Interdecadal Variability of Summer Precipitation Efficiency in East Asia. (4th December 2019)

• Record Type: Journal Article
• Authors: Wang, Jian; Gui, Shu; Ma, Anqi; Yang, Ruowen; Zhang, Qi
• Other Names: Gonzalez Jorge E. Academic Editor.
• Is Part Of: Advances in meteorology. Volume 2019(2019)
• Publication Date: 2019-12-04
• Subjects: Meteorology -- Periodicals; Meteorology; Periodicals; 551.505
• DOI: 10.1155/2019/3563024
• Languages: English
• ISSNs: 1687-9309

Abstract

Abstract : Precipitation efficiency (PE) is a crucial physical quantity in convective processes, describing the efficiency of rainfall generation from cloud detrainment. Although the importance of PE in extreme precipitation events is widely accepted, the evolution of PE in the warming climate and the associated moisture processes in East Asia are still not well understood. To address these issues, the interdecadal variability of PE in East Asia during summer in 1979–2016 is investigated in this study. Two major modes of summertime precipitation efficiency are identified using Empirical Orthogonal Function (EOF) analysis. The leading EOF mode (EOF1) has a dipole pattern that reveals the variations of mean precipitation efficiency. The second EOF mode (EOF2) presents a quadrupole pattern that shows changes in the variability of precipitation efficiency. Both EOF modes exhibit significant interdecadal variability (IDV). The IDV of EOF1 is closely associated with the phase change of the Pacific decadal oscillation (PDO). The Pacific sea surface temperature anomalies associated with the PDO can excite wind anomalies that significantly modulate moisture transport and further alter the mean precipitation efficiency in East Asia. The IDV of EOF2 can be attributed to the interdecadal change of occurrence frequency of Eastern Pacific El Niño-Southern Oscillation (ENSO) events, which affect water vapor transport by inducing an East Asia-Pacific teleconnection-like wave train anomaly pattern. The IDV patterns of precipitation efficiency for both the mean value and variability will improve the ability to predict precipitation in East Asia.