Regularities of soil temperature changes during the period with snow cover in modern climatic conditions of the Eurasian Subarctic

• Published in: Journal of the Belarusian State University. Geography and Geology
• Main Author: Lev M. Kitaev
• Format: Article in Journal/Newspaper
• Language: Belarusian; English; Russian
• Published: Belarusian State University 2021
• Subjects: snow thickness; air temperature; soil temperature; spatial distribution; long-term variation; Geography (General); G1-922; Geology; QE1-996.5; Subarctic; Siberia
• Online Access: https://doi.org/10.33581/2521-6740-2021-1-13-22; https://doaj.org/article/c21d22d7130540208f97709bc29b6464

The influence of snow cover on the dynamics of soil temperature in the modern climatic conditions of the Eurasian Subarctic was investigated through a quantitative assessment of the features of the seasonal and long-term variation of parameters. Seasonal and long-term values of soil temperature for stable snow period decrease from west to east: a decrease of snow thickness and air temperature from west to east of Eurasia leads to a weakening of the heat-insulating properties of the snow cover with a significant decrease in regional air temperatures. With the emergence of a stable snow cover, the soil temperature seasonal and long-term standard deviation sharply decreases compared to the autumn and spring periods. With the appearance of snow cover, the soil temperature standard deviation drops sharply compared to the autumn and spring periods. An exception is the northeast of Siberia: here, a relatively small thickness of snow determines a noticeable dependence of the course of soil temperature on the dynamics of surface air temperature. There are no significant long-term trends in soil temperature due to its low variability during winter period. Analysis of the course of the studied characteristics anomalies showed an insignificant and non-systematic number of their coincidences. Currently, we have not found similar research results for large regions. The revealed patterns can be used in the analysis of the results of monitoring the state of the land surface, in the development of remote sensing algorithms, in the refinement of predictive scenarios of environmental changes.