| DOI: | 10.1175/JCLI-D-17-0233.1
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| Scopus记录号: | 2-s2.0-85040548511
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| 论文题名: | Interannual variations and prediction of spring precipitation over China |
| 作者: | You Y.; Jia X.
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| 刊名: | Journal of Climate
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| ISSN: | 8948755
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| 出版年: | 2018
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| 卷: | 31, 期:2 | | 起始页码: | 655
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| 结束页码: | 670
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| 语种: | 英语
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| 英文关键词: | Atmosphere-ocean interaction
; Climate variability
; El Nino
; ENSO
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| Scopus关键词: | Atmospheric thermodynamics
; Climate change
; Climatology
; Coastal zones
; Forecasting
; Linear regression
; Oceanography
; Orthogonal functions
; Regression analysis
; Rivers
; Surface waters
; Water analysis
; Atmosphere-ocean interactions
; Climate variability
; EL Nino
; Empirical Orthogonal Function
; ENSO
; Linear regression models
; Observational analysis
; Time series forecasts
; Climate models
; air-sea interaction
; annual variation
; climate modeling
; climate prediction
; El Nino
; El Nino-Southern Oscillation
; empirical orthogonal function analysis
; precipitation (climatology)
; sea surface temperature
; spring (season)
; Atlantic Ocean
; Atlantic Ocean (North)
; China
; Guangdong
; Pacific Ocean
; Pacific Ocean (Tropical)
; Yangtze River
; Zhujiang Delta
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| 英文摘要: | The interannual variations and the prediction of the leading two empirical orthogonal function (EOF) modes of spring (April-May) precipitation over China for the period from 1951 to 2014 are investigated using both observational data and the seasonal forecast made by six coupled climate models. The leading EOF mode of spring precipitation over China (EOF1-prec) features a monosign pattern, with the maximum loading located over southern China. The ENSO-related tropical Pacific SST anomalies in the previous winter can serve as a precursor for EOF1-prec. The second EOF mode of spring precipitation (EOF2-prec) over China is characterized by a dipole structure, with one pole near the Yangtze River and the other one with opposite sign over the Pearl River delta. A North Atlantic sea surface temperature (SST) anomaly dipole in the preceding March is found contribute to the prec-EOF2 and can serve as its predictor. A physics-based empirical (P-E) model is then formulated using the two precursors revealed by the observational analysis to forecast the variations of EOF1-prec and EOF2-prec. Compared to coupled climate models, which have little skill in forecasting the time variations of the two EOF modes, this P-E model can significantly improve the forecast skill of their time variations. A linear regression model is further established using the time series forecast by the P-E model to forecast the spring precipitation over China. Results suggest that the seasonal forecast skill of the spring precipitation over southeastern China, especially over the Yangtze River area, can be significantly improved by the regression model. © 2018 American Meteorological Society. |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/111718
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| Appears in Collections: | 气候减缓与适应
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作者单位: | School of Earth Sciences, Zhejiang University, Hangzhou, Zhejiang, China
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| Recommended Citation: | |
You Y.,Jia X.. Interannual variations and prediction of spring precipitation over China[J]. Journal of Climate,2018-01-01,31(2)
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