| 雷达反射率资料的三维变分同化研究 |
| |
| 引用本文： | 范水勇,王洪利,陈敏,高华.雷达反射率资料的三维变分同化研究[J].气象学报,2013,71(3):527-537. |
| |
| 作者姓名： | 范水勇 王洪利 陈敏 高华 |
| |
| 作者单位： | 中国气象局北京城市气象研究所, 北京, 100089;美国国家大气研究中心(NCAR), Boulder, CO, 80307;中国气象局北京城市气象研究所, 北京, 100089;中国气象局北京城市气象研究所, 北京, 100089 |
| |
| 基金项目： | 国家科技支撑计划课题(2008BAC37B03);气象关键技术集成与应用重点项目(CAMGJ2012Z20). |
| |
| 摘 要： | 应用天气研究和预报模式(WRF)三维变分系统中一种新的雷达反射率资料间接同化方法来进行反射率资料的三维变分同化研究,评估雷达反射率资料对夏季短时定量降水预报的作用.该方法不直接同化雷达反射率资料,而是同化由反射率资料反演出的雨水和估计的水汽.以2009年夏季北京地区发生的4次强降水过程为例,考察了北京市气象局业务运行的快速更新循环同化预报系统对京津冀地区雷达网的雷达反射率资料的同化性能以及雷达反射率资料和径向风资料同时同化的效果.数值试验结果表明:(1)同化反演雨水或水汽都能改善降水预报,但同化反演水汽对降水预报效果的改善起了更重要的作用;(2)同化反射率资料能极大地提高短时降水预报的效果,其稳定的正面效果可以延伸到6h的预报时效,而同化径向风资料不能得到稳定的正效果;(3)同化雷达资料时,应用快速更新循环同化预报系统是提高短时定量降水预报的一个有效途径.
|
| 关 键 词： | 天气研究和预报模式(WRF) 三维变分同化 雷达反射率 资料同化 快速更新循环 |
| 收稿时间： | 2012/10/8 0:00:00 |
| 修稿时间： | 1/9/2013 12:00:00 AM |
Study of the data assimilation of radar reflectivity with the WRF 3D-Var |
| |
| FAN Shuiyong,WANG Hongli,CHEN Min and GAO Hua.Study of the data assimilation of radar reflectivity with the WRF 3D-Var[J].Acta Meteorologica Sinica,2013,71(3):527-537. |
| |
| Authors: | FAN Shuiyong WANG Hongli CHEN Min and GAO Hua |
| |
| Institution: | Institute of Urban Meteorology, CMA, Beijing 100089, China;National Center of Atmospheric Researeh, Boulder, CO80307, USA;Institute of Urban Meteorology, CMA, Beijing 100089, China;Institute of Urban Meteorology, CMA, Beijing 100089, China |
| |
| Abstract: | The three-dimensional variational data assimilation of radar reflectivity is studied using an indirect radar reflectivity assimilation scheme within the Weather Researeh and Forecasting model(WRF) three-dimensional data assimilation system(WRF 3D-Var).This scheme,instead of assimilating radar reflectivity directly, assimilates retrieved rainwater and water vapor derived from radar reflectivity.The impact of radar reflectivity from the radar network of the Beijing-Tianjin-Hebei area is assessed by conducting the numerical experiments using the operational Rapid Update and Cycling data assimilation and forecast system at the BMB.The four summertime connective cases, which produced severe rainfall in Beijing in June 2009,are studicd.The results show that both assimilating retrieved rainwater and derived water vapor can improve precipitation forecasts and assimilating derived water vapor play a more important role.On average, the assimilation of reflectivity data can significantly improve short-term precipitation forecast skill up to 6 hours,but the assimilation of radial velocity cannot make a stable improvement.The RUC mode is very important to short-term quantitative precipitation forecast (QPF) when radar data assimilated. |
| |
| Keywords: | WRF 3D-Var Radar reflectivity Data assimilation RUC |
|
| 点击此处可从《气象学报》浏览原始摘要信息 |
| 点击此处可从《气象学报》下载免费的PDF全文 |
|
