【摘要】 2021年7月17—22日河南省发生了一次历史罕见的持续性强降水，造成了巨大的经济损失。目前极端降水预报仍是次季节气候预测研究的热点和难点。区域气候模式有着比全球模式更精细的空间分辨率和更为完善的物理过程参数化方案，为进一步提高中国次季节降水预报能力提供了新途径。使用区域气候模式CWRF(regional Climate-Weather Research and Forecasting model)对中国气象局全球气候模式次季节预测系统CMA＿CPSv3(China Meteorological Administration Climate Prediction System version 3)的预报结果进行中国区域动力降尺度，分析了CWRF和CMA＿CPSv3模式对河南省2021年7月17—22日持续性强降水的预测效果。结果表明，区域模式和全球模式预报的降水空间分布和量级存在明显差异。尽管两个模式都低估了此次强降水过程的降水量，但总体上CWRF模式预报的降水量更大且更好地捕捉到了降水的空间分布。CWRF模式自6月26和29日起报的降水预报明显好于同一起报日CMA＿CPSv3模式的预报结果。与CMA＿CPSv3预报相比，CWRF显著地改善了东亚低空风场和低空急流的预报。CWRF对低空急流和水汽通量输送方向的改善尤为明显，预报的水汽在山脉的迎风坡辐合，为降水提供了有利的水汽条件。同时CWRF更好地预报了郑州上空的垂直上升运动，这些改善都有利于CWRF模式对降水有更高的预报技巧。更多还原

【Abstract】 An unprecedented persistent heavy precipitation occurred in Henan province during 17—22 July 2021, causing huge economic losses. Currently, extreme precipitation forecasting is still a hotspot and a difficult issue in sub-seasonal climate prediction research. Regional climate models provide a new way to further improve sub-seasonal precipitation forecasting in China with finer spatial resolution and better parameterization of physical processes compared to that of the global models. This study uses the regional Climate-Weather Research and Forecasting model(CWRF) nested with the China Meteorological Administration Climate Prediction System version 3(CMA＿CPSv3) to improve prediction capabilities for this persistent heavy precipitation event. It is shown that the spatial distribution, magnitude, and forecast accuracy of precipitation predicted by CWRF are improved compared to that predicted by CMA＿CPSv3. Although both models underestimate the amount of precipitation, the CWRF forecasts larger accumulated precipitation and spatial distribution of precipitation is more consistent with observation. CWRF forecasts initialized on26 June and 29 June are better than that of CMA＿CPSv3 on the same initial dates. The CWRF significantly improves the forecast of low-level wind fields and low-level jets in East Asia compared with the CMA＿CPSv3. The CWRF is particularly effective in improving the simulation of directions of low-level jets and water vapor fluxes, allowing water vapor to converge on the windward slopes of mountain ranges and providing favorable water vapor conditions for precipitation. The CWRF better forecasts the water vapor flux convergence and ascending motions over Zhengzhou, and all these improvements lead to higher precipitation forecasting skill of CWRF.更多还原