AbstractThe relationships between the variables at different times are crucial in climate prediction. This study explores the lead‐lag correlations between monthly near‐surface air temperatures, and analyzes the associated influencing factors and processes using mathematical physics equations and statistical methods, based on monthly observations and ERA5 reanalysis data spanning from 1979 to 2013. The results reveal high lead‐lag correlations of near‐surface air temperatures in the middle and lower reaches of the Yangtze River basin, characterized by high frequency and intensity of heatwaves. The lead‐lag correlations between near‐surface temperatures are mainly due to the lead‐lag relationships between soil temperatures (STs). Current and accumulated net solar radiation, current latent heat flux and antecedent ST of several or many months ago are the main factors affecting the lead‐lag relationships between STs. The processes associated with lead‐lag correlations between STs are triggered by antecedent ST, concurrent and accumulated influence factors, respectively. The anomalies of antecedent ST can lead to the anomalies of current one by the persistence of anomaly signals in soil. The effects of accumulated or concurrent influential variables on the lead‐lag correlations between STs are attributed to the signals similar to antecedent STs in these influential variables, and the signals may arise from the response of atmosphere to land or ocean forcing. Moreover, the use of reanalysis data increases the uncertainty of the results. The study reveals influential factors and possible physical processes associated with lead‐lag correlations between near‐surface temperatures, which is helpful for understanding lead‐lag relationship between land surface and the atmosphere.
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