应用雷达回波强度资料反演大气云微物理量

MICROPHYSICAL RETRIEVAL FROM DOPPLER RADAR REFLECTIVITY USING VARIATIONAL DATA ASSIMILATION

文中利用三维变分原理 ,由多普勒天气雷达回波强度反演模式大气的雨水混合比 qr,分析变量 qr 的确定取决于对目标函数的极小化计算 ,目标函数由分析变量 qr 与 qr 的背景场之差 ,以及由分析变量演算的大气回波强度与雷达观测的回波强度之差构成。采用所谓的NMC方法求取模式变量的背景场误差协方差矩阵 ,采用二阶自回归型相关函数确定空间水平变换中的递归滤波系数以适用于反映积云结构的小尺度空间。通过理想数值试验 ,验证了变分同化系统和结果的合理性 ,由敏感性试验说明了雷达观测的回波强度随机误差对于反演的qr 值有一定的影响。对 2 0 0 2年 6月 19日安徽省马鞍山市一次多普勒雷达实际观测数据的个例试验表明 ,经过变分同化反演后的积云尺度模式大气的 qr 场与观测的雷达回波图像的细节相吻合。

One of the Microphysical variables, the rainwater mixing ratio q_r, was retrieved from Doppler radar observed reflectivity by a 3D variation data assimilation system. The q_r as analysis variable was determined by minimizing a cost function defined by the difference between radar observed reflectivities and their retrieve from q_r, plus the difference between q_r and their background field from a mesoscale model prediction. The covariance matrix of background field errors was determined by so called NMC method. The Second-order Auto-regressive (SOAR) method is used to calculate the coefficients of regressive filter to fit in with small spatial scale such as cumulus in the process of spatial transformation. An ideal experiment demonstrates the correctness of this system and a sensitive experiment proves that the random errors of observed reflectivity have effect on the analyzed results. At last an experiment with real data from the Doppler radar at Maanshan City in Anhui Province on June 19 of 2002 was performed. The retrieved analysis variable qr in this test shows the detailed structures, which coincide with the distribution of the echo picture observed by the radar.