Here, we describe and extensively validate snow cover retrieval from historical 1-km AVHRR data using a stable snow detection algorithm, which allows consistent snow sampling across all AVHRR sensors. As a new asset, a pixel-wise probability map based on logistic regression is provided for each snow mask. The spatial and seasonal validation includes a comparison to MOD10A1 and webcam imagery. In addition, the influence of acquisition geometry and the sensor-to-sensor consistency have been investigated using LANDSAT TM data and a snow climatology based on long-term station data.
We conclude that the snow detection algorithm tested allows for a 1-km snow extent climatology to be generated from the 25-year full-resolution AVHRR data archived at the University of Bern with favorable accuracy and stability. Given the importance of mountainous regions for climate change studies, this satellite-based data set could become an important tool for assessing environmental changes in the European Alps.