| 中国南方降水及其极端事件的动力-统计相结合延伸期预报 |
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| 引用本文： | 张可越,李娟,徐邦琪,朱志伟.中国南方降水及其极端事件的动力-统计相结合延伸期预报[J].气象学报,2023,81(1):79-93. |
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| 作者姓名： | 张可越 李娟 徐邦琪 朱志伟 |
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| 作者单位： | 南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心，南京，210044 |
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| 基金项目： | 国家自然科学基金基础科学中心项目（42088101）、国家重点研发计划重点专项（2018YFC1505803） |
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| 摘 要： | 延伸期预报是无缝隙预测系统中的薄弱环节，如何提高灾害天气过程的延伸期预报技巧是国际热点及前沿问题。本研究基于2005年12月—2014年8月的观测/再分析资料，通过奇异值分解方法，揭示了与中国南方低频降水变化高度耦合的热带对流和中纬度波列信号。利用中国气象局参加国际次季节至季节预报计划模式（BCC-CPS-S2Sv2模式，简称BCC S2S模式）的回报数据，对中国南方低频降水异常场进行统计降尺度，构建了一套动力-统计相结合的延伸期降水预测模型。独立预测时段（2014年12月—2019年8月）的结果表明，BCC S2S模式可以提前10—15 d预报中国南方大部分区域的异常降水；提前15—20 d以上预报时，动力-统计结合预报模型对冬季（夏季）华南沿海地区（长江以北地区）的降水时间演变、降水空间分布及极端强降水事件的预报技巧均优于BCC S2S模式。文中提出的思路和方法可广泛应用于其他区域气象要素和极端天气事件的延伸期预报。
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| 关 键 词： | 动力-统计结合 延伸期预报 S2S模式 中国南方降水 |
| 收稿时间： | 2022-04-06 |
| 修稿时间： | 2022-07-27 |
The dynamical-statistical extended-range prediction of precipitation and extreme precipitation events over southern China |
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| Affiliation: | Key Laboratory of Meteorological Disaster，Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters，Nanjing University of Information Science and Technology，Nanjing 210044，China |
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| Abstract: | How to improve the extended-range predictive skill is a hotspot and frontier research issue, which is crucial for bridging the gap in seamless prediction system. Based on the observations and reanalysis data during December 2005—August 2014, the Singular Value Decomposition analysis is used to reveal the highly coupled modes between the low-frequency precipitation over southern China and intraseasonal tropical convection/mid-latitude wave trains in boreal winter and summer, respectively. The BCC-CPS-S2Sv2 (hereafter referred to as BCC S2S) model provided by China Meteorological Administration is used to construct a set of dynamical-statistical models for subseasonal prediction of low-frequency precipitation anomalies over southern China using the statistical downscaling method. The BCC S2S model participates the Subseasonal-to-Seasonal Project and exhibits reasonable skills on the forecast of rainfall anomalies over most of southern China at 10—15 d forecast lead times during the independent prediction period of December 2014—August 2019. However, the dynamical-statistical model outperforms the BCC S2S model on precipitation forecast in terms of temporal variability over coastal region of South China (north of the Yangtze river) during winter (summer) and the spatial distribution and extreme events beyond 15—20 d forecast lead. The idea and method proposed by this study can be widely applied to extended-range prediction of other regional meteorological elements and extreme events. |
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