北京地区暴雨个例的观测敏感区研究

利用基于集合预报的相关方法对2009年7月23日发生在北京及周边地区的暴雨过程的观测敏感区进行了分析。通过WRF(Weather Research Forecast)三维变分方法对初始场进行随机扰动,形成30个初始集合样本,做了预报时效为12 h的集合预报。利用该方法分析检验区(北京及周边地区)累积降水[14:00(北京时间,下同)至20:00]相对于初始时刻(08:00)各基本要素的敏感性,确定感性要素及其对应的区域。研究发现初步确定的敏感性要素为水汽和温度,对应的敏感区分别位于北京的西南侧和北京的东北侧,且通过实况分析可知初步确定的敏感性要素和对应的敏感区具有明确的物理意义。还进一步通过观测系统模拟试验(OSSE)的资料同化验证所确定的敏感区,结果表明在水汽对应的敏感区内同化水汽对降水的预报结果有明显的改进;在温度对应的敏感区内同化温度,降水的预报准确率有了明显的提高,说明了初步确定的敏感性要素和敏感区的正确性。在水汽对应的敏感区内同化水汽的同时在温度对应的敏感区内同化温度,使降水预报的技巧有大幅度的提高,说明了温度和水汽的共同作用对提高降水预报准确率贡献最大。因此,通过基于集合预报的相关方法能够快速的确定敏感区。研究结果将为确定北京暴雨的观测敏感区提供参考。

Case Study of Observations and Sensitive Region of Heavy Rainfall in Beijing Area

Using a statistical correlation based on an ensemble forecast, observations and the sensitive region of a heavy rainfall that occurred around Beijing on July 23 2009 are analyzed. An ensemble of 30 initial samples is constructed using WRFDA (Weather Research and Forecasting Data Assimilation) and then a 12-h forecast is produced on the basis of the initial samples. To determine the sensitive variables and their regions, the sensitivity of the accumulated precipitation in the verification region (Beijing area) to the basic variables of the initial conditions is studied using the method described above. A preliminary determination indicates that the sensitive variables are the water vapor and temperature, and their respective sensitive regions are southwest and northeast of Beijing. An analysis of the real atmosphere found that the sensitive variables and their sensitive areas have a clear physical meaning. Moreover, data assimilation of an observing system simulation experiment is used to verify the sensitive region. It is shown that assimilating the sensitive variable water vapor in its sensitive region can improve the precipitation forecast accuracy; assimilating the sensitive variable temperature in its sensitive region can also improve the forecast quality, indicating the correctness of the sensitive variables and sensitive areas. Assimilating the sensitive variable water vapor in its sensitive region while assimilating the sensitive variable temperature in its sensitive region can have a greater positive effect on the forecast quality, illustrating that the effects of temperature and water vapor yields the greatest improvement in the rainfall prediction accuracy. Therefore, the method of statistical correlation can effectively identify the sensitive variables and their sensitive regions. This study can help to identify the observed sensitive region of rainfall in the Beijing area.