Quantitative Changes in the Surface Frozen Days and Potential Driving Factors in Northern Northeastern China

Dongyu Yang, Yang Xiao, Miao Li (), Haoran Man, Dongliang Luo, Shuying Zang and Luhe Wan
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Dongyu Yang: College of Geographical Science, Harbin Normal University, Harbin 150025, China
Yang Xiao: College of Geographical Science, Harbin Normal University, Harbin 150025, China
Miao Li: College of Geographical Science, Harbin Normal University, Harbin 150025, China
Haoran Man: College of Geographical Science, Harbin Normal University, Harbin 150025, China
Dongliang Luo: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Shuying Zang: College of Geographical Science, Harbin Normal University, Harbin 150025, China
Luhe Wan: College of Geographical Science, Harbin Normal University, Harbin 150025, China

Land, 2024, vol. 13, issue 3, 1-22

Abstract: Surface freezing and thawing processes pose significant influences on surface water and energy balances, which, in turn, affect vegetation growth, soil moisture, carbon cycling, and terrestrial ecosystems. At present, the changes in surface freezing and thawing states are hotspots of ecological research, but the variations of surface frozen days (SFDs) are less studied, especially in the permafrost areas covered with boreal forest, and the influence of the environmental factors on the SFDs is not clear. Utilizing the Advanced Microwave Scanning Radiometer for EOS (AMSRE) and Microwave Scanning Radiometer 2 (AMSR2) brightness temperature data, this study applies the Freeze–Thaw Discriminant Function Algorithm (DFA) to explore the spatiotemporal variability features of SFDs in the Northeast China Permafrost Zone (NCPZ) and the relationship between the permafrost distribution and the spatial variability characteristics of SFDs; additionally, the Optimal Parameters-based Geographical Detector is employed to determine the factors that affect SFDs. The results showed that the SFDs in the NCPZ decreased with a rate of −0.43 d/a from 2002 to 2021 and significantly decreased on the eastern and western slopes of the Greater Khingan Mountains. Meanwhile, the degree of spatial fluctuation of SFDs increased gradually with a decreasing continuity of permafrost. Snow cover and air temperature were the two most important factors influencing SFD variability in the NCPZ, accounting for 83.9% and 74.8% of the spatial variation, respectively, and SFDs increased gradually with increasing snow cover and decreasing air temperature. The strongest explanatory power of SFD spatial variability was found to be the combination of air temperature and precipitation, which had a coefficient of 94.2%. Moreover, the combination of any two environmental factors increased this power. The findings of this study can be used to design ecological environmental conservation and engineer construction policies in high-latitude permafrost zones with forest cover.

Keywords: Northeastern China permafrost zone; surface frozen days; influencing factors; freeze–thaw discriminant function algorithm; Optimal Parameters-based Geographical Detector (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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