High-resolution Simulation of an Extreme Heavy Rainfall Event in Shanghai Using the Weather Research and Forecasting Model: Sensitivity to Planetary Boundary Layer Parameterization

被引:1
|
作者
Rui WANG [1 ,2 ,3 ]
Yiting ZHU [1 ,2 ]
Fengxue QIAO [1 ,2 ,4 ]
Xin-Zhong LIANG [5 ,6 ]
Han ZHANG [7 ]
Yang DING [3 ]
机构
[1] Key Laboratory of Geographic Information Science, Ministry of Education,East China Normal University
[2] Institute of Eco-Chongming
[3] Earth System Science Interdisciplinary Center, University of Maryland, College Park
[4] Department of Atmospheric & Oceanic Science, University of Maryland, College Park
[5] Shanghai Central Meteorological Observatory
[6] School of Geographic Sciences, East China Normal University
[7] College of Atmospheric Science, Nanjing University of Information Science and Technology
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
P457.6 [降水预报];
学科分类号
0706 ; 070601 ;
摘要
In this study, an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model, with a focus on the effects of planetary boundary layer(PBL) physics using double nesting with large grid ratios(15:1 and 9:1). The sensitivity of the precipitation forecast was examined through three PBL schemes: the Yonsei University Scheme, the Mellor-Yamada-Nakanishi Niino Level 2.5(MYNN)scheme, and the Mellor-Yamada-Janjic scheme. The PBL effects on boundary layer structures, convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations. The results indicated that in single coarser grids(15 km and 9 km), the extreme rainfall amount was largely underestimated with all three PBL schemes. In the inner 1-km grid, the underestimated intensity was improved; however,using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain-Fritsch cumulus scheme, significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall. MYNN, with the weakest vertical mixing, produced the shallowest and most humid inversion layer with the lowest lifting condensation level, but stronger wind fields and upward motions from the top of the boundary layer to upper levels. These factors all facilitate the development of deep convection and moisture transport for intense precipitation, and result in its most realistic prediction of the primary rainfall peak.
引用
收藏
页码:98 / 115
页数:18
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