| 动力降尺度和多物理参数化方案组合对华南前汛期降水集合预报的影响研究 |
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| 引用本文： | 张凯锋,王东海,张宇,吴珍珍,李国平.动力降尺度和多物理参数化方案组合对华南前汛期降水集合预报的影响研究[J].热带气象学报,2020,36(5):668-682. |
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| 作者姓名： | 张凯锋 王东海 张宇 吴珍珍 李国平 |
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| 作者单位： | 1.佛山市气象局, 广东 佛山 528000 |
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| 基金项目： | 国家自然科学基金项目41775097国家自然科学基金项目41861164027广东省科技计划2017B020218003 |
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| 摘 要： | 针对华南前汛期降水过程，基于全球集合预报系统（GEFS）资料，利用WRF中尺度模式以及GEFS动力降尺度获取的区域集合预报初值场，通过多物理过程参数化方案组合和模式积分方法实现华南前汛期降水的区域集合预报。对2019年5月15日—6月15日共32天的华南前汛期降水过程进行了单一物理过程区域集合预报（REFS_SINGLE）和多物理过程区域集合预报（REFS_MULTI）的数值模拟批量敏感性试验，通过GEFS、REFS_SINGLE和REFS_MULTI的对比分析，探讨多物理过程参数化方案组合对华南前汛期降水的影响，同时利用一次华南前汛期暴雨过程进一步探讨集合预报试验的预报效果。结果表明:（1）REFS集合平均的预报效果明显好于控制性预报。（2）REFS降水集合离散度与预报误差的对应关系好于GEFS。（3）积分48小时后，REFS_MULTI和REFS_SINGLE的扰动能量分别是GEFS的4.7倍和6.3倍。（4）降水级别越大，REFS的TS评分效果就越好于GEFS；REFS_MULTI略微好于REFS_SINGLE。（5）基于32天的批量试验，REFS的AUC值有28天大于GEFS，REFS_MULTI有22天大于REFS_SINGLE，表明REFS的预报技巧好于GEFS，且REFS_MULTI的预报技巧好于REFS_SINGLE。
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| 关 键 词： | 华南前汛期 集合预报 动力降尺度 集合预报检验 |
| 收稿时间： | 2018-12-13 |
STUDY ON IMPACTS OF DYNAMIC DOWNSCALING AND MULTI-PHYSICAL PARAMETERIZATION SCHEME COMBINATION ON ENSEMBLE FORECAST
OF ANNUALLY FIRST RAINY SEASON IN SOUTH CHINA |
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| ZHANG Kai-feng,WANG Dong-hai,ZHANG Yu,WU Zhen-zhen,LI Guo-ping.STUDY ON IMPACTS OF DYNAMIC DOWNSCALING AND MULTI-PHYSICAL PARAMETERIZATION SCHEME COMBINATION ON ENSEMBLE FORECAST
OF ANNUALLY FIRST RAINY SEASON IN SOUTH CHINA[J].Journal of Tropical Meteorology,2020,36(5):668-682. |
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| Authors: | ZHANG Kai-feng WANG Dong-hai ZHANG Yu WU Zhen-zhen LI Guo-ping |
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| Institution: | 1.Meteorological Bureau of Foshan, Foshan 528000, China2.School of Atmospheric Sciences/ Guangdong Provincial Key Laboratory for Climate Change and Natural Disaster Studies/ Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, China3.South China Sea Institute of Marine Meteorology, Guangdong Ocean University, Zhanjiang 524088, China4.School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China |
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| Abstract: | Based on the Global Ensemble Forecast System (GEFS) data, the WRF model and the GEFS dynamic downscaling method are used to obtain the regional ensemble forecast initial states. And through the combination of multi-physical process parameterization schemes and model integration method, the regional ensemble forecast of precipitation in the annually first rainy season in south China is realized. A batch test of single physical process regional ensemble forecast system (REFS_SINGLE) and multi-physical process regional ensemble forecast system (REFS_MULTI) are carried out for the 32-day precipitation period in south China from May 15 to June 15, 2019. Through the comparative analysis of GEFS, REFS_SINGLE and REFS_MULTI, the influence of multi-physical process parameterization scheme combination on precipitation in the annually first rainy season in south China is explored. Meanwhile, a precipitation case in the annually first rainy season in south China is used to further explore the forecasting performance of different ensemble forecasts. The results are as follows. (1) The ensemble mean of REFS is significantly better than that of the control forecast. (2) The correspondence between the precipitation ensemble spread and the forecast error of the REFS is better than that between the precipitation ensemble spread and the forecast error of the GEFS. (3) After 48h, the perturbation energy of the REFS_MULTI and the REFS_SINGLE are 4.7 times and 6.3 times that of the GEFS, respectively. (4) The higher the precipitation level, the higher the TS score of the REFS than that of the GEFS; the REFS_MULTI is slightly better than the REFS_SINGLE. (5) Based on the 32-day batch test, the AUC value of REFS is greater than that of GEFS for 28 days, and REFS_MULTI is greater than REFS_SINGLE for 22 days, indicating that the forecasting skills of REFS are better than that of GEFS, and the forecasting skills of REFS_MULTI are better than that of REFS_SINGLE. |
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| Keywords: | annually first rainy season in south China ensemble forecast dynamical downscaling ensemble forecast test |
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