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

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

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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).

seasonal precipitation predictionland surface processsoil enthalpysoil moisturesoil temperature

Changyu ZHAO、Haishan CHEN、Shanlei SUN

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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), Nanjing 210044, China

School of Atmospheric Science, Nanjing University of Information Science and Technology(NUIST), Nanjing 210044, China

This work was jointly supported by the National Natural Science Foundation of ChinaThis work was jointly supported by the National Natural Science Foundation of ChinaSpecial Fund for Research in the Public Interest of ChinaNatural Science Foundation of Jiangsu Province,ChinaNatural Science Foundation of Jiangsu Province,ChinaResearch Innovation Program for College Graduates of Jiangsu Provinceproject funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions

Grant Nos.4123042241625019Grant No.GYHY201206017Grant Nos.B K20130047BK20151525Grant No.KYLX_0823

2018

大气科学进展(英文版)
中国科学院大气物理研究所

大气科学进展(英文版)

CSTPCDCSCDSCI
影响因子：0.741
ISSN：0256-1530
年,卷(期)：2018.35(4)
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