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云物理初始化对一次强对流天气数值预报的影响研究 被引量:5

INVESTIGATION OF THE IMPACT OF CLOUD INITIALIZATION ON NUMERICAL PREDICTION OF A CONVECTIVE SYSTEM
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摘要 基于第二代华东快速更新循环同化预报模式系统,针对2015年4月28日华东强对流天气,分析了云初始化对强对流数值预报的作用和影响。有无云初始化试验对比结果表明,在循环系统中使用云初始化,能够显著提高0~6 h的降水预报评分,强降水的位置预报更接近实况。云初始化能较好地改善初始场水凝物的质量分布,提供较准确的相关对流系统的初始信息,改进强对流区域内水凝物的预报效果,有效避免了模式初始阶段的降水滞后现象,缩短了模式由于初始微物理信息缺失引起的"spin-up"时间。而积分6 h以后的结果与无云初始化的结果差别不大。 Using the second generation of SMS-WARR Shanghai Meteorological Service-WRF ADAS Rapid Refresh System, prediction of a severe convective event in East China is analyzed with the focus on the impact of cloud initialization. Comparison between the prediction results from the experiments with and without cloud initialization shows that the forecast using the cloud initialization can greatly increase the TS score of 0-6 hour rainfall, and the position of the forecasted precipitation is closer to that of the observation. Further analysis indicates that cloud initialization can significantly improve the initial fields of hydrometeors, provide more accurate information of the convection system, and produce better forecasts of hydrometeors and vertical velocity over the severe convection area. Moreover, cloud initiation largely avoids the delay of precipitation occurrence during the early stage and shortens the "spin-up" time due to the lack of the initial microphysical information. However, results with and without the cloud initialization become quite similar to each other when the integration time period exceeds 6 hours.
作者 李佳 陈葆德 黄伟 张旭 LI Jia;CHEN Bao-de;HUANG Wei;ZHANG Xu(Nanjing University of Information Science & Technology, Nanjing 210044, China;Shanghai Typhoon Institute of China Meteorological Administration, Shanghai 200030, China;Key Laboratory of Numerical Modeling for Tropical Cyclone, CMA, Shanghai 200030, China)
出处 《热带气象学报》 CSCD 北大核心 2018年第2期198-208,共11页 Journal of Tropical Meteorology
基金 国家重点研发计划"政府间国际科技合作项目"重点专项(2016YFE0109700) 国家自然科学基金项目(41575101 41505087) 公益性行业(气象)科研专项(GYHY201206006)共同资助
关键词 天气预报 预报方法 云初始化 快速更新 weather forecast forecast method cloud initialization rapid refresh
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