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Seasonal snow is an important component of the global climate system. It is highly variable in space and time and sensitive to short term synoptic scale processes and long-term climate-induced changes to temperature and precipitation. Current snow products derived from different algorithms applied to various satellite data show significant discrepancies in extent and snow mass, a major source of uncertainty for monitoring and climate model verification. The ESA CCI+ Programme addresses seasonal snow as one of nine Essential Climate Variables derived from satellite data. In the first phase of the snow_cci project (2018-2021), reliable and fully validated processing lines for the generation of snow climate data records were developed and implemented. Homogeneous multi-sensor time series of daily snow extent and snow water equivalent with global coverage were generated. Using GCOS guidelines, the product requirements for these parameters are assessed and consolidated using workshops and other engagement with users dealing with different climate applications. The retrieval algorithms for fractional snow extent provide consistent daily products for snow viewable from space (viewable snow) and snow on the surface corrected for forest masking (snow on ground) with global coverage. Input data are medium resolution optical satellite imagery (AVHRR-2/3, A/ATSR-2, MODIS, SLSTR) from 1982 to present. For the snow_cci Climate Research Data Package version 2, an iterative development cycle was implemented to improve and homogenise the snow extent products from different sensors. Independent validation of the snow extent …