Spatio-temporal Distribution Of Near Surface Temperature And Its Influencing Forces Of China In Recent 20 Years

Near surface temperature（NST）have been increasing since the late 19th century.Understanding how and why temperatures have changed is critical for understanding the current global warming situation.China has showed the same increasing trend and even exceeded natural variability in recent decades.However,the underlying processes and key driving forces of the long-term warming are diverse.This study,from the perspectives of a spatio-temporal distribution on trend of climate variability,explored the characteristics of multi-year averages of NST（MAT）,seasonal-year average of near surface temperature（SAT）and trend of annual NST（TAT）in five climate sub-regions of china from 2003 to 2022.The driving forces were then quantified in each sub-region by constructing a WOA-RF model based on these forces including the downward shortwave radiation（SR）,specific humidity（SH）,Normalized Difference Vegetation Index（NDVI）,carbon dioxide column concentration in the middle troposphere（CO₂）,population density（DP）,Digital Elevation Model（DEM）and Night-light（NL）.The main results were as follows:（1）We found that the spatio-temporal distribution of MAT of southern China is higher than the northern part and varies from 6.81℃to 21.48℃,except in the Tibetan plateau.Compared with regions along the same latitude,the tibetan plateau is lower and is influenced by the topographic driver.For TAT,nearly 83.1%of pixels signaled a warming trend,showing that the warming phenomenon of Chinese climate is unequivocal.The warming trend of different climate sub-regions from highest to lowest changer are:0.03℃/decade（plateau mountain climate region）>0.023℃/decade（subtropical monsoon climate region）>0.021℃/decade（temperate monsoon climate region）>0.019℃/decade（temperate continental climate region）>0.014℃/decade（tropical monsoon climate region）.Moreover,we discovered warming in the plateau（0.068℃/decade）is higher than in the plain（0.03℃/decade）,which shows that climate warming is more significant in higher altitude areas.（2）The seasonal mean of near surface temperature in China from 2003 to 2022showed a spatial distribution characteristic of high in the south and low in the north in spring,autumn,and winter.In summer,the near surface temperature has a small temperature difference among various climatic zones,that is,except for the plateau and mountainous climatic regions,it presents a spatial distribution characteristic of universal high temperature.In the past two decades,there has been a significant spatial difference in the tendency rate of near-surface seasonal average temperature among various climatic zones;In spring,in the temperate continental climate zone and the temperate monsoon climate zone,the warming trend of the climate tendency rate of the near surface temperature is relatively obvious,while the other seasons have a cooling trend;The climate tendency rate of near surface temperature in the plateau mountainous climate region shows a more obvious upward trend in summer,autumn,and winter.（3）The multi-year mean atmospheric specific humidity in China from 2003 to2022 showed a spatial distribution characteristic of high in the south and low in the north,which was highly consistent with the spatial distribution characteristics of the multi-year mean near-surface temperature.The normalized vegetation index（NDVI）presents a spatial distribution characteristic of decreasing from southeast to northwest.The Yangtze River Delta urban agglomeration located in the eastern region of China and the Beijing Tianjin Hebei urban agglomeration present a trend of decreasing NDVI,which is related to the high development of urbanization.The climate tendency rate of tropospheric CO₂column concentration values shows a significant increasing trend nationwide（ppmv/a>0）.The climate propensity rate of short-wave downward radiation（SR）shows a spatial distribution characteristic of high in the north and low in the men.The climate propensity rate of short-wave downward radiation has a more obvious increasing trend in the plateau mountainous climate region.（4）Based on the results comparing the WOA-RF value with the RF value,no matter the result of MAT or TAT,the performance of WOA-RF model was better than that of RF model.The WOA-RF model was optimized to quantitatively explore the relationship between NST and driving forces.（5）The dominant driving forces of MAT indicated that SH had the greatest effect on the national scale,the tropical monsoon climate region,the subtropical monsoon climate region and the plateau mountain climate region.CO₂played an important role in the temperate monsoon climate region and temperate continental climate region.The TAT rank identified key driving forces in China’s spatial variation,and CO₂had the greatest effect on TAT in the national scale,subtropical monsoon climate region,temperate monsoon climate region and the plateau mountain climate region as well as ranking second as a driving force in the tropical monsoon climate region and subtropical monsoon climate region.Growth rate of CO₂ranks either first or second of each climate sub-regions,and growth rate of CO₂also ranks first of the whole country for TAT.