A new method has been developed to directly assimilate volume scans of radar reflectivity data with 4D‐Var in the Met Office Unified Model. The method has been demonstrated in the convective‐scale hourly‐cycling UKV forecast model. Reflectivity observations from 18 C‐band radars in the British Isles are assimilated. This article describes the method of observation processing and quality control, the observation operator, and assimilation method. The assimilation method uses a minimum threshold rainwater content in the forward operator to give sensitivity to reflectivity observations where there is no rain in the background. Furthermore, the use of the Huber norm in the observation penalty function allows the use of observations with large innovations in the assimilation. A change was made to the precipitation efficiency in the microphysics scheme of the linear perturbation forecast model to ensure stability of the scheme. A case‐study is presented which demonstrates how the inclusion of reflectivity observations enhances convergence through analysis increments to the wind field, leading to improvements to the location of convective precipitation features in the forecast. Two‐month trials for summer and winter seasons demonstrate significant improvements to rain forecasts in the nowcasting range.

中文翻译：

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在Met Office Unified模型中使用每小时循环4D-Var进行雷达反射率同化

已开发出一种新方法，可以在Met Office统一模型中使用4D-Var直接吸收雷达反射率数据的体积扫描。该方法已在对流规模小时循环UKV预测模型中得到证明。来自不列颠群岛的18个C波段雷达的反射率观测被吸收。本文介绍了观测处理和质量控制的方法，观测算子以及同化方法。同化方法在前向算子中使用最小阈值雨水含量，以对背景无雨的反射率观测值保持灵敏度。此外，在观察罚函数中使用Huber范数可以在同化中使用具有重大创新的观察。为了确保方案的稳定性，对线性扰动预测模型的微物理方案中的降水效率进行了更改。案例研究表明，反射率观测的纳入如何通过对风场的分析增量来增强收敛性，从而改善对流降水特征在预报中的位置。在夏季和冬季进行的为期两个月的试验表明，临近预报范围的降雨预报有了显着改善。从而改善了对流降水特征在预报中的位置。在夏季和冬季进行的为期两个月的试验表明，临近预报范围的降雨预报有了显着改善。从而改善了对流降水特征在预报中的位置。在夏季和冬季进行的为期两个月的试验表明，临近预报范围的降雨预报有了显着改善。