• 论文 •

### 基于贝叶斯模式平均的东江流域降雨概率预报

1. （1．中山大学 水资源与环境系，广州 510275；2．武汉大学 水资源与水电工程科学国家重点实验室，武汉 430072； 3．广东省东江流域管理局，广东 惠州 516000）
• 出版日期:2015-11-05 发布日期:2015-11-05
• 通讯作者: 王大刚（1975―），男，河北张家口人，副教授，主要从事陆地过程模拟和城市化气候效应研究，（E-mail）wangdag@mail.sysu.edu.cn。
• 作者简介:吴裕珍（1991―），女，广东珠海人，硕士研究生，主要从事气象气候预测研究，（E-mail）wuyzhen@mail.sysu.edu.cn
• 基金资助:

国家重点基础研究973项目（2013CB036400）；国家自然科学基金项目（51379224）；广东省水利科技创新项目

### Probabilistic Precipitation Forecasting over the Dongjiang Basin with BMA

WU Yuzhen1，ZHONG Yixuan2，WANG Dagang1，WU Wenjiao3

1. （1．Department of Water Resources and Environment，Sun Yat-sen University，Guangzhou 510275，China；2．State Key Laboratory of Water Resources and Hydropower Engineering Science，Wuhan University，Wuhan 430072，China；3．Administration of Dongjiang Basin of Guangdong，Huizhou 516000，China）
• Online:2015-11-05 Published:2015-11-05

Abstract:

To evaluate the performance of BMA (Bayesian Model Averaging) in forecasting precipitation in the Dongjiang basin and to provide the theoretical basis for the storm early warning system, the BMA-based prediction method is applied into precipitation forecast in the Dongjiang Basin. The evaluation is conducted for different lead time (i.e., 1-day, 3-days, 5-days, and 10-days) and different regions (i.e. up, mid and downstream) by using the TIGGE (The THORPEX Interactive Grand Global Ensemble) multi-model products. Conclusions are drawn as follows: 1) The forecasting skill of BMA is fairly good in forecasting accuracy for almost all regions and lead time. 2) The forecasting accuracy is improved by using BMA as compared with the original ensemble means, and the improvement is more significant for short lead time. 3) If the 95% percentile rainfall exceeds the disastrous rainfall amount, the early warning system and the preventive work should be initiated; however, the BMA forecasting results should be used with caution as the false warning would occasionally happen. 4) According to the results from our study, together with findings from other studies over different areas, we suggest that BMA would be suitable for precipitation forecasting and worth recommending.