ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable (SCFV) from AVHRR (1979 - 2023), version 4.0 2019
type: Dataset
keyword: DIF10
keyword: ESA
keyword: CCI
keyword: Snow
keyword: Snow Cover Fraction
keyword: orthoimagery
keyword: EARTH SCIENCE>CLIMATE INDICATORS>CRYOSPHERIC INDICATORS>SNOW COVER
keyword: EARTH SCIENCE>SPECTRAL/ENGINEERING>INFRARED WAVELENGTHS
keyword: METOP-A
keyword: METOP-B
keyword: METOP-C
keyword: NOAA-10
keyword: NOAA-11
keyword: NOAA-12
keyword: NOAA-14
keyword: NOAA-16
keyword: NOAA-17
keyword: NOAA-18
keyword: NOAA-19
keyword: NOAA-6
keyword: NOAA-7
keyword: NOAA-8
keyword: NOAA-9
keyword: TIROS-N
keyword: AVHRR
keyword: AVHRR-2
keyword: AVHRR-3
keyword: Metop-A
keyword: Metop-B
keyword: Metop-C
keyword: Level 3C
keyword: snow
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description: This dataset contains Daily Snow Cover Fraction of viewable snow from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction viewable (SCFV) indicates the area of snow viewable from space over land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. The global SCFV product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.The SCFV time series provides daily products for the period 1979-2023. The product V4.0 is based on EUMETSAT Fundamental Data Record (FDR) medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the CLARA-A3 cloud product. The retrieval method of the snow_cci SCFV product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by MetsÃ¤mÃ¤ki et al. (2015) and complemented with a pre- and post-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.63 Âµm and 1.61 Âµm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 Âµm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. The following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas…
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