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首页> 外文期刊>Acta Meteorologica Sinica >Microphysical Retrieval from Doppler Radar Reflectivity Using Variational Data Assimilation
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Microphysical Retrieval from Doppler Radar Reflectivity Using Variational Data Assimilation

机译：利用变分数据同化从多普勒雷达反射率进行微物理反演

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摘要

One of the microphysical variables, the rainwater mixing ratio q_r, is retrieved from the observed reflectivity of Doppler radar by a 3D variational data assimilation system. The q_r as an analysis variable is obtained by minimizing a cost function defined as the difference between observed radar reflectivity and its retrieval from q_r, plus the difference between q_r and its background field from a mesoscale model's prediction. Covariance matrix of the background field's error is determined by the so-called NMC method. A method called the second-order auto-regression (SOAR) is used to calculate the coefficients of regressive filtering 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 sensitivity experiment proves that the random error of observed reflectivity has effect on the analyzed results. At last an experiment with observed data from the Doppler radar at Ma'anshan City in Anhui Province on 19 June 2002 was performed. The retrieved analysis variable q_r in this test shows structures in detail, which coincide with the distribution of the echo picture observed by the radar.
机译：通过3D变异数据同化系统，从多普勒雷达的反射率中检索出雨水混合比q_r是微物理变量之一。通过最小化成本函数来获得q_r，该成本函数定义为观测雷达反射率与其从q_r取回之间的差，加上q_r与中尺度模型预测的背景场之间的差。背景场误差的协方差矩阵由所谓的NMC方法确定。在空间变换过程中，使用一种称为二阶自回归（SOAR）的方法来计算回归滤波系数，以适应诸如积云之类的小空间尺度。理想的实验证明了该系统的正确性，灵敏度实验证明了观测到的反射率的随机误差对分析结果有影响。最后，利用2002年6月19日在安徽省马鞍山市的多普勒雷达观测到的数据进行了实验。在此测试中检索到的分析变量q_r详细显示了结构，这些结构与雷达观测到的回波图像的分布相一致。

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