| 华中区域LRUC系统的构建与试验 |
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| 引用本文： | 李红莉,王志斌.华中区域LRUC系统的构建与试验[J].气象科学,2017,37(2):195-204. |
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| 作者姓名： | 李红莉 王志斌 |
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| 作者单位： | 中国气象科学研究院, 北京 100081;南京信息工程大学, 南京 210044;中国气象局武汉暴雨研究所 暴雨监测预警湖北省重点实验室, 武汉 430205,中国气象局武汉暴雨研究所 暴雨监测预警湖北省重点实验室, 武汉 430205 |
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| 基金项目： | 国家自然科学基金（41375041，41375057，41105072）；国家科技支撑计划（2012BAK10B04）；湖北省科技发展基金数值预报专项（2016S02）；科技部公益（气象）行业专项（GYHY201406001，GYHY201306076） |
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| 摘 要： | 如何将区域观测资料在中尺度模式中快速有效同化是提高区域精细化数值预报准确率和时效性的关键所在。本文简单介绍了基于LAPS和WRF建立的快速循环同化预报系统LRUC,以一次影响长江中游的典型梅雨锋暴雨过程为例,设计几种试验方案,结合实况降水分布,对比分析华中区域多普勒雷达资料循环同化对改善暴雨预报的作用;根据个例试验结果,设计批量后报试验方案,对比分析雷达资料同化对华中区域2007年主汛期(6—8月)多个时效降水预报评分。暴雨个例试验结果表明,华中区域多普勒雷达资料在LAPS中的同化,能为WRF提供更优初值场;同化华中区域地面资料和雷达资料后,比仅同化地面资料更能改进模式初值,改善模式降水预报,且降雨量级越大,24 h降水预报TS评分越高。批量后报试验结果表明,建立的快速循环同化预报系统LRUC,能对区域多源观测资料进行多时次循环同化分析,为模式初值增加观测资料的时间演变信息,提高模式对暴雨量级降水的预报水平;系统具有稳定性和一定的评分水平。
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| 关 键 词： | LAPS 快速更新循环 数值试验 暴雨 雷达 |
| 收稿时间： | 2015/11/14 0:00:00 |
| 修稿时间： | 2016/2/19 0:00:00 |
Establishment and evaluation of LRUC in central China |
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| LI Hongli and WANG Zhibin.Establishment and evaluation of LRUC in central China[J].Scientia Meteorologica Sinica,2017,37(2):195-204. |
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| Authors: | LI Hongli and WANG Zhibin |
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| Institution: | Chinese Academy of Meteorological Sciences, Beijing 100081, China;Nanjing University of Information Science & Technology, Nanjing 210044, China;Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research/Institute of Heavy Rain of CMA, Wuhan 430205, China and Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research/Institute of Heavy Rain of CMA, Wuhan 430205, China |
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| Abstract: | Rapid and effective assimilation of the regional observation data in meso-scale model is the key to improve the accuracy and timeliness of the local finer numerical prediction. The rapid update cycle system (LRUC) based on LAPS and WRF was briefly introduced in this study. Taking a typical Meiyu front rainstorm influencing the middle reaches of Yangtze River as an example, several experiment schemes were designed to comparatively analyze the impact of Doppler radar data cycle assimilation over Middle China on the improvement of heavy rain forecast combined with the precipitation observation. Based on the case study, a few schemes are selected to analyze the impact of radar data assimilation on the application of LRUC in the main flood season (June-August) of 2007. It is shown that better initial model field for WRF with the Doppler radar data assimilation in LAPS can be provided. It can be revealed that the LAPS background field assimilating both surface and radar observations by LAPS leads to better initial field and further precipitation forecast improvement than only assimilating surface observations. The larger the precipitation is, the higher the TS scores of 24 h precipitation forecast lead to. It is concluded that building LRUC can add time evolution information of observations to the initial field of model by using more time cycle analysis, so as to improve the precipitation forecast, especially for the heavy rainfall. The LRUC is stable and has good TS scores. |
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| Keywords: | LAPS RUC Numerical simulation Heavy rainfall Radar |
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