Predicting summer rainfall in the Yangtze River basin with neural networks
作者： Heike Hartmann , Stefan Becker , Lorenz King
DOI: 10.1002/JOC.1588
关键词:
摘要: Summer rainfall in the Yangtze River basin is predicted using neural network techniques. Input variables (predictors) for are Southern Oscillation Index (SOI), East Atlantic/Western Russia (EA/WR) pattern, Scandinavia (SCA) Polar/Eurasia (POL) pattern and several indices calculated from sea surface temperatures (SST), level pressures (SLP) snow data December to April period 1993 2002. The output variable of May September 1994 2002, which was previously classified into six different regions by means a principal component analysis (PCA). Rainfall 2002. The winter SST SLP identified be most important predictors summer basin. Tibetan Plateau depth, SOI other teleconnection seem minor importance an accurate prediction. This may result length available time series, does not allow deeper impact multi-annual oscillations. The algorithms proved capable explaining variability For five out regions, our predictions explain at least 77% total variance measured rainfall. Copyright © 2007 Royal Meteorological Society
lehman.edu 参考文章(29)
Xu Qun, Analysis of causes and seasonal prediction of the severe floods in Yangtze / Huaihe basins during summer 1991 Advances in Atmospheric Sciences. ,vol. 12, pp. 215- 224 ,(1995) , 10.1007/BF02656834
Chʿeng-lan Pao, Synoptic meteorology in China China Ocean Press , Springer-Verlag. ,(1987)
Guo Yufu, Zhao Yan, Wang Jia, Numerical simulation of the relationships between the 1998 yangtze river valley floods and SST anomalies Advances in Atmospheric Sciences. ,vol. 19, pp. 391- 404 ,(2002) , 10.1007/S00376-002-0074-0
C. Venkatesan, S. D. Raskar, S. S. Tambe, B. D. Kulkarni, R. N. Keshavamurty, Prediction of all India summer monsoon rainfall using error-back-propagation neural networks Meteorology and Atmospheric Physics. ,vol. 62, pp. 225- 240 ,(1997) , 10.1007/BF01029704
A. K. Sahai, D. R. Pattanaik, V. Satyan, Alice M. Grimm, Teleconnections in recent time and prediction of Indian summer monsoon rainfall Meteorology and Atmospheric Physics. ,vol. 84, pp. 217- 227 ,(2003) , 10.1007/S00703-002-0595-1
S. Becker, H. Hartmann, Q. Zhang, Y. Wu, T. Jiang, Cyclicity analysis of precipitation regimes in the Yangtze River basin, China International Journal of Climatology. ,vol. 28, pp. 579- 588 ,(2008) , 10.1002/JOC.1572
Y. F. Qian, Y. Q. Zheng, Y. Zhang, M. Q. Miao, Responses of China's summer monsoon climate to snow anomaly over the Tibetan plateau International Journal of Climatology. ,vol. 23, pp. 593- 613 ,(2003) , 10.1002/JOC.901
Anthony G. Barnston, Robert E. Livezey, Classification, seasonality and persistence of low-frequency atmospheric circulation patterns Monthly Weather Review. ,vol. 115, pp. 1083- 1126 ,(1987) , 10.1175/1520-0493(1987)115<1083:CSAPOL>2.0.CO;2
P. Guhathakurta, M. Rajeevan, V. Thapliyal, Long Range Forecasting Indian Summer Monsoon Rainfallby a Hybrid Principal Component Neural Network Model Meteorology and Atmospheric Physics. ,vol. 71, pp. 255- 266 ,(1999) , 10.1007/S007030050059
Robert Kistler, William Collins, Suranjana Saha, Glenn White, John Woollen, Eugenia Kalnay, Muthuvel Chelliah, Wesley Ebisuzaki, Masao Kanamitsu, Vernon Kousky, Huug van den Dool, Roy Jenne, Michael Fiorino, The NCEP–NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation Bulletin of the American Meteorological Society. ,vol. 82, pp. 247- 267 ,(2001) , 10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2