| WRF模式物理参数化方案对一次局地大暴雨预报的影响研究 |
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| 引用本文： | 盛春岩,荣艳敏,曲巧娜,范苏丹.WRF模式物理参数化方案对一次局地大暴雨预报的影响研究[J].山东气象,2020,40(1):66-78. |
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| 作者姓名： | 盛春岩 荣艳敏 曲巧娜 范苏丹 |
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| 作者单位： | (山东省气象科学研究所，山东 济南 250031) |
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| 基金项目： | “十三五”山东现代农业气象服务保障工程（鲁发改农经〔2017〕97号）；山东省重点研发计划项目(2016GSF120017)；山东省气象科学研究所数值天气预报应用技术开放研究基金项目(SDQXKF2014Z02)；山东省气象局科研项目(2018sdqxm10) |
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| 摘 要： | 基于WRF(Weather Research and Forecasting)模式及其3Dvar(3-Dimentional Variational)资料同化系统，采用36、12、4 km嵌套网格进行快速更新循环同化和不同的微物理及积云对流参数化方案对比试验，对2011年5月8日鲁中一次局地大暴雨过程进行了研究。结果表明，快速更新循环同化地面观测资料是影响模式降水落区预报准确性的关键因素，不同的微物理和积云对流参数化方案主要影响降水强度预报。采用不同的微物理参数化方案和积云对流参数化方案进行降水预报对比试验表明，LIN方案和WSM6(WRF Single-Moment 6-class)微物理参数化方案对降水预报均较好，LIN方案降水预报较WSM6方案略强。4 km网格预报使用K-F (Kain-Fritsch)积云对流参数化方案或不使用积云对流参数化方案，预报的降水均较好。4 km网格使用旧的K-F积云对流参数化方案，预报的近地层大气风场偏弱，导致大气动力抬升作用偏弱，从而造成模式降水预报偏弱。
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| 关 键 词： | WRF模式 资料同化 物理参数化方案 大暴雨 |
| 收稿时间： | 2019/9/13 0:00:00 |
| 修稿时间： | 2019/11/7 0:00:00 |
Numerical simulation and comparative study on a local rainstorm event via WRF with different physical parameterization schemes |
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| SHENG Chunyan,RONG Yanmin,QU Qiaon,FAN Sudan.Numerical simulation and comparative study on a local rainstorm event via WRF with different physical parameterization schemes[J].Journal of Shandong Meteorology,2020,40(1):66-78. |
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| Authors: | SHENG Chunyan RONG Yanmin QU Qiaon FAN Sudan |
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| Institution: | (Shandong Institute of Meteorological Sciences, Jinan 250031, China) |
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| Abstract: | Using the WRF (Weather Research and Forecasting) model and it''s 3Dvar (3-Dimentional Variational) data assimilation (DA) system, a local rainstorm event in middle Shandong on 8 May 2011 is studied adopting 3-h assimilation cycle of 36 km, 12 km, and 4 km nested grid and comparative experiments of different microphysics and cumulus convective parameterization schemes. The results are as follows. Rapid update cycle of surface observation data is a key factor for the model forecast of precipitation area. Different microphysics and cumulus convective parameterization schemes mainly affect the precipitation intensity forecast. Comparative experiments of different microphysics and cumulus convective parameterization schemes show that LIN scheme and WSM6 (WRF Single-Moment 6-class) microphysics schemes are both good for precipitation forecast and the LIN scheme performs better. The precipitation forecast of 4 km nested grid both performs better with K-F (Kain-Fritsch) cumulus convective parameterization schemes or without cumulus convective parameterization schemes. The 4 km grid forecast with the previous K-F cumulus convective parameterization schemes indicates that the weak surface wind field leads to weak lifting motion and the precipitation of model forecast is weaker. |
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| Keywords: | the WRF model data assimilation physical parameterization scheme rainstorm |
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