大气科学2017，Vol.41Issue(2)：321-332,12.DOI:10.3878/j.issn.1006-9895.1605.16107
基于NLS-4DVar方法的雷达资料同化及其在暴雨预报中的应用
The Radar Data Assimilation System Based on NLS-4DVar and Its Application in Heavy Rain Forecast
摘要
Abstract
In this paper,the PODEn4DVar-based radar data assimilation scheme (PRAS) was improved according to the theory of NLS (Non-Linear Least Squares)-4DVar (four-dimensional variational analysis) scheme.This work aims to deal with the application problem of PRAS under highly nonlinear conditions.As a result,a new radar data assimilation scheme,i.e.NLS-4DVar-based radar data assimilation scheme (NRAS),was developed.To evaluate whether NRAS can further improve the performance compared to PRAS,the Observing System Simulation Experiments (OSSEs) and real radar data assimilation experiments for two heavy rain events (July 8,2010,central China;March 30,2014,southern China) were conducted in this study.The results demonstrate that,for both the OSSEs and the real radar data assimilation experiments,NRAS can further improve the assimilation result in comparison to PRAS.By increasing iteration times,NRAS can adjust the wind field and water vapor field.This leads to further improvements on the forecast of intensity and location of the rainfall However,with increases in the iteration times,the adjustment for the initial condition by NRAS becomes smaller,which leads to a smaller improvement on the rainfall forecast.The results indicate that NRAS can effectively deal with the application of PRAS under highly non-linear condition.With fewer iteration times,NRAS can obtain approximate convergence result.NRAS is expected to better assimilate radar data in numerical weather predictions,and thus further improve the prediction of meso-micro scale weather systems.关键词
雷达资料同化/PRAS资料同化系统/NLS-4DVar同化方法/NRAS资料同化系统/降水Key words
Radar data assimilation/PODEn4DVar-based radar data assimilation scheme (PRAS)/Non-Linear Least Squares-four-dimensional variational analysis (NLS-4DVar)/NLS-4DVar-based radar data assimilation scheme (NRAS)/Rainfall分类
天文与地球科学引用本文复制引用
张斌,田向军,张立凤,孙建华..基于NLS-4DVar方法的雷达资料同化及其在暴雨预报中的应用[J].大气科学,2017,41(2):321-332,12.基金项目
国家自然科学基金项目41575100,公益性行业(气象)科研专项GYHY201506002 National Natural Science Foundation of China (Grant 41575100),the Special Fund for Meteorological Scientific Research in Public Interest (Grant GYHY201506002) （气象）
