A spatial-temporal projection model for 10-30 day rainfall forecast in South China
| LEADER | caa a22 4500 | ||
|---|---|---|---|
| 001 | 605473919 | ||
| 003 | CHVBK | ||
| 005 | 20210128100345.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150301xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00382-014-2215-4 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00382-014-2215-4 | ||
| 245 | 0 | 2 | |a A spatial-temporal projection model for 10-30 day rainfall forecast in South China |h [Elektronische Daten] |c [Pang-Chi Hsu, Tim Li, Lijun You, Jianyun Gao, Hong-Li Ren] |
| 520 | 3 | |a 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. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Extended range forecast |2 nationallicence | |
| 690 | 7 | |a Spatial-temporal projection model |2 nationallicence | |
| 690 | 7 | |a Low-frequency oscillation |2 nationallicence | |
| 700 | 1 | |a Hsu |D Pang-Chi |u Earth System Modeling Center and Key Laboratory of Meteorological Disaster, College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, China |4 aut | |
| 700 | 1 | |a Li |D Tim |u International Pacific Research Center, University of Hawaii, Honolulu, HI, USA |4 aut | |
| 700 | 1 | |a You |D Lijun |u Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China |4 aut | |
| 700 | 1 | |a Gao |D Jianyun |u Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China |4 aut | |
| 700 | 1 | |a Ren |D Hong-Li |u Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China |4 aut | |
| 773 | 0 | |t Climate Dynamics |d Springer Berlin Heidelberg |g 44/5-6(2015-03-01), 1227-1244 |x 0930-7575 |q 44:5-6<1227 |1 2015 |2 44 |o 382 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00382-014-2215-4 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00382-014-2215-4 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Hsu |D Pang-Chi |u Earth System Modeling Center and Key Laboratory of Meteorological Disaster, College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Li |D Tim |u International Pacific Research Center, University of Hawaii, Honolulu, HI, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a You |D Lijun |u Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Gao |D Jianyun |u Fujian Climate Center, China Meteorological Administration, Fuzhou, Fujian, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Ren |D Hong-Li |u Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Climate Dynamics |d Springer Berlin Heidelberg |g 44/5-6(2015-03-01), 1227-1244 |x 0930-7575 |q 44:5-6<1227 |1 2015 |2 44 |o 382 | ||