Rainfall assimilation using a new four-dimensional variational method: A single-point observation experiment

被引:0
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作者
Juanjuan Liu
Bin Wang
机构
[1] Chinese Academy of Sciences,State Key Laboratory of Numerical Modeling for Atmospheric Sciences & Geophysical Fluid Dynamics, Institute of Atmospheric Physics
来源
关键词
data assimilation; dimension-reduced projection four-dimensional variational data assimilation (DRP-4DVar); rainstorm; numerical simulation;
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学科分类号
摘要
Accurate forecast of rainstorms associated with the mei-yu front has been an important issue for the Chinese economy and society. In July 1998 a heavy rainstorm hit the Yangzi River valley and received widespread attention from the public because it caused catastrophic damage in China. Several numerical studies have shown that many forecast models, including Pennsylvania State University National Center for Atmospheric Research’s fifth-generation mesoscale model (MM5), failed to simulate the heavy precipitation over the Yangzi River valley. This study demonstrates that with the optimal initial conditions from the dimension-reduced projection four-dimensional variational data assimilation (DRP-4DVar) system, MM5 can successfully reproduce these observed rainfall amounts and can capture many important mesoscale features, including the southwestward shear line and the low-level jet stream. The study also indicates that the failure of previous forecasts can be mainly attributed to the lack of mesoscale details in the initial conditions of the models.
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页码:735 / 742
页数:7
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