On Northern Hemisphere Wave Patterns Associated with Winter Rainfall Events in China

作     者：Claudia Christine STEPHAN Yan Ho NG Nicholas P. KLINGAMAN 

作者机构：National Centre for Atmospheric Science - Climate Department of Meteorology University of Reading Reading RG6 6BB United Kingdom Department of Meteorology University of Reading Reading RG6 6BB United Kingdom 

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8期

页      面：125-138页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0707[理学-海洋科学] 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：supported by the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP) China,as part of the Newton Fund supported by an Independent Research Fellowship from the UK Natural Environment Research Council(NE/L010976/1) 

主　　题：rainfall in China spring flooding Rossby wave dynamics EOT analysis predictability teleconnections 

摘      要：During extended winter （November-April）, 43% of the intraseasonal rainfall variability in China is explained by three spatial patterns of temporally coherent rainfall, These patterns were identified with empirical orthogonal teleconnection （EOT） analysis of observed 1982-2007 pentad rainfall anomalies and connected to midlatitude disturbances. However, ex- amination of individual strong EOT events shows that there is substantial inter-event variability in their dynamical evolution, which implies that precursor patterns found in regressions cannot serve as useful predictors. To understand the physical nature and origins of the extratropical precursors, the EOT technique is applied to six simulations of the Met Office Unified Model at horizontal resolutions of 200-40 km, with and without air-sea coupling. All simulations reproduce the observed precursor patterns in regressions, indicating robust underlying dynamical processes. Further investigation into the dynamics associated with observed patterns shows that Rossby wave dynamics can explain the large inter-event variability. The results suggest that the appaxently slowly evolving or quasi-stationaxy waves in regression analysis are a statistical amalgamation of more rapidly propagating waves with a variety of origins and properties.