Assimilation of Reflectivity Data in a Convective-Scale, Cycled 3DVAR Framework with Hydrometeor Classification
Assimilation of Reflectivity Data in a Convective-Scale, Cycled 3DVAR Framework with Hydrometeor Classification
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DOI：
10.1175/jas-d-11-0162.1
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发表时间：
2012-03
影响因子：
3.1
通讯作者：
Jidong Gao;D. Stensrud
中科院分区：
文献类型：
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作者：
Jidong Gao;D. Stensrud
摘要利用2003年5月8日的一个理想雷暴个例和一个真实的个例，探讨了间歇循环三维变分同化（3DVAR）系统同化雷达反射率和径向速度资料的影响。提出了一种新的雷达反射率正演算子，它利用数值天气预报模式提供的背景温度场进行水凝物自动分类。三种类型的实验进行理想化和真实的数据的情况下。第一个实验仅使用径向速度数据，第二个实验使用径向速度和反射率数据而不进行水凝物分类，最后一个实验使用径向速度和反射率数据并进行水凝物分类。所有实验都使用数值模型预测将分析状态提前到下一个观察时间，然后将其用作下一次分析的背景。从理想化和真实的数据的情况下，结果表明，.
AbstractThe impact of assimilating radar reflectivity and radial velocity data with an intermittent, cycled three-dimensional variational assimilation (3DVAR) system is explored using an idealized thunderstorm case and a real data case on 8 May 2003. A new forward operator for radar reflectivity is developed that uses a background temperature field provided by a numerical weather prediction model for automatic hydrometeor classification. Three types of experiments are performed on both the idealized and real data cases. The first experiment uses radial velocity data only, the second experiment uses both radial velocity and reflectivity data without hydrometeor classification, and the final experiment uses both radial velocity and reflectivity data with hydrometeor classification. All experiments advance the analysis state to the next observation time using a numerical model prediction, which is then used as the background for the next analysis. Results from both the idealized and real data cases show that...