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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 3, pp. 31-40

Validation of daily Snow Depth FEWS NET product over River Ural basin on snow depth meteorological observations

A.G. Terekhov 1, 2 , N.I. Ivkina 2 , N.N. Abayev 2, 3 , A.G. Yeltay 3 , Z.M. Yegemberdyeva 1, 4 
1 Institute of Information and Computing Technology MES RK, Almaty, Kazakhstan
2 RSE Kazhydromet, Almaty, Kazakhstan
3 al-Farabi Kazakh National University, Almaty, Kazakhstan
4 Almaty University of Power Engineering and Telecommunications, Almaty, Kazakhstan
Accepted: 28.04.2020
DOI: 10.21046/2070-7401-2020-17-3-31-40
Snow depth is an important climatic characteristic of the Russian Federation. However, the Russian meteorological observational network is quite rare and instrumental measurements of snow depth over steppe and forest-steppe zones are often hampered by strong winds. This determines the interest in different estimates of snow cover parameters based on satellite data. Recently introduced for Central Asia, the product Snow Depth of the Famine Early Warning System Network (Snow Depth FEWS NET) with a resolution of 0.044×0.044° is updated daily, and the archive since 2000 covers part of the territory of Russia south of 56° N. The product documentation does not contain references to validation results for ground data in various parts of the coverage area. In the work, we tested the Snow Depth FEWS NET product for the River Ural basin. The validation used the meteorological data of 2005–2018 from five weather stations in the Russian part of the River Ural basin: Verkhneuralsk (WMO ID-28833), Magnitogorsk (WMO ID-28838), Kizilskoe (WMO ID-28939), Energetik (WMO ID-35038) and Orsk (WMO ID-35138). About 5,600 ground-based snow height measurements were compared with more than 2,000 daily Snow Depth FEWS NET maps. The Pearson correlation coefficient was 0.702 for separate daily values and 0.997 for multi-year average. But, the Snow Depth FEWS NET values were overestimated by about 28 % and had bias of (+4 cm) relative to meteorological observations. These discrepancies are insignificant and the Snow Depth FEWS NET product can be of interest for snow depth monitoring in the Russian part of the River Ural basin.
Keywords: snow cover height, meteorological observations, Snow Depth FEWS NET, River Ural basin, validation, linear regression
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