Evolution of the thermal state of permafrost under climate warming in Central Yakutia

• Published in: The Holocene
• Main Authors: Varlamov, Stepan P, Skachkov, Yuri B, Skryabin, Pavel N
• Format: Article in Journal/Newspaper
• Language: English
• Published: SAGE Publications 2019
• Subjects: Active layer thickness; permafrost; Yakutia
• Online Access: http://dx.doi.org/10.1177/0959683619855959; http://journals.sagepub.com/doi/pdf/10.1177/0959683619855959; http://journals.sagepub.com/doi/full-xml/10.1177/0959683619855959

The relevance of the problem under review is explained by the need to study the thermal response of permafrost to the modern climate change. Evolution of the thermal state of grounds has been studied with a view to evaluate the effects of modern climate warming on permafrost in Central Yakutia. The leading method to study this problem is the arrangement and performance of long-term monitoring observations of the permafrost thermal state that enable quantitative evaluation of the thermal response of upper permafrost layers to climatic fluctuations of recent decades. The analysis of long-term records from weather stations in the region has clearly revealed one of the highest increasing trends in the mean annual air temperature in northern Russia. Quantitative relationships in the long-term variability of ground thermal parameters, such as ground temperature at the bottom of the active layer, at the bottom of the annual heat exchange layer, and active thaw depth, have been established. The thermal state dynamics of the annual heat exchange layer under climate warming indicates that both warm and cold permafrost are thermally stable. Short-term variability of the snow accumulation regime is the main factor controlling the thermal state of the ground in permafrost landscapes. The active-layer thickness is characterized by low interannual variability and exhibits little response to climate warming, with no statistically meaningful increasing or decreasing trend. The results of ground thermal monitoring can be extended to similar landscapes in the region, providing a reliable basis for predicting heat transfer in natural landscapes.