摘要
以美国新近研发的天气研究预报模式(WRF)配置的三维变分(3D-Var)同化系统WRF3D-Var为平台,结合物理初始化方法(Physical Initialization,简称PI)来同化多普勒雷达径向风和回波强度观测资料。其基本做法是首先用物理初始化方法由雷达回波资料估计出比湿、云水混合比和垂直速度,然后用估计的比湿和云水混合比对模式的相应变量进行调整,最后再将估计出的垂直速度作为一种新的观测类型添加到现有的WRF3D-Var目标函数中,同时以WRF3D-Var提供的方法直接同化径向风。针对2002年6月19日的一次强对流性降水过程和2003年7月5日的一次梅雨锋暴雨过程进行了一组同化多普勒雷达径向风和回波资料的试验研究。同化结果表明:分析变量的增量场和观测的雷达回波有很好的对应关系。在雷达回波区,有正的比湿增量、云水含量增量和垂直速度增量,并且水平风增量在此辐合;在没有雷达回波的地方有负的垂直速度增量。预报结果表明,调整云水含量对降水预报改善不明显,调整比湿对降水预报改进明显,直接用物理初始化估计出的垂直速度替代模式的初始垂直速度,对降水预报改进不明显,但以新的方案同化雷达资料能有效地缩短模式的起转时间(spin-uptime),明显改进短时降水预报。
The three-dimensional variational （3D-Var） data assimilation system of the weather research and forecasting （WRF） model （WRF-Var） is further developed with physical initialization （PI） to assimilate Doppler radar radial velocity and reflectivity observations. In this new 3D-Var assimilation scheme, specific humidity, cloud water content and vertical velocity are first derived from reflectivity observations with PI, then the model fields of specific humidity and cloud water content are replaced by the modified ones, and finally, the estimated vertical velocity is added into the cost-function of the existing WRF-Var （version 2.0） as a new type of observation, and radial velocity observations are assimilated directly by the method afforded by WRF-Var. The new assimilation scheme is tested with a heavy convective precipitation event in the middle reach of the Yangtze River on 19 June 2002 and a meiyu front torrential rain event in the Huaihe river basin on 5 July 2003. Assimilation results show that the increments of analyzed variables correspond well with the horizontal distribution of the observed reflectivity. There are positive increments of cloud water content, specific humidity and vertical velocity in the echo region and negative increments of vertical velocity in the echo-free region where the increments of horizontal winds present an anticlockwise transition. Results of forecast experiments show that the effects of adjusting cloud water content or vertical velocity directly with PI on precipitation forecasts are not obvious. Adjusting specific humidity shows a better performance in forecasting the precipitation than directly adjusting cloud water content or vertical velocity. Significant improvements in predicting the precipitation as well as in reducing model＇s spin-up time are observed when radial velocity and reflectivity observa- tions are assimilated with the new scheme. Therefore, it is an effective way to improve the short-range prediction of precipitation.
出处
《气象学报》
CAS
CSCD
北大核心
2008年第4期479-488,共10页
Acta Meteorologica Sinica
基金
国家自然科学基金(40505022,40305779)
国家重点基础研究发展计划(973)项目(2004CB418305)
关键词
三维变分
物理初始化
同化
多普勒雷达
3D-Var, Physical initialization, Data assimilation, Doppler radar
