利用WRF和多普勒雷达资料同化对一次江淮地区梅雨降水过程的模拟研究
投稿时间:2020-04-30  修订日期:2020-05-12  点此下载全文
引用本文:
摘要点击次数: 21
全文下载次数: 0
作者单位E-mail
黄兴友 南京信息工程大学 huangxy@nuist.edu.cn 
陈晓颖 南京信息工程大学 710462727@qq.com 
基金项目:国家重点研发计划“重大自然灾害监测预警与防范”项目课题(2018YFC1506102);国家自然科学基金项目(G41805070)
中文摘要:为了研究同化雷达资料对数值模式降水预报的改进效果,针对2015年6月26-28日江淮地区梅雨降水过程,本文进行了结合雷达资料同化的数值模拟研究。论文首先介绍了过程的降水概况、环流形势,并着重分析了造成降水的中小尺度对流系统的生消过程。利用WRF模式进行了降水过程的数值模拟,在完成控制试验的基础上进行WRF-3DVAR的雷达资料同化。经过15h的spin-up后,分别进行了针对背景误差协方差矩阵中特征长度(len_scaling)和方差尺度(var_scaling)的敏感性试验,得到结果:最适合本次个例的特征长度为0.5、方差尺度为0.7。设置最优的特征长度和方差尺度进行同时同化反射率因子与径向风、单独同化反射率因子和单独同化径向风的同化试验,并分别设置了1h间隔和30min间隔的同化频率。通过分析个例水汽场和动力场的物理条件及降水预报结果,得到结论:在本次试验中,雷达数据同化能够有效提高降水预报的效果,且同时同化雷达反射率因子和径向风的效果最好;同化雷达资料频率越高,效果提高也越明显。
中文关键词:梅雨锋  降水  多普勒天气雷达  同化  尺度因子
 
Research on the Simulation of a Rainfall Event Along Meiyu Front in Jianghuai Area Using WRF and Doppler Radar Data Assimilation
Abstract:In order to study the improvement effects of radar data assimilation on the numerical model precipitation forecast, taking the precipitation process of Meiyu in Jianghuai area from June 26-28, 2015, this paper carried out a numerical simulation study combined with radar data assimilation. The general precipitation situation and circulation situation of this event are introduced. The development and disappearance process of the meso-scale convective system causing precipitation are analyzed emphatically. The numerical simulation of WRF mode is used for this process, and the radar data assimilation of WRF-3DVAR is carried out after the control experiment. After 15 h spin-up, the sensitivity experiments for len_scaling and var_scaling of background error covariance matrix were performed respectively with the conclusion that the most suitable combination for the case is that len=0.5 and var = 0.7.The optimal characteristic length and variance scales were set for simultaneous assimilation of reflectivity and radial velocity, assimilation of reflevtivity alone and assimilation of radial velocity alone. The assimilation frequencies of 1 hour interval and 30 min interval were set respectively. By analyzing the physical conditions of the water vapor field and the dynamic field as well as the precipitation results, it is concluded that in this experiment radar data assimilation can effectively improve the effect of precipitation forecast, and meanwhile the assmilation results of radar reflectivity and radial velocity have the best effect. The higher the frequency of the assimilation radar data, the more obvious the effect is.
keywords:Meiyu Front  Precipitation  DopplerWeather Radar  Assimilation  Scale Factor
  查看/发表评论  下载PDF阅读器