微物理过程和积云参数化方案对海南岛秋季暴雨模拟的影响  

Impacts of microphysical processes and cumulus parameterization schemes on simulated rainfall in Autumn over the Hainan Island

作　　者：杨薇[1] 冯文[1] 李勋[1] YANG Wei;FENG Wen;LI Xun(Meteorological Observatory of Hainan Province, Haikou 570203)

机构地区：[1]海南省气象台,海口570203

出　　处：《暴雨灾害》2017年第1期8-17,共10页Torrential Rain and Disasters

基　　金：海南省气象局青年基金项目(HNQXQN201403)

摘　　要：利用WRF(ARW)V3.6模式模拟了2010年10月5—6日发生在海南的一次秋季大暴雨过程,从降水、风场、反射率和云结构等方面分析WRF模式中3个积云参数化方案(KF,BMJ,Tied Tke)和4个微物理参数化方案(Lin et al,WSM5,WSM6,Thompson)对海南岛秋季暴雨模拟的影响。结果表明:此次秋季暴雨过程模拟对不同的积云参数化方案和微物理参数化方案组合是比较敏感的,不同的积云参数化方案和微物理参数化方案组合通过调整温湿场结构,从而影响模拟降水的时间、强度和落区。对比发现,Thompson微物理方案的组合对于降水量级的模拟更为敏感,能较合理的描述暴雨发生发展过程中的水汽输送、热力和动力条件,并通过影响雨水混合比和云水混合比的高度和大小从而影响降水。其中Thompson微物理方案和Tied Tke积云方案的组合能较好的模拟出本次暴雨过程的特征,与实测最为接近,该组合模拟的最大垂直速度和反射率区与最大云水混合比对应。另外,积云方案和微物理方案的选择不影响水汽混合比的模拟。The Advanced Research WRF (ARW) version 3.6 has been used to simulate a heavy rainfall event that has occurred on 5-6 October 2010 over Hainan Island. The impacts of three cumulus parameterization schemes (KF, BMJ, TiedTke) and four microphysics parameterization schemes (Lin et al, WSM5, WSM6, Thompson) on heavy rainfall simulations are studied by means of precipitation, wind, reflectivity,and cloud structure. The results indicate that WRF model is sensitive to all combinations of cumulus parameterization schemes and microphysics parameterization schemes; each of them impacts greatly on time and location of rainfall intensity through regulating the structure of temperature and humidity fields. The combinations with Thompson scheme, which can catch the characterization of moisture transport, thermal and dynamic conditions, are more sensitive to the amount of precipitation than other combinational schemes during the development of heavy rainfall. The precipitation can be effected through changing the developing height and amount of cloud water mixing ratio and rain water mixing ratio. The Thompson scheme coupled with the TiedTke scheme can simulate characteristics of the tropical rainstorm event well and results in the most close values to the observed data. The simulated maximum cloud water mixing ratio is at the position where the vertical velocity and reflectivity is also maximized. Additionally, the production of water vapor mixing ratio is independent of cumulus parameterization schemes and microphysics parameterization schemes.

关 键 词：数值模拟 WRF 秋季暴雨 微物理参数化方案 积云参数化方案 

分 类 号：P435[天文地球—大气科学及气象学]