Asymmetric effects of soil moisture on mean daily maximum and minimum temperatures over eastern China

Changes in mean daily maximum (Tmax) and minimum (Tmin) surface air temperatures and the associated climate extreme events have more substantial impacts on both human society and the natural environment than does the mean temperature. Soil moisture can influence surface air temperature mainly through its control on the partitioning of sensible and latent heat fluxes. This study statistically investigates the asymmetric effects of soil moisture on Tmax and Tmin over eastern China during growing season (March-November) using Global Land Data Assimilation System (GLDAS) soil moisture and observational temperatures. Feedback parameters based on lagged covariance ratios are computed to quantify soil moisture feedbacks on surface air temperature in the observations. The results show that soil moisture exerts different effects on surface air temperature in spring [March-May (MAM)], summer [June-August (JJA)] and fall [September-November (SON)], and has an asymmetric effects on Tmax and Tmin. In spring and summer, significantly negative feedbacks on temperature dominate the transition zones between dry and wet climates of northern China and Mongolia, accounting for 5-20% of the total variance. Soil moisture is found to have much stronger effects on Tmax than Tmin in spring. While, positive feedbacks are limited to small areas of southeast China in spring, and some areas of northeast China in summer. In contrast, in fall soil moisture has much stronger effects on Tmin than Tmax with significantly positive feedbacks over the areas of northeast China to northern China where 5-20% of the total Tmin variance are explained. The asymmetric effects of soil moisture on Tmax and Tmin estimated from GLDAS are generally consistent with those from the observational soil moisture in Climate Prediction Center global soil moisture monitoring product. These findings emphasize the importance of soil moisture feedbacks on surface air temperature during growing season, and would provide the help for seasonal temperature forecasting.