| 基于GSI的华南地区对流尺度快速循环同化预报试验 |
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| 引用本文： | 文秋实,王东海.基于GSI的华南地区对流尺度快速循环同化预报试验[J].气象,2017,43(6):653-664. |
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| 作者姓名： | 文秋实 王东海 |
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| 作者单位： | 成都信息工程大学，成都 610225,中山大学大气科学学院，广州 510275;中国气象科学研究院灾害天气国家重点实验室，北京 100081 |
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| 基金项目： | 公益性行业(气象)科研专项(GYHY201506002和GYHY201306004)共同资助 |
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| 摘 要： | 针对对流尺度快速循环同化系统多次循环同化带来的预报效果改进和资料应用问题,利用GSI同化技术和WRFARW区域模式,设计了华南地区对流尺度快速循环同化方案,对2016年4月17一18日华南地区的飑线天气强降水过程进行模拟试验,分析不同循环同化方案和雷达径向风资料同化对雷达回波、相对湿度、降水量级等的预报效果,以期提高华南地区飑线强降水过程预报技巧。检验结果表明:尽管只同化常规资料对预报效果的改进有局限性,但是多次循环同化对于模式预报的降水有一定改善作用;同时同化雷达径向风资料与常规资料对湿度和降水等模拟技巧均有所提高,大雨以上量级的ETS评分改进尤为明显;尽管模式模拟降水峰值小于真实观测值,但同化雷达径向风资料有效改善了飑线最强时段内的垂直上升速度,使得强降水发生时间和强度更接近真实观测。
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| 关 键 词： | GSI同化，快速循环同化，雷达径向风同化 |
| 收稿时间： | 2016/11/7 0:00:00 |
| 修稿时间： | 2017/4/13 0:00:00 |
Test of GSI Based Rapid Update Cycle Numerical Prediction in Southern China |
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| WEN Qiushi and WANG Donghai.Test of GSI Based Rapid Update Cycle Numerical Prediction in Southern China[J].Meteorological Monthly,2017,43(6):653-664. |
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| Authors: | WEN Qiushi and WANG Donghai |
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| Institution: | Chengdu University of Information Technology, Chengdu 610025 and School of Atmospheric Sciences, Sun Yat Sen University, Guangzhou 510275; State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences, Beijing 100081 |
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| Abstract: | Based on the GSI assimilation system and WRF ARW model, a severe rainfall event which occurred in southern China for the period in 17-18 April 2016 was simulated by the method of rapid update cycle. The experiments used radar radial wind data and other conventional data in assimilation cycle. Several kinds of forecast variables were analyzed to find how the assimilation cycles and difference data would influence the forecast result. The results showed that despite the limitation of the single type of observation, there is a certain improvement effect on the false precipitation prediction by the use of rapid update cycle. Radar radial wind data and conventional data mixing assimilation could improve the humidity and precipitation prediction skills, especially at heavy rainfall levels ETS score. Although the simulated rainfall peak value is less than real observation, the assimilation of radar radial wind data could effectively improve the vertical velocity of the squall line, so the occurrence time and intensity of heavy rainfall are much closer to the real observation. |
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| Keywords: | GSI (gridpoint statistical interpolation) assimilation rapidly cycle assimilation radar radial wind assimilation |
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