A Toolkit for Snow-Cover Area Calculation and Display Based on the Interactive Multisensor Snow and Ice Mapping System and an Example for the Tibetan Plateau Region

Abstract

This research develops a toolkit for snow-cover area calculation and display (SACD) based on the Interactive Multisensor Snow and Ice Mapping System (IMS). The paper uses the Tibetan Plateau region as an example to describe the toolkit’s method, results, and usage. The National Snow and Ice Data Center (NSIDC) provides to the public IMS a well-used system for monitoring the snow and ice cover. The newly developed toolkit is based on a simple shoe-lace formula for a grid box area on a sphere and can be conveniently used to calculate the total area of snow cover given the IMS data. The toolkit has been made available as an open source Python software on GitHub. The toolkit generates the time series of the daily snow-covered area for any region over the Northern Hemisphere from 4 February 1997. The toolkit also creates maps showing snow and ice coverage with an elevation background. The Tibetan Plateau (TP) region [Formula: see text]–[Formula: see text]N)[Formula: see text][Formula: see text]–[Formula: see text]E) is used as an example to demonstrate our work on SACD. The IMS products at 24, 4, and 1[Formula: see text]km resolutions include each grid’s latitude and longitude coordinates that are used to calculate the grid box’s area using the shoe-lace formula. The total TP area calculated by the sum of the areas of all the grid boxes approximates the true spherical TP surface area bounded by [Formula: see text]–[Formula: see text]N) [Formula: see text]–[Formula: see text]E) with a difference 0.046% for the 24[Formula: see text]km grid and 0.033% for the 4[Formula: see text]km grid. The differences in the snow-cover area reported by the 24[Formula: see text]km and 4[Formula: see text]km grids vary between [Formula: see text]% and 6.24%. The temporal variations of the daily TP snow cover are displayed in time series from 4 February 1997 to present with 4[Formula: see text]km and 24[Formula: see text]km resolutions.