Abstract: The precipitation forecast performance of GRAPES_Meso model with 3 km spatial resolution and its cloud analysis system was investigated and compared through numerical experiments for 13 heavy rainfall cases in summer and batch forecast in July 2018 in Northwest China. The results are as follows: (1) GRAPES_Meso model with 3 km spatial resolution had a good forecasting skill and stable performance for precipitation forecast in Northwest China, it could provide favourable outputs for short-term forecasting and nowcasting business. The average threat score of light rain and above for 13 heavy rainfall cases was between 0.5 and 0.6, while the threat score of batch experiments in July was slightly worse than that of 13 heavy rainfall cases. (2) By introducing observed data of radar reflectivity, satellite TBB and CTA, the cloud analysis system could reasonably adjust cloud water, rain water and other hydrometeor content, consequently reduce spin-up time in the mesoscale model and improve the forecast ability of precipitation with different magnitudes. However, the forecast results of cyclic assimilations in cloud analysis system weren’t stable. (3) The predicted coverage of radar echo by GRAESP_Meso model and cloud analysis system was consistent with observations, while the intensity of composite reflectivity was higher than the observations.

Key words: GRAPES_Meso model, cloud analysis system, Northwest China, precipitation forecast

摘要： 应用GRAPES_Meso模式(3 km)及其云分析系统，对中国西北地区2018年夏季13次强降水天气过程进行数值预报试验，并就7月天气开展了批量试验，检验评估该模式系统在西北地区的降水预报效果。结果表明：（1）该模式对西北地区降水有着良好且稳定的预报能力，小雨及以上量级降水TS评分在13个强降水个例中平均为0.5~0.6，而批量试验平均为0.4~0.5，可为短临天气预报业务提供支撑；（2）云分析系统能够对模式中水凝物含量进行合理调整，提高了各量级降水预报质量，但云分析系统的循环同化预报结果表现不稳定；（3）预报的雷达回波范围和观测较一致，但强度较观测偏高。

关键词: GRAPES_Meso模式, 云分析系统, 西北地区, 降水预报