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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, 2024, Vol. 21, No. 6, pp. 224-232

Dynamics of precipitation amounts in Tyva Republic based on ground and global data

Kh.B. Kuular 1 , A.F. Chuldum 1 
1 Tuvinian Institute for Exploration of Natural Resources SB RAS, Kyzyl, Russia
Accepted: 15.11.2024
DOI: 10.21046/2070-7401-2024-21-6-224-232
For poorly studied mountainous regions, global climate data of the Earth’s surface are available. However, their applicability for the mountains of Southern Siberia has not yet been sufficiently explored. In this work, we present a map of the distribution of annual precipitation totals based on ERA5-Land Daily (European ReAnalysis 5-Land Daily) reanalysis data for Tyva Republic, located in the center of Asia, and assess the trend of dynamics over a 62-year period (1961–2023). For the digital elevation model (DEM) of the Tyva Republic, ALOS (Advanced Land Observing Satellite) data with a resolution of 30 m are used. The study provides a comparative analysis of precipitation amounts based on meteorological station data and the results of ERA-5-Land reanalysis. Additionally, precipitation amounts are analyzed across five altitude levels. According to the reanalysis data, the highest precipitation amount (averaging from 273 to 458.8 mm) is concentrated at the highest altitude level of 2200 m and above, while the lowest precipitation amount (averaging 88.5–144.0 mm) occurs at altitudes of 500–1000 m. The results obtained are acceptable for mountainous basin areas, as they demonstrate significant differentiation of precipitation amounts across all altitude levels, taking into account regional differences. Global climate data become a valuable source of information for mountainous regions with sparse data or a lack of meteorological stations. The role of reanalysis data for mountainous areas will increase with further improvements in conjunction with remote sensing data.
Keywords: trends in annual precipitation amounts, meteorological stations data, reanalysis data, altitude levels
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