Evaluating the Capabilities of Soil Enthalpy, Soil Moisture and Soil Temperature in Predicting Seasonal Precipitation

作     者：Changyu ZHAO Haishan CHEN Shanlei SUN 

作者机构：Key Laboratory of Meteorological Disaster Ministry of Education (KLME)/International Joint Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science and Technology (NUIST) School of Atmospheric Science Nanjing University of Information Science and Technology (NUIST) 

出 版 物：《Advances in Atmospheric Sciences》 (大气科学进展（英文版）)

年 卷 期：2018年第35卷第4期

页      面：445-456页

核心收录：

学科分类：09[农学] 0903[农学-农业资源与环境] 0706[理学-大气科学] 0816[工学-测绘科学与技术] 0825[工学-航空宇航科学与技术] 

基　　金：jointly supported by the National Natural Science Foundation of China (Grant Nos. 41230422 and 41625019) the Special Fund for Research in the Public Interest of China (Grant No. GYHY201206017) the Natural Science Foundation of Jiangsu Province, China (Grant Nos. BK20130047 and BK20151525) the Research Innovation Program for College Graduates of Jiangsu Province (Grant No. KYLX 0823) a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions 

主　　题：seasonal precipitation prediction land surface process soil enthalpy soil moisture soil temperature 

摘      要：Soil enthalpy （H） contains the combined effects of both soil moisture （w） and soil temperature （T） in the land surface hydrothermal process. In this study, the sensitivities of H to w and T are investigated using the multi-linear regression method. Results indicate that T generally makes positive contributions to H, while w exhibits different （positive or negative） impacts due to soil ice effects. For example, w negatively contributes to H if soil contains more ice; however, after soil ice melts, w exerts positive contributions. In particular, due to lower w interannual variabilities in the deep soil layer （i.e., the fifth layer）, H is more sensitive to T than to w. Moreover, to compare the potential capabilities of H, w and T in precipitation （P） prediction, the Huanghe-Huaihe Basin （HHB） and Southeast China （SEC）, with similar sensitivities of H to w and T, are selected. Analyses show that, despite similar spatial distributions of H-P and T-P correlation coefficients, the former values are always higher than the latter ones. Furthermore, H provides the most effective signals for P prediction over HHB and SEC, i.e., a significant leading correlation between May H and early summer （June） P. In summary, H, which integrates the effects of T and w as an independent variable, has greater capabilities in monitoring land surface heating and improving seasonal P prediction relative to individual land surface factors （e.g., T and w）.