Parametrization of radiation transfer through clouds is an important factor in the ability of Numerical Weather Prediction models to correctly describe the weather evolution. Here we present a practical parameterization of both liquid droplets and ice optical properties in the longwave and shortwave radiation. An advanced spectral averaging method is used to calculate the extinction coefficient, single scattering albedo, forward scattered fraction and asymmetry factor (b_ext, v, f, g), taking into account the nonlinear effects of light attenuation in the spectral averaging. An ensemble of particle size distributions was used for the ice optical properties calculations, which enables the effective size range to be extended up to 570 μm and thus be applicable for larger hydrometeor categories such as snow, graupel, and rain. The new parameterization was applied both in the COSMO limited-area model and in ICON global model and was evaluated by using the COSMO model to simulate stratiform ice and water clouds. Numerical weather prediction models usually determine the asymmetry factor as a function of effective size. For the first time in an operational numerical weather prediction (NWP) model, the asymmetry factor is parametrized as a function of aspect ratio. The method is generalized and is available on-line to be readily applied to any optical properties dataset and spectral intervals of a wide range of radiation transfer models and applications.

中文翻译：

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业务数值天气预报模型中液云和冰云光学特性的参数化

通过云的辐射传输的参数化是数值天气预报模型正确描述天气演变能力的重要因素。在这里，我们介绍了在长波和短波辐射中液滴和冰光学特性的实用参数化。先进的光谱平均方法用于计算消光系数，单散射反照率，前向散射分数和不对称因子（b _ext，v，f​​，g），并考虑到光谱平均中光衰减的非线性影响。粒径分布的整体用于冰的光学性质计算，这使得有效粒径范围可以扩展到570μm，因此适用于较大的水凝物类别，例如雪，gra和雨水。新的参数化已应用到COSMO有限区域模型和ICON全局模型中，并通过使用COSMO模型模拟层状冰和水云进行了评估。数值天气预报模型通常将不对称因子确定为有效大小的函数。在可操作数值天气预报（NWP）模型中，首次将不对称因子参数化为长宽比的函数。