise in the coming centuries than is represented in the projections presented here. The data consist of annual time series of the projected change in the time-mean coastal water level relative to the average value for the period 1981-2000. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). As with the 21st Century projections, nine percentiles are provided to characterise the projection uncertainty, based on underlying modelling uncertainty. However, users should view these uncertainties with a much lower degree of confidence for the period post-2100.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThis dataset was updated in March 2023 to correct a minor processing error in the earlier version of the UKCP18 site-specific sea level projections relating to the adjustment applied to convert from the IPCC AR5 baseline of 1986-2005 to the baseline period of 1981-2000. The update results in about a 1 cm increase compared to the original data release for all UKCP18 site-specific sea level projections at all timescales. Further details can be found in the accompanying technical note.",
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            "uuid": "9dace73ad8654298aea626b8bde0a782",
            "title": "Optimised global monthly mean surface flux of ethane (2008-2014) produced using the INVICAT 4D-Var inverse model",
            "abstract": "This data file contains two sets of optimised global surface fluxes of ethane (C2H6), produced through variational inverse methods using the TOMCAT chemical transport model, and the INVICAT inverse transport model. Emissions were produced using an iterative method of optimisation, known as 4D-Var, which minimised the model-observation differences.\r\n\r\nThese surface fluxes are produced as monthly mean values on the (approximately) 5.6 degree horizontal model grid. The associated uncertainty for the flux from each gridcell is also included.  \r\n\r\nThe fluxes and uncertainties are global, and cover the period Jan 2008 - Dec 2014.\r\n \r\nThere are two alternative emissions sets, labelled EMIS_ALL and EMIS_ANTH, whilst the uncertainties are labelled ERROR_ALL and ERROR_ANTH, respectively. The two optimised emission estimates are produced through iterative minimisation of model-observation error in INVICAT. In all cases the observations are surface flask samples of ethane produced by by the National Oceanic and Atmospheric Administration’s Global Monitoring Division (NOAA GMD) and the University of Colorado’s Institute of Arctic and Alpine Research (INSTAAR). Whole air samples in flasks are collected weekly to bi-weekly at each site and C2H6 is measured using gas chromatography with a flame ionization detection method.\r\n  \r\nThe EMIS_ALL fluxes are produced through variation of all surface emission types (anthropogenic, biomass burning, oceanic and biospheric), whilst the EMIS_ANTH fluxes are produced by only allowing the surface anthropogenic emissions to vary, with prior estimates of other emission types then added back on.\r\n\r\nFlux and uncertainty units are kg(C2H6)/m2/s, and time units are days since January 1st 2008. These emissions show improved performance relative to independent observations when included in the TOMCAT model. Further details about the data can be found in the PDF documentation stored along side this data, as well as in Monks et al., 2018.",
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            "dataLineage": "Produced by C. Wilson using the INVICAT inverse model, developed at the University of Leeds, Leeds, UK.   INVICAT is based on the TOMCAT chemical transport model, which was developed by M. P. Chipperfield, also now at the University of Leeds.",
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            "ob_id": 26136,
            "uuid": "489e9b2a0abd43a491d5afdd0d97c1a4",
            "title": "RAL Infrared Microwave Sounder (IMS) temperature, water vapour, ozone and surface spectral emissivity",
            "abstract": "The Rutherford Appleton Laboratory (RAL) Infrared Microwave Sounder (IMS) data set contains vertical profiles of temperature, water vapour, and ozone as well as surface spectral emissivity spanning infrared and microwave, surface temperature, cloud fraction and height. Data are retrieved from co-located measurements by the Infrared Atmospheric Sounding Interferometer (IASI), the Microwave Humidity Sounder (MHS) and the Advanced Microwave Sounding Unit (AMSU) on board the Eumetsat Metop satellites.\r\n\r\nDevelopment of the IMS scheme and data production were funded by the UK’s National Centre for Earth Observation (NCEO) under the Natural Environment Research Council (NERC), with additional funding from EUMETSAT contract EUM/CO/13/4600001252/THH.\r\n\r\nData were produced by the Remote Sensing Group (RSG) at the Rutherford Appleton Laboratory (RAL).\r\n\r\nThis first public release consists of a full processing of the Metop A mission from 2007 to the end of 2016, using version 2.1 of the algorithm.\r\n\r\nIMS data are produced with the horizontal sampling of IASI, ~25 x 25 km",
            "keywords": "IASI, MHS, AMSU, IMS retrieval, temperature, water vapour, surface emissivity, ozone",
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        {
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            "uuid": "bf4fb57ac7f9461db27dab77c8c97cf2",
            "title": "Forcing files for the ECMWF Integrated Forecasting System (IFS) Single Column Model (SCM) over Indian Ocean/Tropical Pacific derived from a 10-day high resolution simulation",
            "abstract": "This data set consisting of initial conditions, boundary conditions and forcing profiles for the Single Column Model (SCM) version of the European Centre for Medium-range Weather Forecasts (ECMWF) model, the Integrated Forecasting System (IFS). The IFS SCM is freely available through the OpenIFS project, on application to ECMWF for a licence. The data were produced and tested for IFS CY40R1, but will be suitable for earlier model cycles, and also for future versions assuming no new boundary fields are required by a later model. The data are archived as single time-stamp maps in netCDF files. If the data are extracted at any lat-lon location and the desired timestamps concatenated (e.g. using netCDF operators), the resultant file is in the correct format for input into the IFS SCM. \r\n\r\nThe data covers the Tropical Indian Ocean/Warm Pool domain spanning 20S-20N, 42-181E. The data are available every 15 minutes from 6 April 2009 0100 UTC for a period of ten days. The total number of grid points over which an SCM can be run is 480 in the  longitudinal direction, and 142 latitudinally. With over 68,000 independent grid points available for evaluation of SCM simulations, robust statistics of bias can be estimated over a wide range of boundary and climatic conditions. \r\n  \r\nThe initial conditions and forcing profiles were derived by coarse-graining high resolution (4 km) simulations produced as part of the NERC Cascade project, dataset ID xfhfc (also available on CEDA). The Cascade dataset is archived once an hour. The dataset was linearly interpolated in time to produce the 15-minute resolution required by the SCM. The resolution of the coarse-grained data corresponds to the IFS T639 reduced gaussian grid (approx 32 km). The boundary conditions are as used in the operational IFS at resolution T639. The coarse graining procedure by which the data were produced is detailed in Christensen, H. M., Dawson, A. and Holloway, C. E., 'Forcing Single Column Models using High-resolution Model Simulations', in review, Journal of Advances in Modeling Earth Systems (JAMES).\r\n  \r\nFor full details of the parent Cascade simulation, see Holloway et al (2012). In brief, the simulations were produced using the limited-area setup of the MetUM version 7.1 (Davies et al, 2005). The model is semi-Lagrangian and non-hydrostatic. Initial conditions were specified from the ECMWF operational analysis. A 12 km parametrised convection run was first produced over a domain 1 degree larger in each direction, with lateral boundary conditions relaxed to the ECMWF operational analysis. The 4 km run was forced using lateral boundary conditions computed from the 12 km parametrised run, via a nudged rim of 8 model grid points. The model has 70 terrain-following hybrid levels in the vertical, with vertical resolution ranging from  tens of metres in the boundary layer, to 250 m in the free troposphere, and with model top at 40 km. The time step was 30 s.\r\n  \r\nThe Cascade dataset did not include archived soil variables, though surface sensible and latent heat fluxes were archived. When using the dataset, it is therefore recommended that the IFS land surface scheme be deactivated and the SCM forced using the surface fluxes instead. The first day of Cascade data exhibited evidence of spin-up. It is therefore recommended that the first day be discarded, and the data used from April 7 - April 16.\r\n  \r\nThe software used to produce this dataset are freely available to interested users;\r\n  1. \"cg-cascade\"; NCL software to produce OpenIFS forcing fields from a high-resolution MetUM simulation and necessary ECMWF boundary files.\r\n     https://github.com/aopp-pred/cg-cascade\r\n  Furthermore, software to facilitate the use of this dataset are also available, consisting of;\r\n  2. \"scmtiles\"; Python software to deploy many independent SCMs over a domain. \r\n     https://github.com/aopp-pred/scmtiles\r\n  3. \"openifs-scmtiles\"; Python software to deploy the OpenIFS SCM using scmtiles.\r\n     https://github.com/aopp-pred/openifs-scmtiles\r\n  ",
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            "uuid": "0f4570c780ba41b19a362e774509c883",
            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 03.3",
            "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v03.3 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document.  Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014",
            "keywords": "ESA, Soil Moisture, CCI, Combined",
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            "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project.\r\nThis dataset forms part of the v03.3 Soil Moisture CCI data (doi:10.5285/b810601740bd4848b0d7965e6d83d26c. http://dx.doi.org/10.5285/b810601740bd4848b0d7965e6d83d26c )",
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            "uuid": "bb339ff791814fc6a8b9a93d339f5bc1",
            "title": "APHH: Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the IAP-Beijing site during the winter and summer campaigns.",
            "abstract": "This dataset contains Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe measurements were taken using the FAGE (Fluorescence Assay by Gas Expansion) technique which is a LIF (laser induced fluorescence) that measures on-resonance fluorescence at 308 nm. HO2 and RO2 are converted to OH via reaction with NO and NO + CO respectively. \r\n\r\nThe instrument is calibrated by photolysis of known concentration of water vapour at 185 nm to generate know concentrations of OH and HO2, same method used for HO2 but NO is injected into the flow to convert HO2 to OH. RO2 is calibrated by photolysing water vapur at 185 nm to generate OH but CH4 is added to convert OH to CH3O2, then CH3O2 is converted to OH using CO and NO. The calibration was preform every three days on campaign, and from this we can convert counts measured into concentration. The units for OH, HO2 and RO2 and there associated errors is molecules cm-3. The data has been filtered for instabilities in data collection including unstable pressure, unstable online, low laser power and not going online correctly. The data has been flagged for when the values were below limit of detection.",
            "keywords": "OH, HO2, RO2, China, pollution, APHH",
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            "title": "APHH: Solar actinic UV flux photolysis rates made at the IAP-Beijing site during the summer and winter campaigns",
            "abstract": "This dataset contains direct measurement of solar actinic UV flux from which photolysis frequencies are calculated  made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the summer and winter APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nPhotolysis rates were derived from the product of absorption cross-section of the precursor molecule, the quantum yield of the photo-product and the actinic flux density (cm-2s-1nm-1). The actinic flux is measured between 280 - 650 nm (<1 nm resolution) using a spectral radiometer attached to a quartz receiver optic. Absorption cross sections and quantum yields are taken from the latest IUPAC recommendations. The instrument was calibrated between 250 - 750 nm using a spectral Irradiance of Standard Tungsten-Halogen lamp before and after the campaign.",
            "keywords": "spectroradiometer, photolysis frequencies, UV, actinic flux, China, APHH",
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            "uuid": "8ed84f3c770544c49329df9b068ab662",
            "title": "APHH: Laser induced fluorescence (LIF) OH reactivity measurements made at the IAP-Beijing site during the winter and summer campaigns",
            "abstract": "This dataset contains Laser induced fluorescence (LIF) OH reactivity measurements made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe Leeds OH reactivity instrument measures OH reactivity by photolysing ozone at 266 nm to produce OH, decay of OH with ambient air is measured with LIF (laser induced fluorescence) at 308 nm. The results generate a bi-exponential curve and a line of best fit can be used to calculate OH lifetime. The instrument is calibrated by flowing air zero through the instrument. The units for OH reactivity is in s-1. The data has been filtered for instrument instabilities such as pressure, laser power, high background (laser scatter) and laser alignment",
            "keywords": "OH, China, pollution, APHH",
            "publicationState": "published",
            "dataPublishedTime": "2018-07-26T15:43:30",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109537/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109538/?format=api",
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            "ob_id": 26183,
            "uuid": "7b9c3b7d3f554f48b9082bc4dcc9607c",
            "title": "APHH: Formaldehyde (HCHO) measurements made at the IAP-Beijing site during the winter and summer campaigns",
            "abstract": "This dataset contains measurements of formaldehyde using laser induced fluorescence (LIF) made at the  Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nFormaldehyde concentration measurements in pptv were made using the Leeds Formaldehyde instrument which uses off-resonance laser induced fluorescence at 353 nm to detect ambient formaldehyde. The instrument was calibrated at regular intervals during the campaign using a commercial permatube containing paraformaldehyde.",
            "keywords": "Formaldehyde, HCHO, Laser induced fluorescence, LIF, APHH",
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        {
            "ob_id": 26187,
            "uuid": "065f6040ef08485db989cbd89d536167",
            "title": "ESA Fire Climate Change Initiative (Fire_cci): Small Fire Dataset (SFD) Burned Area pixel product for Sub-Saharan Africa, version 1.1",
            "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Dataset (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from MODIS MOD14MD Collection 6 active fire products.\r\n\r\nThis dataset is part of v1.1 of the Small Fire Dataset (also known as FireCCISFD11), which covers Sub-Saharan Africa for the year 2016.   Data is available here at pixel resolution (0.00017966259 degrees, corresponding to approximately 20m at the Equator).   Gridded data products are also available in a separate dataset.",
            "keywords": "ESA, CCI, Pixel, Burned Area, Fire Disturbance, Climate Change, GCOS",
            "publicationState": "citable",
            "dataPublishedTime": "2018-10-12T08:43:45",
            "doiPublishedTime": "2018-10-12T16:00:00",
            "updateFrequency": "notPlanned",
            "status": "completed",
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 41917713485,
                "numberOfFiles": 1395,
                "fileFormat": "The product is a set of three single-layer GeoTIFF files  (labelled JD, CL and LC in the filenames for layers 1 to 3 respectively).\r\n\r\nLayer 1 (JD):  Date of the first detection; Pixel Spacing = 0.00017966259deg (approx. 20m); Pixel value = Day of the year, from 1 to 365 (or 366) . A value of 0 is included when the pixel is not burned in the month; a value of -1 is allocated to pixels that are not observed in the month; a value of -2 is allocated to pixels that are not burnable (build up areas, bare areas, , snow and/or ice, open water). Data type = Integer; Number of layers = 1; Data depth = 16\r\n\r\nLayer 2: Confidence Level; Pixel Spacing = 0.00017966259deg (approx. 20m); Pixel value = 0 to 100, where the value is the probability in percentage that the pixel is actually burned, as a result of thedifferent steps of the burned area classification. The higher the value, the higher the confidence that the pixel is actually burned. A value of 0 is allocated to pixels that are not observed in the month, or not taken into account in the burned area processing (non burnable). Data type = Byte; Number of layers = 1; Data depth = 8\r\n\r\nLayer 3: Land cover of that pixel, extracted from the CCI S2 prototype Land Cover map at 20m of Africa 2016. N is the number of the land cover categories in the reference map. It is only valid when layer 1 &gt; 0. Pixel value is 0 to N under the following codes: 1 – Trees cover area; 2 – Shrubs cover area; 3 – Grassland; 4 – Cropland; 5 – Vegetation aquatic or regularly flooded; 6 – Lichen Mosses / Sparse vegetation; Pixel Spacing = 0.00017966259deg  (approx. 20m); Datatype = Byte; Number of layers = 1; Data depth = 8"
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        {
            "ob_id": 26188,
            "uuid": "4f377defc2454db9b2a6d032abfd0cbd",
            "title": "ESA Fire Climate Change Initiative (Fire_cci): AVHRR-LTDR Burned Area Grid product, version 1.0",
            "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The AVHRR - LTDR  Grid v1.0 product described here contains gridded data of global burned area derived from spectral information from the AVHRR (Advanced Very High Resolution Radiometer) Land Long Term Data Record (LTDR) v5 dataset produced by NASA.\r\n\r\nThe dataset provides monthly information on global burned area on a  0.25 x 0.25 degree resolution grid from 1982 to 2017.   The year 1994 is omitted as there was not enough input data for this year.   For further information on the product and its format see the product user guide.\r\n\r\nThis v1.0 product is released as a beta version; only the gridded version of the data is available.",
            "keywords": "ESA, CCI, Pixel, Burned Area, Fire Disturbance, Climate Change, GCOS Essential Climate Variable",
            "publicationState": "citable",
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            "doiPublishedTime": "2019-03-12T10:56:27",
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 40555281206,
                "numberOfFiles": 457,
                "fileFormat": "Data are in NetCDF format"
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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.    \r\n\r\nData has been derived from spectral infomration from the AVHRR Land Long Term Data Record (LTDR) product version 5 dataset (https://ltdr.modaps.eosdis.nasa.gov/cgi-bin/ltdr/ltdrPage.cgi)",
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        {
            "ob_id": 26189,
            "uuid": "4b0773a84e8142c688a628c9ce62d4ec",
            "title": "ESA Fire Climate Change Initiative (Fire_cci): Small Fire Database (SFD) Burned Area grid product for Sub-Saharan Africa, version 1.1",
            "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Database (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from MODIS MOD14MD Collection 6 active fire products.\r\n\r\nThis gridded dataset has been derived from the Small Fire Database (SFD) Burned Area pixel product for Sub-Saharan Africa, v1.1 (also available), which covers Sub-Saharan Africa for the year 2016, 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.",
            "keywords": "ESA, CCI, Grid, Burned Area, Fire Disturbance, Climate Change, GCOS Essential Climate Variable",
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            "doiPublishedTime": "2019-02-08T14:51:09",
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            "title": "UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080",
            "abstract": "\"Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains 12km data for the United Kingdom, the Isle of Man and the Channel Islands provided on the Ordnance Survey's British National Grid. Further information on this dataset and UKCP18 can be found in the documentation section.",
            "keywords": "UK, Climate, Projections, UKCP18, Regional, Europe, Simulation, Model, Runs",
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            "title": "DEMON: Simulation output from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observations into the Lisflood-FP flood forecast model ",
            "abstract": "This dataset contains simulation results from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observation into Lisflood-FP flood forecast model for the the lower Severn-Avon rivers in the South West United Kingdom. This was run over a 30.6 x 49.8 km (1524 km2) domain, as part of Developing enhanced impact models for integration with next generation NWP and climate outputs (DEMON) project (NE/I005242/1).\r\n\r\nCOSMO-Skymed Synthetic Aperture Radar (CSK-SAR) data were acquired processed and transformed into Water Level Observations (WLOs) by crossing with LiDAR Digital Terrain Model. Data from Environment Agency (EA) rain gauges were used to estimate precipitation and combined with potential evapotranspiration data from the Met Office's Met Office Rainfall and Evapo-transpiration Calculation System (MORECS) to generate forcings within the \"topHSPF\" catchment-scale rainfall-runoff hydrologic model. These were used in tern to generate simulated runoff forecast used as the forcing for the coupled Lisflood-FP v5.9 inundation model. \r\n\r\nCSK-SAR based WLO were assimilated into ensemble simulations using the Lisflood-FP v5.9 model, run with perturbed physics (friction parameters, bathymetric errors) and runoff inputs from the topHSPF hydrologic model",
            "keywords": "DEMON, Synthetic Aperture Radar, Flood forecast, Assimilation, Ensemble Kalman Filter",
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        {
            "ob_id": 26224,
            "uuid": "89a34bc430834422bef1f72e2172e3b9",
            "title": "ACITES: Monthly global surface ozone concentration and ozone dry deposition flux fields from models",
            "abstract": "Monthly global surface ozone concentration and ozone dry deposition flux fields from models participating in the UN/ECE Task Force on Hemispheric Transport of Air Pollution (TF HTAP) intercomparison.  Models were driven by meteorological fields for the year 2001.\r\n\r\nData are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format.",
            "keywords": "ACITES, Atmospheric Chemistry, Ozone, HTAP",
            "publicationState": "published",
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            "dataLineage": "Data are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format. Further details about the HTAP intercomparison are available from http://www.htap.org/ and the original model data can be obtained from: http://join.iek.fz-juelich.de/access",
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            "ob_id": 26225,
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            "title": "ACITES: Land cover data for the Olson and Global Land Cover Facility data sets",
            "abstract": "Model grid cell areas and land cover data for the Olson and Global Land Cover Facility. Data are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format.\r\nThe Olson land cover dataset was developed from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993.\r\nThe Global Land Cover Facility dataset was developed from monthly satellite sensor data of NDVI values for 1987.",
            "keywords": "ACITES, Atmospheric Chemistry, Land Cover",
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            "dataPublishedTime": "2018-10-16T10:24:39",
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            "dataLineage": "Land cover data regridded to the same resolution\r\nas the HTAP model results, approximately 3 x 3 degrees.\r\n\r\n1. The data is in NetCDF format\r\n\r\n2. The area for each 3 x 3 degree grid cell is in area3x3.nc\r\n\r\n3. The land cover data for the Olson and Global Land Cover Facility\r\n   data sets are in:  lc_olson_3x3.nc and lc_umd_3x3.nc\r\n\r\n4. The original Olson land cover data set was obtained from:\r\n   http://acmg.seas.harvard.edu/geos/\r\n\r\n5. The original Global Land Cover Facility data set was obtained from:\r\n   http://www.landcover.org/\r\n\r\n6. See Hardacre et al., Atmos. Chem. Phys., 15, 6419-6436, 2015,\r\n   doi:10.5194/acp-15-6419-2015 for further details on the data\r\n   sets used in this study.",
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            "discoveryKeywords": [
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            ]
        },
        {
            "ob_id": 26227,
            "uuid": "b7953003f065461c9568e3fd9a13460f",
            "title": "ACITES: Monthly ozone observations from European and North American sites and CASTNET data.",
            "abstract": "Monthly surface ozone concentration and ozone dry deposition flux fields from observations in Europe and North America and from CASTNET data saved in NetCDF format.",
            "keywords": "ACITES, Atmospheric Chemistry, Ozone, HTAP",
            "publicationState": "published",
            "dataPublishedTime": "2018-10-16T10:22:14",
            "doiPublishedTime": null,
            "updateFrequency": "",
            "status": "completed",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/26228/?format=api",
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                "volume": 429206,
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50559/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50561/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57905/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57906/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57907/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57908/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57909/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/87814/?format=api"
            ],
            "dataLineage": "1. > o3_observation directory\r\n   \r\n   > SITE_mon_ave.nc\r\n     Monthly average ozone dry deposition flux, surface\r\n     ozone concentration (where available) and ozone deposition\r\n     velocity.\r\n     \r\n\r\n2. > castnet_data directory\r\n\r\n   > CASTNET_mon_ave_SITE.nc\r\n     Monthly average ozone dry deposition flux, surface ozone\r\n     concentration and ozone deposition velocity for each year that \r\n     observations were available. The ozone dry deposition flux is\r\n     calculated. Note that data was not necessarily available for all\r\n     of the years between 1987-2014.",
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            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 03.3",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54643/?format=api",
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            "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project.\r\nThis dataset forms part of the v03.3 Soil Moisture CCI data (doi:10.5285/b810601740bd4848b0d7965e6d83d26c. http://dx.doi.org/10.5285/b810601740bd4848b0d7965e6d83d26c )",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109717/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109719/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/110049/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/110050/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/110051/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/110052/?format=api",
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        {
            "ob_id": 26234,
            "uuid": "f77cbcfbb6214448aebaa2119d829692",
            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 04.2",
            "abstract": "The Soil Moisture CCI 'Active' dataset  is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v04.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014",
            "keywords": "ESA, Soil Moisture, CCI, Active",
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        {
            "ob_id": 26236,
            "uuid": "dd3da2570363429791b51120bdd29c02",
            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 05.2",
            "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.\r\n\r\nThe v05.2 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070",
            "keywords": "ESA, Soil Moisture, CCI, Active",
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            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 05.2",
            "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v05.2 COMBINED product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070",
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            "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v05.2 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070",
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