A Spatial-Temporal Projection Model for 10-30 Day Rainfall Forecast in South China
- 作者：Pang-Chi HsuTim LiLijun YouJianyun GaoHong-Li Ren
- 会议时间：2014-09-10
- 作者单位：Pang-Chi Hsu(Earth System Modeling Center and Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, China)Tim Li(International Pacific Research Center, University of Hawaii, Honolulu, Hawaii;Earth System Modeling Center and Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing, China)Lijun You,Jianyun Gao(Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China)Hong-Li Ren(Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China)
- 母体文献：第八届全国优秀青年气象科技工作者学术研讨会论文集
- 会议名称：第八届全国优秀青年气象科技工作者学术研讨会
- 会议地点：江苏宜兴
- 主办单位：中国气象学会
- 语种：chi
摘要
Extended-range (10-30 day) forecast, lying between well-developed short-range weather and long-range (monthly and seasonal) climate predictions, is one of the most challenging forecast currently faced by operational meteorological centers around the world.In this study, a set of spatial-temporal projection (STP) models was developed to predict low-frequency rainfall events at lead times of 5-30 days.We focused on early monsoon rainy season (mid April to mid July) in South China.To ensure that the model developed can be used for real-time forecast, a non-filtering method was developed to extract the low-frequency atmospheric signals of 10-60 days without using a band-pass filter.The empirical models were built based on 12-yr (1996-2007) data, and independent forecast was then conducted for a 5-yr (2008-2012) period.The assessment of the 5-year forecast of rainfall over South China indicates that the ensemble prediction of the STP models achieved a useful skill (with a temporal correlation coefficient exceeding 95% confidence level) at a lead time of 20 days.The amplitude error was generally less than one standard deviation at all lead times of 5-30 days.Furthermore, the STP models provided useful probabilistic forecasts with the ranked probability skill score between 0.3-0.5 up to 30-day forecast in advance.The evaluation demonstrated that the STP models exhibited useful 10-30 day forecast skills for real-time extended-range rainfall prediction in South China.