The surface temperature of the reservoir is a significant characteristic of the state of the lake ecosystem and one of the most important parameters, allowing to identify climatic changes. The purpose of this research was to study the peculiarities of spatial-temporal distribution of the temperature on the surface of Lake Hovsgol useing remote sensing data from satellites so as remote sensing is an indispensable tool to study large inland water bodies, including Lake Hovsgol with water area of 2, 67 thousand square kilometres. In the course of the present study a series of maps of water surface temperature of Lake Hovsgol during the open water period according to AVHRR (Advanced Very High Resolution Radiometer) data from 1998 till 2015 was composed, intra-annual and interannual variability in temperature distribution on the surface of the lake was studyed and it was found that the highest interannual variability of Lake Hovsgol surface temperature was observed in August, when the maximum warming of the surface of the lake was occurred. The impact of the most significant factors on the formation of the maximum temperature values on the surface in exposed parts of Lake Hovsgol was analyzed. With the use of reanalysis data of NCEP/NCAR (The National Centers for Environmental Prediction / The National Center of Atmospheric Research) it was shown that the relationship of maximum temperatures of water surface in the exposed parts of the water bodies with surface air temperature averaged for the month preceding the observed maximum temperature of the water surfaces for Lake Hovsgol was determined as high with the correlation coefficient of 0,61. The relationship of maximum water temperatures with the timing of the final disappearance of all ice on Lake Hovsgol was described as moderate negative with the value of the correlation coefficient of -0,47. Using the water surface temperature distribution maps of Lake Hovsgol the localization and characteristics of the thermal bar and pelagic upwelling in the lake and their interannual variability for the period 1998–2015 were also defined, the factors affecting the character of these dynamic phenomena were studied.

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