为研究不同物理过程参数化方案对江淮梅雨降水预报的影响,基于WRFv4.4.2,利用GFS预报数据、第六版MODIS土地覆盖类型产品和ERA5-Land观测数据集,使用均方根误差、相关系数、公平技巧评分和偏差评分等方法,模拟评估Ferrier、WSM6和Thompson这3种云微物理过程参数化方案,以及KF、BMJ和Tiedtke这3种积云对流参数化方案共9种组合,对2020年7月14日00：00—17日00：00江淮流域梅雨期一次降水过程的预报效果进行分析。结果表明,（1）积云对流参数化方案对江淮梅雨降水预报有更为明显的影响,使用BMJ可以获得较好的预报结果;（2）WRF模式在山地、城市等区域表现不佳,在平原、农田等区域表现尚可,适用性存在一定不足;（3）在江淮流域北部地区（32.7 °N以上）使用WSM6和BMJ的实验组合综合表现较佳,可较为准确地预报降水过程变化趋势,对小雨和中雨量级的降水落区有较高的预报技巧。为今后江淮梅雨期降水预报提供参考。
In order to investigate the impact of different physical process parameterization schemes on the forecast of Meiyu precipitation in the Jianghuai region, based on WRFv4.4.2, GFS forecast data, the sixth edition MODIS land cover type product, and ERA5 Land observation dataset were used to simulate and evaluate three cloud microphysical process parameterization schemes, Ferrier, WSM6, and Thompson, as well as nine combinations of three cumulus convective parameterization schemes, KF, BMJ, and Tiedtke, using methods such as root mean square error, correlation coefficient, fair skill score, and bias score. The forecast effect of a precipitation process during the Meiyu period in the Jianghuai River Basin from 00:00 on July 14, 2020 to 00:00 on July 17, 2020 was evaluated. The results indicated that (1) the parameterization scheme of cumulus convection had a more significant impact on the precipitation forecast of Jianghuai plum rain, and using BMJ could obtain better forecast results; (2) the WRF model performed poorly in mountainous and urban areas, but fairly well in plains, farmland, and other areas, with certain limitations in applicability; (3) the experimental combination of WSM6 and BMJ performed well in the northern region of the Jianghuai region (above 32.7°N), and could accurately predict the trend of precipitation process changes. It had high forecasting skills for precipitation areas of light rain and moderate rain levels. The purpose was to provide references for future precipitation forecasting during the Jianghuai region rain season.
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