Observation Instance

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{
    "ob_id": 33172,
    "uuid": "d7773cb976d64b1c900a518773428df6",
    "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction – viewable snow (SCFV) from AATSR (2002 – 2012), version 1.0",
    "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from AATSR, produced by the Snow project of the ESA Climate Change Initiative programme.  \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at 0.01° grid size (about 1 km) for all land areas, excluding Antarctica and Greenland ice sheet. The coastal zones of Greenland are included. \r\nThe SCFV time series provides daily products for the period 2002 – 2012. \r\n\r\nThe SCFV product is based on Advanced Along-Track Scanning Radiometer (AATSR) data aboard the Envisat satellite. \r\n\r\nThe retrieval method of the snow_cci SCFV product from AATSR data has been further developed and improved based on the ESA GlobSnow approach (Metsämäki et al. 2015) and complemented with a pre-classification module. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al. 2015), defined as SCDA2.3. All cloud-free pixels are then used for the snow extent mapping, using spectral bands centred at about 659 nm and 1.61 µm, and an emissive band centred at about 10.85 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud-free pixels which are clearly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include adaptation of the retrieval method for mapping in forested areas the SCFV.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the grid size of the SCFV product. Water areas are masked if more than 30% of the grid cell is classified as water, permanent snow and ice areas are masked if more than 50% is identified as such areas in the aggregated map. The product uncertainty for observed land areas is provided as unbiased root mean square error (RMSE) per grid cell in the ancillary variable.\r\n\r\nThe SCFV product aims to serve the needs of users working with the cryosphere and climate research and monitoring activities, including the assessment of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nThe Norwegian Computing Center (Norsk Regnesentral, NR) is responsible for the SCFV product development and generation from AATSR data. The Remote Sensing Research Group of the University of Bern supported the development. ENVEO IT GmbH developed and prepared all auxiliary data sets used for the product generation.\r\n\r\nThere are a few days without any AATSR acquisitions in the years 2002, 2003, 2004, 2006, 2008, 2010 and 2012.",
    "keywords": "ESA, CCI, Snow, Snow Cover Fraction",
    "publicationState": "citable",
    "dataPublishedTime": "2023-08-08T13:18:27",
    "doiPublishedTime": "2023-08-08T13:18:16.922994",
    "updateFrequency": "notPlanned",
    "status": "completed",
    "result_field": {
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        "dataPath": "/neodc/esacci/snow/data/scfv/AATSR/v1.0",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 63476170290,
        "numberOfFiles": 3558,
        "fileFormat": "NetCDF"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11080/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2614/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6021/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6022/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/32072/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62645/?format=api",
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    ],
    "dataLineage": "The snow_cci SCFV products from AATSR are based on the AATSR version 4.0 (2021) reprocessed dataset (which is conformant with SLSTR), provided by ESA.\r\n\r\nThe snow_cci SCF processing chain for AATSR includes the masking of clouds, the identification of clearly snow-free areas, and the retrieval of snow cover fraction per grid cell for all remaining observed grid cells. Finally, permanent snow and ice areas as well as water bodies are masked in the SCFV products using the corresponding classes from the Land Cover CCI map of the year 2000 as auxiliary layers. All SCFV products are prepared according to the CCI data standards.\r\n\r\nThe processing chain was developed by Norsk Regnesentral (Norwegian Computing Center, NR), and the processing took place on the Fram supercomputer operated by UNINETT Sigma2 AS (Sigma2, The Norwegian e-infrastructure for Research & Education). \r\n\r\nData were supplied for archiving at the Centre for Environmental Data Analysis (CEDA) as part of the CCI Open Data Portal project.",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [
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    "projects": [
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    "observationcollection_set": [],
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    "procedureAcquisition": null,
    "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/39619/?format=api",
    "procedureComputation": null,
    "permissions": [
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            "accessConstraints": null,
            "accessCategory": "public",
            "accessRoles": null,
            "label": "public: None group",
            "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_snow_terms_and_conditions.pdf",
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