Statistical analysis of the relationship between spring soil moisture and summer precipitation in East China



The relationship between spring soil moisture (SM) and summer precipitation in East China (EC) was examined using monthly temperature and precipitation data and ERA-40 SM data. EC was divided into five different climate regions to investigate how SM-precipitation correlations vary under different climatic conditions. Both local and remote impacts of spring SM in EC were assessed. It was found that spring SM had significant correlations with summer precipitation in the East, Southeast, and Southwest regions, but not in the Northwest and Northeast region. This is possibly because correlations between summer precipitation and temperature (as a surrogate to SM–evaporation relationship) were statistically significant in the first three regions, but not in the Northwest and Northeast regions. Statistically significant positive correlations between SM and summer precipitation were found in the East and Southeast regions and statistically significant negative correlations were in the Southwest region. The negative SM-precipitation relationship is possibly because the Southwest region is primarily an energy-controlled regime. Significant SM-precipitation correlations were usually associated with strong SM persistence and precipitation autocorrelation. Our results suggest that strong correlation between spring SM and summer precipitation might be due to the combination of SM–precipitation interactions and precipitation autocorrelation. Our study also demonstrated that there are strong temporal variations in SM–precipitation relationships in the regions where significant correlations occurred. May SM had significant positive correlations (approximately 0.6) with summer precipitation over most of the study period in East region. Strong negative correlation (approximately −0.6) was found in Southwest during 1980s-1990s due to strong SM persistence and strong precipitation autocorrelation in the same period. This suggested that SM–precipitation relationships vary over time even in regions with strong coupling. Multivariate regression analysis demonstrated that SM persistence had the largest contribution to summer precipitation variation in East region and April precipitation was the dominant predictor of summer precipitation variations in Southeast and Southwest regions. Statistical analysis of SM and precipitation relationships should consider both SM persistence and precipitation autocorrelation. Results from this study can be used to improve the predictability of droughts.