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Arid Land Geography ›› 2021, Vol. 44 ›› Issue (5): 1299-1308.doi: 10.12118/j.issn.1000–6060.2021.05.11

• Earth Surface Process • Previous Articles     Next Articles

Spatio-temporal distribution and variation characteristics of annual maximum land surface temperature in China during 2003-2018

WANG Liping1,2(),DUAN Sibo2(),ZHANG Xiaoyu1,YU Yanru2   

  1. 1. School of Environment and Resources, Shanxi University, Taiyuan 030006, Shanxi, China
    2. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2020-08-18 Revised:2021-04-06 Online:2021-09-25 Published:2021-09-22
  • Contact: Sibo DUAN E-mail:wlpn123@163.com;duansibo@caas.cn

Abstract:

Land surface temperature (LST) is a very important environmental factor that impacts the energy and water exchange between the atmosphere and ecosystems. Research on China’s climate change in the context of global climate change is of great significance for global and Chinese food security as well as the sustained and stable development of the social economy. Compared with surface temperature data obtained via thermal infrared remote sensing, information regarding the maximum surface temperature is of increased significance as it removes the influence of clouds and rain. The annual variation of the maximum surface temperature is relatively stable; however, it is highly sensitive to changes in land use, drought, and heat waves. This study uses moderate resolution imaging spectroradiometer (MODIS) surface temperature data and normalized difference vegetation index (NDVI) data to obtain the annual maximum surface temperature using the maximum value synthesis method. On the basis of the MODIS LST data from 2003 to 2018, the temporal and spatial distribution and variation characteristics of annual LST maxima in China were analyzed using techniques including the climate trend rate and linear correlation coefficient, and regional analyses were conducted according to the agricultural climate regionalization of China. The correlation between the annual maximum change of the LST and land cover types in China is established. The correlation between the annual maximum LST and the maximum NDVI in the regions with significant trend changes is studied, and the factors that influence the annual maximum LST change in China are investigated. The results obtained indicate the following: (1) The annual maximum value of China’s surface temperature presents a higher spatial distribution characteristic in the north and lower in the south; its highest value was observed in the Turpan Basin of Xinjiang. (2) According to the analysis of the spatial distribution of the annual maximum surface temperature in China’s climate zoning, the annual maximum surface temperature is the highest in the temperate continental climate zone, with an average of 325.39 K over 16 years. The second hottest region is the temperate monsoon climate zone, where the average annual maximum surface temperature over 16 years is 312.84 K. The plateau mountain, subtropical monsoon, and tropical monsoon climate zones have lower values of annual maximum surface temperature. The spatial distribution pattern of the annual maximum surface temperature is related to the type of surface cover. (3) During the period of 2003-2018, the temporal variation of the annual maximum surface temperature in China showed a slight cooling trend, with a climate tendency rate of -0.06 K·(10a)-1; the area in which a cooling trend was observed accounted for 50.45% of the country’s total area. (4) The climate tendency rate of the annual maximum surface temperature and the linear correlation coefficient are high in the west and low in the east, and the warming trend in the west is clearer than that in the east. Some areas showed a significant cooling trend; these areas included central northern China, southern China, and the edge of the Tarim Basin. The cooling in these areas is related to changes in the vegetation cover. The maximum surface temperature contains a large amount of geographic information, which reflects the impact of human activities on the geographic environment and provides theoretical support for decisions related to transforming the geographic environment.

Key words: annual maximum surface temperature, time series, temporal and spatial variation, MODIS data