doi:  10.3878/j.issn.1006-9895.1810.18125
风廓线雷达资料在GRAPES-Meso模式中的同化应用研究

A Study on Assimilation of Wind Profiling Radar Data in GRAPES-Meso Model
摘要点击 275  全文点击 179  投稿时间:2018-02-08  
查看HTML全文  查看全文  查看/发表评论  下载PDF阅读器
基金:  国家自然科学基金项目41475029,公益性行业气象国家自然科学基金项目41475029,公益性行业(气象)科研专项GYHY201506003,灾害天气国家重点实验室开放课题2018LASW-B10
中文关键词:  风廓线雷达  质量控制  资料同化  影响试验
英文关键词:  Wind profiling radar  Quality control  Data assimilation  Impact experiment
                 
作者中文名作者英文名单位
王丹WANG Dan中国气象局数值预报中心,北京 100081;中国气象科学研究院灾害天气国家重点实验室,北京 100081
阮征RUAN Zheng中国气象科学研究院灾害天气国家重点实验室,北京 100081
王改利WANG Gaili中国气象科学研究院灾害天气国家重点实验室,北京 100081
朱立娟ZHU Lijuan中国气象局数值预报中心,北京 100081
田伟红TIAN Weihong中国气象局数值预报中心,北京 100081
李丰and LI Feng中国气象科学研究院灾害天气国家重点实验室,北京 100081
引用:王丹,阮征,王改利,朱立娟,田伟红,李丰.2019.风廓线雷达资料在GRAPES-Meso模式中的同化应用研究[J].大气科学,43(3):634-654,doi:10.3878/j.issn.1006-9895.1810.18125.
Citation:WANG Dan,RUAN Zheng,WANG Gaili,ZHU Lijuan,TIAN Weihong,and LI Feng.2019.A Study on Assimilation of Wind Profiling Radar Data in GRAPES-Meso Model[J].Chinese Journal of Atmospheric Sciences (in Chinese),43(3):634-654,doi:10.3878/j.issn.1006-9895.1810.18125.
中文摘要:
      以未来业务化应用为目标,本文进行了业务数值预报模式GRAPES_Meso(Global/Regional Assimilation and Prediction System)中的风廓线雷达资料同化应用研究。基于2015年7月的全国风廓线雷达观测数据,首先建立了面向同化应用的风廓线雷达资料两步质量控制方案。通过对比分析质量控制前后风廓线雷达观测资料集与欧洲中心再分析资料ERA-Interim的差值场特征,论证了质量控制方案的合理性,两步质控后风场误差显著减小,同时观测背景差更接近高斯分布,符合数值同化应用假设。将质量控制后的风廓线雷达资料应用于GRAPES-3DVAR系统,开展有、无风廓线雷达资料同化的对比试验,通过批量试验和台风“莲花”个例分析来探讨风廓线雷达资料同化对数值预报的影响。研究表明:在循环同化过程中加入风廓线雷达资料对数值模式初始场有一定改善,风场、温度场、湿度场的分析误差均有减小,从而使短期降水(0~12 h)的预报技巧得以提高。针对台风暴雨个例分析结果表明,风廓线雷达资料同化能有效地调整台风降水区的动力结构和水汽分布,在模式中形成更有利于对流发展的环境条件,从而更好地预报降水的位置与强度。
Abstract:
      Aiming at future operational implementation, the research on assimilation of wind profiling radar (WPR) data into the GRAPES_Meso model (Global/Regional Assimilation and Prediction System) is carried out. Based on observational WPR datasets in China during July 2015, a two-step quality control (QC) procedure is developed first. The differences between the ERA-Interim reanalysis data and the WPR observational data before and after QC are calculated, respectively. Results show that the wind field errors are largely reduced after QC, and the distributions of the innovations corresponding to observations after QC are closer to a Gaussian distribution. Based on the GRAPES-3DVAR system, the WPR observations after QC were used in one-month continuous experiments as well as a real-case study to illustrate the influence of WPR observations on GRAPES_Meso model. Results show that the assimilation of WPR data can improve the initial condition of the model. Analysis errors of wind, temperature and humidity field are reduced, and the prediction skill for short-term precipitation (0-12 h) is improved. The impact of assimilating WPR data on the analysis and forecast of typhoon “Linfa” is also investigated in this study. Results show that assimilating WPR data can effectively adjust the dynamic structure and water vapor condition over the typhoon precipitation area, producing a more favorable condition for the development of convective system and improving the forecast skill of precipitation.
主办单位:中国科学院大气物理研究所 单位地址:北京市9804信箱
联系电话: 010-82995051,010-82995052传真:010-82995052 邮编:100029 Email:dqkx@mail.iap.ac.cn
本系统由北京勤云科技发展有限公司设计
京ICP备09060247号