Aerosol-Cloud-Precipitation Interactions in WRF Model:Sensitivity to Autoconversion Parameterization

作     者：解小宁 刘晓东 XIE Xiaoning;LIU Xiaodong

作者机构：State Key Laboratory of Loess and Quaternary GeologyInstitute of Earth EnvironmentChinese Academy of Sciences Department of Environmental Science and TechnologySchool of Human Settlements and Civil EngineeringXi’an Jiaotong University 

出 版 物：《Journal of Meteorological Research》 (气象学报（英文版）)

年 卷 期：2015年第29卷第1期

页      面：72-81页

核心收录：

学科分类：07[理学] 0707[理学-海洋科学] 070601[理学-气象学] 070602[理学-大气物理学与大气环境] 0815[工学-水利工程] 0706[理学-大气科学] 0816[工学-测绘科学与技术] 0824[工学-船舶与海洋工程] 0825[工学-航空宇航科学与技术] 

基　　金：Supported by the National Basic Research and Development(973)Program of China(2011CB403406) Strategic Priority Research Program of the Chinese Academy of Sciences(XDA05110101) National Natural Science Foundation of China(41105071and 41290255) 

主　　题：autoconversion parameterization aerosol-cloud-precipitation interactions numerical simulation 

摘      要：Cloud-to-rain autoconversion process is an important player in aerosol loading, cloud morphology, and precipitation variations because it can modulate cloud microphysical characteristics depending on the participation of aerosols, and affects the spatio-temporal distribution and total amount of precipitation. By applying the Kessler, the Khairoutdinov-Kogan（KK）, and the Dispersion autoconversion parameterization schemes in a set of sensitivity experiments, the indirect effects of aerosols on clouds and precipitation are investigated for a deep convective cloud system in Beijing under various aerosol concentration backgrounds from 50 to 10000 cm^-3. Numerical experiments show that aerosol-induced precipitation change is strongly dependent on autoconversion parameterization schemes. For the Kessler scheme, the average cumulative precipitation is enhanced slightly with increasing aerosols, whereas surface precipitation is reduced significantly with increasing aerosols for the KK scheme. Moreover, precipitation varies non-monotonically for the Dispersion scheme, increasing with aerosols at lower concentrations and decreasing at higher *** different trends of aerosol-induced precipitation change are mainly ascribed to differences in rain water content under these three autoconversion parameterization schemes. Therefore, this study suggests that accurate parameterization of cloud microphysical processes, particularly the cloud-to-rain autoconversion process, is needed for improving the scientific understanding of aerosol-cloud-precipitation interactions.