EARTH SCIENCE>CLIMATE INDICATORS>CRYOSPHERIC INDICATORS>SNOW COVER
CEDA
CEDA Data Catalogue Page - Detail and access information for the resource
Snow CCI key documents - No further details.
MetsÃ¤mÃ¤ki, S., Pulliainen, J., Salminen, M., Luojus, K., Wiesmann, A., Solberg R. and Ripper, E. 2015. Introduction to GlobSnow Snow Extent products with considerations for accuracy assessment. Remote Sensing of Environment, 156, 96â108 - No further details.
ESA Land Cover CCI project team; Defourny, P. (2019): ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 2.0.7. Centre for Environmental Data Analysis, 13.04.2021. - No further details.
High-Resolution Global Maps of 21st-Century Forest Cover Change. - No further details.
ESA Climate Change Initiative website - No further details.
Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. âHigh-Resolution Global Maps of 21st-Century Forest Cover Change.â Science 342 (15 November): 850â53 - No further details.
This dataset contains Daily Snow Cover Fraction (snow on ground) from AATSR, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction on ground (SCFG) indicates the area of snow observed from space on land surfaces, in forested areas corrected for the transparency (âtransmissivityâ) of the forest canopy. The SCFG is given in percentage (%) per grid cell. The global SCFG product is available at 0.01Â° grid size (about 1 km) for all land areas, excluding Antarctica and Greenland ice sheet. The coastal zones of Greenland are included. The SCFG time series provides daily products for the period 2002 â 2012. The SCFG product is based on Advanced Along-Track Scanning Radiometer (AATSR) data aboard the Envisat satellite. The retrieval method of the snow_cci SCFG product from AATSR data has been further developed and improved based on the ESA GlobSnow approach (MetsÃ¤mÃ¤ki 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) (MetsÃ¤mÃ¤ki 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 Âµm, and an emissive band centred at about 10.85 Âµm. 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 SCFG retrieval method is applied. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include the usage of a global forest transmissivity map developed and created within snow_cci based on forest density from Hansen et al. (2013) and forest type layers from Land Cover CCI (Defourny 2019). The forest transmissivity map provides the local transparency of the forest canopy and is applied or estimating the fractional snow cover on the ground.Permanent 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 SCFG 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.The SCFG 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.The Norwegian Computing Center (Norsk Regnesentral, NR) is responsible for the SCFG 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.There are a few days without any AATSR acquisitions in the years 2002, 2003, 2004, 2006, 2008, 2010 and 2012.
ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction â snow on ground (SCFG) from AATSR (2002 â 2012), version 1.0 2002