Forecast of summer precipitation in the Yangtze River Valley based on South China Sea springtime sea surface salinity

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zeng, L., Schmitt, R. W., Li, L., Wang, Q., & Wang, D. Forecast of summer precipitation in the Yangtze River Valley based on South China Sea springtime sea surface salinity. Climate Dynamics, 53(9-10), (2019): 5495-5509, doi: 10.1007/s00382-019-04878-y.As a major moisture source, the South China Sea (SCS) has a significant impact on the summer precipitation over China. The ocean-to-land moisture transport generates sea surface salinity (SSS) anomalies that can be used to predict summer precipitation on land. This study illustrates a high correlation between springtime SSS in the central SCS and summer precipitation over the middle and lower Yangtze River Valley (the YRV region). The linkage between spring SSS in the central SCS and summer YRV precipitation is established by ocean-to-land moisture transport by atmospheric processes and land–atmosphere soil moisture feedback. In spring, oceanic moisture evaporated from the sea surface generates high SSS in the central SCS and directly feeds the precipitation over southern China and the YRV region. The resulting soil moisture anomalies last for about 3 months triggering land–atmosphere soil moisture feedback and modulating the tropospheric moisture content and circulation in the subsequent summer. Evaluation of the atmospheric moisture balance suggests both a dynamic contribution (stronger northward meridional winds) and a local thermodynamic contribution (higher tropospheric moisture content) enhance the summer moisture supply over the YRV, generating excessive summer precipitation. Thus, spring SSS in the SCS can be utilized as an indicator of subsequent summer precipitation over the YRV region, providing value for operational climate prediction and disaster early warning systems in China.This research has been supported by the National Natural Science Foundation of China (Nos. 41776025, 41476014, 41606030, 41806027, 41806035). RWS was supported by NSF Grant ICER-1663704. LL was supported by NSF-ICER-1663138. QW was also sponsored by the Pearl River S&T Nova Program of Guangzhou (201906010051). LZ was also supported by the Innovation Academy of South China Sea Ecology and Environmental Engineering (ISEE), Chinese Academy of Sciences, and the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)

Changes to the North Atlantic Subtropical High and Its Role in the Intensification of Summer Rainfall Variability in the Southeastern United States

This study investigates the changes of the North Atlantic subtropical high (NASH) and its impact on summer precipitation over the southeastern (SE) United States using the 850-hPa geopotential height field in the National Centers for Environmental Prediction (NCEP) reanalysis, the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), long-term rainfall data, and Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) model simulations during the past six decades (1948–2007). The results show that the NASH in the last 30 yr has become more intense, and its western ridge has displaced westward with an enhanced meridional movement compared to the previous 30 yr. When the NASH moved closer to the continental United States in the three most recent decades, the effect of the NASH on the interannual variation of SE U.S. precipitation is enhanced through the ridge’s north–south movement. The study’s attribution analysis suggested that the changes of the NASH are mainly due to anthropogenic warming. In the twenty-first century with an increase of the atmospheric CO2 concentration, the center of the NASH would be intensified and the western ridge of the NASH would shift farther westward. These changes would increase the likelihood of both strong anomalously wet and dry summers over the SE United States in the future, as suggested by the IPCC AR4 models. 1