一种基于WRF模式的可能最大暴雨估算新方法

数值天气模式能通过大气物理方程概化气象因子与暴雨关系,基于此模式的暴雨因子放大法已成为估算可能最大暴雨(PMP)的重要途径。考虑到风速在地形作用下能够影响水汽垂直运动,进而与水汽辐合共同影响降雨,增加风速作为放大因子,提出了基于WRF模式的水汽风速放大法估算PMP,即通过大量敏感性试验,研究水汽、风速放大的垂直层数、水平范围、倍比,诊断水汽、风速因子与PMP的正相关性,同时通过因子组合放大确定能产生最大降雨的最恶劣暴雨情景。将其应用于湖北咸宁核电厂暴雨预测中,与基于线性假定的传统水汽风速放大法相比,该法从因子放大后暴雨特征的同向增强效应角度确定最不利暴雨,更为科学合理。

A New Method for Estimating Probable Maximum Rainstorm Based on WRF Model

The numerical weather model can better generalize the relationship between storm and its factor using atmospheric physical equations. The storm factor amplification method based on this model has become an important way to estimate probable maximum precipitation (PMP). Considering that under the topography, wind speed could affect the moisture vertical movement and rainfall with the moisture convergence, we proposed the maximization method of combining moisture and wind speed based on WRF model to estimate PMP, i.e., through a large number of sensitivity tests, vertical layers, horizontal ranges and maximizing ratio of moisture and wind speed were diagnosed and determined, and then the worst rainstorm was obtained. Applied to Xianning nuclear power plant in Hubei Province, compared with the traditional moisture and wind speed maximization method based on linear assumption, this method is more reasonable because the worst rainstorm is determined based on the same storm effect of factor maximization.