caa a22 4500 605473919 CHVBK 20210128100345.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s00382-014-2215-4 doi (NATIONALLICENCE)springer-10.1007/s00382-014-2215-4 A spatial-temporal projection model for 10-30 day rainfall forecast in South China [Elektronische Daten] [Pang-Chi Hsu, Tim Li, Lijun You, Jianyun Gao, Hong-Li Ren] Extended-range (10-30days) 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 5-30days. We focused on early monsoon rainy season (mid April-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 10-60days without using a band-pass filter. The empirical models were built based on 12-year (1996-2007) data, and independent forecast was then conducted for a 5year (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 20days. The amplitude error was generally less than one standard deviation at all lead times of 5-30days. 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 10-30days forecast skills for real-time extended-range rainfall prediction in South China. Springer-Verlag Berlin Heidelberg, 2014 Extended range forecast nationallicence Spatial-temporal projection model nationallicence Low-frequency oscillation nationallicence Hsu Pang-Chi Earth System Modeling Center and Key Laboratory of Meteorological Disaster, College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, China aut Li Tim International Pacific Research Center, University of Hawaii, Honolulu, HI, USA aut You Lijun Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China aut Gao Jianyun Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China aut Ren Hong-Li Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China aut Climate Dynamics Springer Berlin Heidelberg 44/5-6(2015-03-01), 1227-1244 0930-7575 44:5-6<1227 2015 44 382 https://doi.org/10.1007/s00382-014-2215-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00382-014-2215-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Hsu Pang-Chi Earth System Modeling Center and Key Laboratory of Meteorological Disaster, College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, China aut NATIONALLICENCE 700 1- Li Tim International Pacific Research Center, University of Hawaii, Honolulu, HI, USA aut NATIONALLICENCE 700 1- You Lijun Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China aut NATIONALLICENCE 700 1- Gao Jianyun Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China aut NATIONALLICENCE 700 1- Ren Hong-Li Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China aut NATIONALLICENCE 773 0- Climate Dynamics Springer Berlin Heidelberg 44/5-6(2015-03-01), 1227-1244 0930-7575 44:5-6<1227 2015 44 382