Increasing Snow–Soil Interface Temperature in Farmland of Northeast China from 1979 to 2018

• Main Authors: Xiuxue Chen, Xiaofeng Li, Lingjia Gu, Xingming Zheng, Guangrui Wang, Lei Li
• Format: Article
• Language: English
• Published: MDPI AG 2021-09-01
• Series: Agriculture
• Subjects: snow cover; snow–soil interface temperature; climate change; SNTHERM; Northeast China
• Online Access: https://www.mdpi.com/2077-0472/11/9/878

The presence of seasonal snow cover in the cold season can significantly affect the thermal conditions of the ground. Understanding the change of the snow–soil interface temperature (<i>T_SS</i>) and its environmental impact factors is essential for predicting subnivean species changes and carbon balance in future climatic conditions. An improved Snow Thermal Model (SNTHERM) is employed to quantify <i>T_SS</i> in farmland of Northeast China (NEC) in a 39-year period (1979–2018) firstly. This study also explored the variation tendency of <i>T_SS</i> and its main influencing factors on grid scale. The result shows that annual average <i>T_SS</i> and the difference between <i>T_SS</i> and air temperature (<i>T_DSSA</i>) increased rapidly between 1979 and 2018 in the farmland of NEC, and we used the Mann–Kendall test to further verify the increasing trends of <i>T_SS</i> and <i>T_DSSA</i> on aggregated farmland of NEC. The correlation analysis showed that mean snow depth (<i>M_SD</i>) is the most pivotal control factor in 95% of pixels and <i>T_DSSA</i> increases as <i>M_SD</i> increases. Snow depth can better predict the change of <i>T_SS</i> in deep–snow regions than average winter temperature (<i>T_SA</i>). The results of this study are of great significance for understanding the impact of snow cover on the energy exchange between the ground and the atmosphere in the cold climate.