An efficient modular volume‐scanning radar forward operator for NWP models: description and coupling to the COSMO model
An efficient modular volume‐scanning radar forward operator for NWP models: description and coupling to the COSMO model
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DOI：
10.1002/qj.2904
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发表时间：
2016-10
影响因子：
8.9
通讯作者：
Yuefei Zeng;U. Blahak;Dorit Jerger
中科院分区：
文献类型：
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作者：
Yuefei Zeng;U. Blahak;Dorit Jerger
由于雷达观测在空间和时间分辨率上高度密集，因此通常用于通过详细模型验证和 3D 雷达数据同化来改进短期数值天气预报 (NWP)。然而，观测到的量不能直接与 NWP 模型的预报变量（例如水凝物密度、风矢量、温度、压力等）进行比较，因此促进这种比较的常见方法是从模型变量中导出合成雷达观测值；这就是所谓的“雷达前向算子”。在本文中，介绍了一种用于多普勒速度和反射率的新型高效模块化体积扫描雷达操作器 (EMVORADO)。尽管它是在 COSMO 模型框架中开发的，但它也可以在线耦合到任何其他 NWP 模型。雷达测量的综合物理方面（例如波束弯曲/加宽/屏蔽、具有下降速度和反射率加权的多普勒速度、衰减反射率、可检测信号等）已以模块化方式实现，使用具有不同近似水平和数值成本的最先进方法，可以选择。从预测模型变量推导的反射率尽可能“模型一致”，并仔细考虑与部分熔化颗粒相关的不确定性。超级计算机的效率和适用性（MPI 并行性）是一项主要设计标准，它使我们能够在一个模型运行中模拟 3D 体积扫描气象雷达的整个网络，并使 EMVORADO 非常适合操作应用。本文旨在对 EMVORADO 进行全面描述，并通过一些选定的案例研究提供对不同模块性能的初步了解。
Since radar observations are highly dense in spatial and temporal resolutions, they have been often used to improve short‐term numerical weather prediction (NWP) by means of detailed model verification and 3D radar data assimilation. However, the observed quantities are not directly comparable to the prognostic variables of NWP models (e.g. hydrometeor densities, wind vector, temperature, pressure, etc.), so a common approach to facilitate this comparison is to derive synthetic radar observations from model variables; this is the so‐called ‘radar forward operator’. In the present article, a new Efficient Modular VOlume scanning RADar Operator (EMVORADO) for Doppler velocity and reflectivity is introduced. Although it has been developed in the COSMO model framework, it can be also coupled online to any other NWP model. Comprehensive physical aspects of radar measurements (e.g. beam bending/broadening/shielding, Doppler velocity with fall speed and reflectivity weighting, attenuated reflectivity, detectable signal, etc.) have been implemented in a modular way, using state‐of‐the‐art methods with different levels of approximation and numerical costs that can be optionally chosen. The reflectivity derivation from the prognostic model variables is as ‘model consistent’ as possible and carefully honours the uncertainties associated with partially melted particles. Efficiency and applicability on supercomputers (MPI‐parallelism) is a major design criterion, which allows us to simulate entire networks of 3D volume‐scanning meteorological radars within one model run and makes EMVORADO well suited for operational applications. This article aims to give a thorough description of the EMVORADO and to provide a first insight to the performance of different modules by some selected case‐studies.