1 September 2017 Effects of microphysics parameterization on simulations of summer heavy precipitation in the Yangtze-Huaihe Region, China
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Abstract
It has been a longstanding problem for current weather/climate models to accurately predict summer heavy precipitation over the Yangtze-Huaihe Region (YHR) which is the key flood-prone area in China with intensive population and developed economy. Large uncertainty has been identified with model deficiencies in representing precipitation processes such as microphysics and cumulus parameterizations. This study focuses on examining the effects of microphysics parameterization on the simulation of different type of heavy precipitation over the YHR taking into account two different cumulus schemes. All regional persistent heavy precipitation events over the YHR during 2008-2012 are classified into three types according to their weather patterns: the type I associated with stationary front, the type II directly associated with typhoon or with its spiral rain band, and the type III associated with strong convection along the edge of the Subtropical High. Sixteen groups of experiments are conducted for three selected cases with different types and a local short-time rainstorm in Shanghai, using the WRF model with eight microphysics and two cumulus schemes. Results show that microphysics parameterization has large but different impacts on the location and intensity of regional heavy precipitation centers. The Ferrier (microphysics) –BMJ (cumulus) scheme and Thompson (microphysics) – KF (cumulus) scheme most realistically simulates the rain-bands with the center location and intensity for type I and II respectively. For type III, the Lin microphysics scheme shows advantages in regional persistent cases over YHR, while the WSM5 microphysics scheme is better in local short-term case, both with the BMJ cumulus scheme.
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Yu Kan, Bo Chen, Tao Shen, Chaoshun Liu, Fengxue Qiao, "Effects of microphysics parameterization on simulations of summer heavy precipitation in the Yangtze-Huaihe Region, China", Proc. SPIE 10405, Remote Sensing and Modeling of Ecosystems for Sustainability XIV, 104050D (1 September 2017); doi: 10.1117/12.2271977; https://doi.org/10.1117/12.2271977
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