Preliminary simulation of spatial distribution patterns of soil thermal conductivity in permafrost of the Arctic

ABSTRACT

The Arctic amplification (AA) has exacerbated permafrost degradation, posing a serious threat to infrastructure security and other areas. Therefore, it is crucial to accurately assess the current status and future changes of permafrost, and reliable soil thermal conductivity (STC) is an important prerequisite for permafrost prediction. However, few methods and products are available for regional-scale STC simulations in permafrost of the Arctic, which lead to greater uncertainty in the simulation of land surface temperatures. This study conducted a preliminary STC simulation based on the XGBoost method. The results show that the average STC during the freezing period is between 0.71∼0.73 W·m⁻¹K⁻¹, and around 0.67 W·m⁻¹K⁻¹ during the thawing period; The variation of STC between the thawing and freezing period ranged from −0.34–0.23 W·m⁻¹K⁻¹, with an average value of −0.02 W·m⁻¹K⁻¹; The areas where STC of the thawing period is smaller than that of the freezing period are mainly concentrated in the marginal areas near the sea on the continental side of North America and in the typical areas of plains, lowlands, and plateaus on the continental side of Eurasia. The areas with large STC during the thawing period are concentrated in mountainous areas.

KEYWORDS:

• Permafrost
• soil thermal conductivity
• Arctic
• spatial pattern
• machine learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Key Research and Development Program of China: [grant no 2020YFA0608502]; National Natural Science Foundation of China [grant no 42071093]; The State Key Laboratory of Cryospheric Science [grant no SKLCSZZ-2023]. The National Natural Science Foundation of China [grant no 41961144021, 41941015, 32061143032, 41671070]; Youth Science and Technology Fund Plan of Gansu Province [grant no 21JR7RA063]; Gansu Province Science and Technology Plan Project [grant no 22JR5RA061].