论文部分内容阅读
为了调整优化基于WRF模式的民航京沪穗数值预报系统在广州本地的预报效果,使用3组不同的物理参数化方案和资料同化方案组合,对发生在2011年10月13日~14日广东地区的暴雨过程进行模拟。降水预报结果显示不同物理参数化方案和资料同化方案对降水预报有较大的影响,使用香港城市大学大气研究实验室实时预报系统推荐的参数化方案的降水预报好于加拿大温哥华地区业务运行的参数化方案,使用香港的方案,不同化自动站资料的预报效果好于同化自动站资料。而环流形势场、相对湿度场、水汽通量场和CAPE指数场对不同参数化方案的敏感性要小于降水场,另外还分析了系统连续15天预报结果。最终结果表明,不论是降水场还是形势场,使用香港城市大学的方案并且不同化自动站资料的评分优于其他2种方案,可以作为广州本地业务方案使用。
In order to adjust and optimize the prediction effect of the Civil Aviation Beijing-Shanghai Spike Numerical Prediction System based on WRF model in Guangzhou, three sets of different physical parameterization schemes and data assimilation schemes were used. Rainstorm process simulation. Precipitation forecast results show that different physical parameterization schemes and data assimilation schemes have a greater impact on precipitation forecasting. Precipitation forecast using the parameterization scheme recommended by the Real-time Forecasting System of City University of Hong Kong Laboratory is better than the operational parameters in Vancouver, Canada The scheme of using Hong Kong’s scheme and the effect of forecasting the data of different automated stations are better than those of assimilating automatic stations. Circumferential field, relative humidity field, water vapor flux field and CAPE index field are less sensitive to different parameterized schemes than precipitation field. In addition, the forecast results of 15 consecutive days are also analyzed. The final result shows that the use of the Hong Kong City University scheme and the disaggregation of automated station data outperformed the other two schemes in both the precipitation and the situational scenarios and could be used as a local business scenario in Guangzhou.