Abstract
Abstract. Satellite data are used to study water balance in large river basins in the East European Plain. For this purpose, the accuracy of estimates of snow water equivalent (SWE) based on microwave remote sensing data was evaluated through the comparison of these data with SWE measurements in open and forested areas. The errors of the SWE estimates, evaluated as their relative root-mean-square deviations from the measured values, are maximal in the Northern Dvina basin (53%); for the Oka and Don river basins, the errors are 35 and 33%, respectively. The main problems of remote sensing for northern river basins occur due to the thick canopy and the high snowpack, whose height exceeds the penetration depth. For the southern regions and midland river basins, a priority problem is due to the presence of liquid water in the snowpack during thaws.
Highlights
Seasonal snow cover is one of the most widespread and dynamic natural objects and a powerful climate-forming factor
After general and primary comparison of the ground-based data from the meteorological stations with corresponding pixels of the remote sensing data raster, it was decided to average the data within the boundaries of river watersheds, which is more suitable for hydrological purposes
The aim of the study is spatial–temporal analysis of the available microwave data of passive remote sensing and the estimation of whether the passive microwave remote sensing can be used for studying snow cover in European Russia
Summary
Seasonal snow cover is one of the most widespread and dynamic natural objects and a powerful climate-forming factor. With the technological developments in the sphere of Earth surface and land cover observations in recent decades, the use of remote sensing to determine snow characteristics is under intensive investigation. Because higher frequencies are more sensitive to the grain size, the brightness temperature at these frequencies (e.g. 37 GHz) decreases more than that at lower frequencies (e.g. 18 GHz), so the difference between them will increase with snow depth until a saturation point is reached. Based on this concept, several SWE estimation algorithms have been developed for passive microwave observations. The estimation was carried out for the period from 2002 until 2010 with the use of remote sensing SWE data from the National Snow and Ice Data Center through their comparison with ground-based data from meteorological stations
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