Arid Zone Research ›› 2024, Vol. 41 ›› Issue (5): 765-775.doi: 10.13866/j.azr.2024.05.05

• Weather and Climate • Previous Articles     Next Articles

Simulation of land surface temperature in complex mountainous terrain and the influence of environmental factors: A case study in Daqingshan, Inner Mongolia

ZHAO Lichao1,2(), ZHANG Chengfu1,2(), HE Shuai1,2, MIAO Lin1,2, FENG Shuang1,2, PAN Sihan3   

  1. 1. College of Desert Management, Inner Mongolia Agricultural University, Hohhot 010018, Inner Mongolia, China
    2. Key Laboratory of Desert Ecosystem Protection and Restoration, National Forestry and Grassland Administration, Hohhot 010019, Inner Mongolia, China
    3. Bayannaoer Forestry and Grassland Bureau, Bayannaoer 015000, Inner Mongolia, China
  • Received:2023-12-01 Revised:2024-01-31 Online:2024-05-15 Published:2024-05-29

Abstract:

This study aimed to spatially and temporally characterize not only land surface temperature (LST) in the complex mountainous terrain of Daqingshan, Inner Mongolia but also the environmental factors affecting it. We used the Weather Research and Forecasting Mode (WRF) used to obtain LST data with high temporal and spatial resolution and analyze the variation of mountain influencing factors. The accuracy of the WRF simulated LST (WRF LST) was verified by the observation values of meteorological stations and MODIS LST values, and the relationship between LST and environmental factors was analyzed by the method of comprehensive impact factor analysis and the method of single impact factor analysis. The comprehensive impact factor analysis is based on regional WRF LST and regional environmental factors. Single impact factor analysis achieves the relationship between WRF LST and single environmental factors by fixing other environmental factors. The results revealed that the correlation coefficients between the simulated and observed values were >0.97 (P<0.001) and the spatial correlation with MODIS LST was 0.73 (P<0.05), indicating that WRF has good practicability in mountainous areas. After comprehensive impact factor analysis, it was found the annual WRF LST had the greatest correlation with elevation (R>0.97), followed by temperature at 2 m and water/air mixing ratio at 2 m (R>0.8), vegetation coverage and slope (R>0.3), and other factors. By single impact factor analysis, LST decrease rate with elevation was 0.83 K·(100m)-1, 0.79 K·(100m)-1, 0.80 K·(100m)-1 and 0.32 K·(100m)-1 in spring, summer, autumn and winter, and it increased by -0.05 K, 0.17 K, -0.14 K, and 0.02 K for every 10° increase in slope in spring, summer fall winter, respectively. LST also increased for every 10% increase in vegetation cover by 0.31 K, 1.41 K in summer and winter, and was not correlated with fall. The slope direction and average LST for the four seasons were south>southwest>southeast>west>east>northwest>northeast>north. The 2 m water-air mixing ratio increased logarithmically with LST, while the 2 m air temperature increased exponentially with LST. This study demonstrated that the WRF model can be used to simulate the spatial and temporal distribution of LST in mountainous terrain and analyze the LST relationship in complex mountain environments.

Key words: WRF model, land surface temperature, environmental factors, Daqingshan of Inner Mongolia