A Study of the Scale-Aware Physical Parameterizations in High-Resolution Numerical Weather Prediction Models
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摘要: 随着高性能计算能力的提升，数值天气预报模式的分辨率迅速提升。但由于对流、云和边界层过程参数化方案对于模式分辨率的高度依赖性，直接或简单地提高模式分辨率会导致诸如“灰色尺度”等问题。“灰色尺度”问题将极大地限制数值天气预报模式在高分辨率条件下性能的提高，甚至导致预报准确率下降，这是高分辨数值天气预报和气候模拟所面临重要的挑战之一。发展了适用于高分辨率的分辨率自适应的次网格混合（包括边界层混合）参数化方案和分辨率自适应的对流参数化方案，为高分辨率业务天气预报模式提供物理过程方面的理论和实践基础。Abstract: The resolution of numerical weather prediction models will continually increase with increasing computer power. Physical processes parameterizations associated with convection, cloud and planetary boundary layer (PBL) depend on the resolutions of model. These motions can be partially resolved by grid scale dynamics. However, a substantial part of turbulent motion still needs to be parameterized, which results in the so-called gray zone problem. The gray zone problem can hugely downgrade the forecast skill of the numerical prediction models. In this study, a scale-aware subgrid mixing (including turbulence in PBL) scheme and a scale-aware cumulus convection scheme are developed. The new schemes will adapt to the model grid size as it is varied through the gray zone.This study will provide theoretical and technical supports for the development of high-resolution numerical weather model and operational prediction.
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Keywords:
- physical parameterizations /
- scale aware /
- gray zone /
- turbulence /
- convection
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