强对流天气预报的不确定性很大，集合预报是定量估计预报不确定性的动力学方法。联合概率方法是基于集合预报模式输出，综合考虑多个重要物理参数的不确定性，进而预报天气事件可能发生的关键区。通过时空匹配2009—2015年4～9月（暖季）安徽省80个国家站逐日灾害性天气观测资料、降水观测资料和美国国家环境预报中心（NCEP）的FNL资料，借鉴“配料法”思路统计分析得到弱降水对流、强降水对流天气各4个具有较好表征意义的对流参数及各对流参数在暖季逐月的阈值，据此建立弱降水对流、强降水对流联合概率预报方程。利用2016—2017年4～9月欧洲中期天气预报中心（ECMWF）集合预报产品和同期观测资料开展联合概率预报的系统性ROC检验和不同天气过程检验。结果表明，联合概率方法对于是否发生弱降水对流或强降水对流具有良好的分辨能力，对判别强降水对流发生与否更优，不同时效的预报表现相当。弱降水对流联合概率对于区域性或范围较小的对流天气均具有较好的指示性，但也存在一定程度的空报。强降水对流联合概率对于区域性集中短时强降水具有良好的指示作用，对较小范围的强降水也具有一定指示意义。此方法也存在个别漏报，可以大致将10%作为联合概率预报阈值以获得较高的TS评分。基于集合预报的联合概率方法可以为强对流天气提供具有实用价值的短期概率预报指导。

In consideration of large uncertainties in severe convective weather forecast, ensemble forecasting is a dynamic method developed to quantitatively estimate forecast uncertainty. Based on ensemble output, joint probability is a post-processing method to delineate key areas where weather event may actually occur by taking account of the uncertainty of several important physical parameters. An investigation of the environments of little rainfall convection and strong rainfall convection from April to September (warm season) during 2009-2015 was presented using daily disastrous weather data, precipitation data of 80 stations in Anhui province and NCEP Final Analysis (FNL) data. Through ingredients-based forecasting methodology and statistical analysis,four convective parameters characterizing two types of convection were obtained, respectively, which were used to establish joint probability forecasting together with their corresponding thresholds. Using the ECMWF ensemble forecast and observations from April to September during 2016-2017, systematic verification mainly based on ROC and case study of different weather processes were conducted. The results demonstrate that joint probability method is capable of discriminating little rainfall convection and non-convection with comparable performance for different lead times, which is more favorable to identifying the occurrence of strong rainfall convection. The joint probability of little rainfall convection is a good indication for the occurrence of regional or local convection, but may produce some false alarms. The joint probability of strong rainfall convection is good at indicating regional concentrated short-term heavy precipitation as well as local heavy rainfall. There are also individual missing reports in this method, and in practice, 10% can be roughly used as joint probability threshold to achieve relative high TS score. Overall, ensemble-based joint probability method can provide practical short-term probabilistic guidance for severe convective weather.