多普勒雷达观测在北京7.21暴雨数值模拟中的三维变分同化研究

基于背景误差的特征长度理论,研究调整背景误差水平分辨率对多普勒雷达资料三维变分同化的影响。首先利用NMC方法针对暴雨落区统计不同水平分辨率的背景误差协方差,分析两种不同分辨率的背景误差的结构特征,研究水平分辨率对背景误差特征长度的影响。将其应用于雷达资料同化中,研究背景误差水平分辨率变化对雷达资料同化的影响。结果表明:背景误差水平分辨率由27 km提高到3 km时,在大气低层体现出更细致的动力场信息,其动力场水平特征长度按水平分辨率的二次根递减,而温度场与水汽场水平特征长度变化不明显。在将不同分辨率的背景误差用于三维变分同化时,更高分辨率的背景误差可以在分析场增量中体现更细致的中小尺度信息,能够明显改善雷达径向速度资料同化效果,并在随后的暴雨数值模拟中雨量及其分布形态更接近实况。

3D-VAR research of Doppler radar observation in numerical simulation of Beijing 7.21 torrential rain

Based on the de-correlation length theory of background error, the impact of the adjustment of background error horizontal resolution on 3-Dimensional Variational Assimilation (3D-VAR) of Dopplar radar data was studied. Firstly, the NMC method is used to gain the background error covariance of different horizontal resolution in torrential rain area. The structure characteristics of two background errors of different resolution and the impact of horizontal resolution on de-correlation length of background error covariance are both analyzed. Then it is applied into radar data assimilation in order to analyze the impact of background error horizontal resolution on the radar assimilation. Results show that when the horizontal resolution of the background error resolution increases from 27 km to 3 km, the lower atmosphere can reflect more meticulous information of dynamic field and the de-correlation length of dynamic field would decrease by secondary roots of the horizontal resolution, while the de-correlation of temperature field and water vapor field has no significant change. When applying them to 3D-VAR, the background with higher resolution would reflect more mesoscale information in the analysis field increments and significantly improve radar radial velocity data assimilation effect and the precipitation forecast effect in torrential rain simulation.