The dataset provides daily snow thickness distribution data in China from October 24, 1978 to December 31, 2012, with a spatial resolution of 25km. The original data used to retrieve the snow depth data set are from SMMR (1978-1987), SSM / I (1987-2008) and AMSR-E (2002-2012) daily passive microwave brightness data processed by the National Snow and Ice Data Center (NSIDC). Because the three sensors are installed on different platforms, there is a certain system inconsistency in the data obtained. By simultaneous interpreting the brightness temperature of different sensors, the consistency of brightness temperature data is increased. Then we use Dr. chetao's modified algorithm based on Chang algorithm to retrieve snow depth in China. Refer to "data description document" for specific inversion methods.
The dataset consists of two projection methods: ease grid and longitude latitude, which are put into two different folders respectively: ease grid rar (data only in 2010) and lon lat RAR. Two kinds of projection data are packed year by year, and the file naming method is: sensor name shorthand + year, for example, sr1985 in ease grid pur directory represents the snow depth of 1985 retrieved with SMMR brightness temperature data; si1990 represents the snow depth of 1990 retrieved with SSM / I brightness temperature data; ae2005 represents the snow depth of 2005 retrieved with AMSR-E brightness temperature data, and the projection mode of these data is ease grid. In the lon lat pur directory, the above dataset names are interpreted the same, except that the projection mode is latitude and longitude projection. Please refer to the data documentation for detailed data description.
The original data used to retrieve the snow depth data set are from SMMR (1978-1987), SSM / I (1987-2008) and AMSR-E (2002-2012) daily passive microwave brightness data processed by the National Snow and Ice Data Center (NSIDC).
Because the three sensors are installed on different platforms, there is a certain system inconsistency in the data obtained. By simultaneous interpreting the brightness temperature of different sensors, the consistency of brightness temperature data is increased. Then we use Dr. chetao's modified algorithm based on Chang algorithm to retrieve snow depth in China. Refer to "data description document" for specific inversion methods.
Data set quality control through strict manual audit
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