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The methods and results of a comparative analysis of the effects of climate changes on the dynamics of the areas of thermokarst lakes over the past 36 years in the Arctic regions on the Yamal, Gydan, and Taimyr peninsulas are considered, the areas of which are 114, 175 and 426 thousand km2, respectively. All three regions are located within the permafrost zone of the Siberian Arctic. Using images of the Landsat 4, 5, 7, and 8 satellites, time series of data on average values of lake areas for the indicated regions were obtained on the basis on averaging areas of lakes over 23 test (key) areas. The total area of the test sites is about 800 km2. Using the ERA5 reanalysis system, time series of data on the mean annual air temperature in these territories have been generated, which show a rise of the temperature over the studied period 1985–2021. A comparison of trends in changes in regional mean areas of lakes and mean annual air temperature shows that with approximately the same rate of the temperature rise on these peninsulas, different trends in the dynamics of the lake areas are observed, which are manifested, on the one hand, in a noticeable reduction in the areas of lakes in the territories of Yamal and Gydan and, on the other hand, in their growth in Taimyr. Air temperature averaged over the period 1985–2021 and coefficients of the linear trend of changes in the lake areas in each of the above regions were compared. The results show that on the territories of Yamal and Gydan, where the lake areas decrease, the mean air temperature for the same period is equal to –8.1±0.9 and –8.9±0.9 °С, respectively. On the Taimyr territory, where the lake areas increase, the mean air temperature is significantly lower: –12.8±0.94 °С. Thus, this makes possible to make a conclusion that these considered regions differ significantly from each other by values of mean air temperature, and respectively, they are characterized by different trends in changes in areas of the thermokarst lakes.
The methods and results of a comparative analysis of the effects of climate changes on the dynamics of the areas of thermokarst lakes over the past 36 years in the Arctic regions on the Yamal, Gydan, and Taimyr peninsulas are considered, the areas of which are 114, 175 and 426 thousand km2, respectively. All three regions are located within the permafrost zone of the Siberian Arctic. Using images of the Landsat 4, 5, 7, and 8 satellites, time series of data on average values of lake areas for the indicated regions were obtained on the basis on averaging areas of lakes over 23 test (key) areas. The total area of the test sites is about 800 km2. Using the ERA5 reanalysis system, time series of data on the mean annual air temperature in these territories have been generated, which show a rise of the temperature over the studied period 1985–2021. A comparison of trends in changes in regional mean areas of lakes and mean annual air temperature shows that with approximately the same rate of the temperature rise on these peninsulas, different trends in the dynamics of the lake areas are observed, which are manifested, on the one hand, in a noticeable reduction in the areas of lakes in the territories of Yamal and Gydan and, on the other hand, in their growth in Taimyr. Air temperature averaged over the period 1985–2021 and coefficients of the linear trend of changes in the lake areas in each of the above regions were compared. The results show that on the territories of Yamal and Gydan, where the lake areas decrease, the mean air temperature for the same period is equal to –8.1±0.9 and –8.9±0.9 °С, respectively. On the Taimyr territory, where the lake areas increase, the mean air temperature is significantly lower: –12.8±0.94 °С. Thus, this makes possible to make a conclusion that these considered regions differ significantly from each other by values of mean air temperature, and respectively, they are characterized by different trends in changes in areas of the thermokarst lakes.
The article discusses the important geoecological problem of predicting the dynamics of thermokarst lakes in the Russian Arctic as intensive sources of natural greenhouse gas emissions, which is considered as one of the factors of current climate change. The purpose of the work is to consider the development of a system for forecasting the dynamics of lake areas using entropy-randomized machine learning algorithms and tools of the NextGIS Web geographic information system. The procedure for processing information to predict the dynamics of lakes is considered. Data from remote measurements of the areas of thermokarst lakes in the Arctic zone of Russia, obtained from Landsat satellite images over the past several decades, and climate data determined by reanalysis of meteorological data for the same period are used as retrospective information for forecasting. The system is implemented on the basis of the NextGIS Web geographic information system, which allows the inclusion of randomized modeling applications using the Python language.
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