DOI: 10.1007/s00382-013-1908-4
Scopus记录号: 2-s2.0-84901987253
论文题名: Hydro-climatic forecasting using sea surface temperatures: Methodology and application for the southeast US
作者: Chen C.-J. ; Georgakakos A.P.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2014
卷: 42, 期: 2017-11-12 起始页码: 2955
结束页码: 2982
语种: 英语
英文关键词: Seasonal forecasting
; Southeast US climate
; Teleconnections
; Water resources planning
英文摘要: Sea surface temperatures (SSTs) are often used for the development of hydro-climatic variable forecasts based on teleconnection methods. Such methods rely on projections or linear combinations of teleconnection indices [e.g. El Niño-Southern Oscillation (ENSO)] and other predictor fields. This study introduces a new hydro-climatic forecasting method identifying SST "dipole" predictors motivated by major teleconnection patterns. An SST dipole is defined as a function of average SST anomalies over two oceanic areas of specific sizes and geographic locations. An optimization algorithm is developed to search for the most significant SST dipole predictors of an external hydro-climatic series based on the Gerrity Skill Score. The significant dipoles are cross-validated and used to generate multiple forecast values. The new method is applied to the forecasting of seasonal precipitation over the southeast US. Hindcasting results show that significant dipoles related to ENSO as well as other prominent patterns at different lead times can indeed be identified. The dipole method also compares favorably with existing statistical forecasting schemes with respect to multiple skill measures. Furthermore, an operational forecasting framework able to produce ensemble forecast traces and uncertainty intervals that can support regional water resources planning and management is also developed. © 2013 Springer-Verlag Berlin Heidelberg.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/54664
Appears in Collections: 过去全球变化的重建
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作者单位: School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Drive, Atlanta, GA, 30332-0355, United States
Recommended Citation:
Chen C.-J.,Georgakakos A.P.. Hydro-climatic forecasting using sea surface temperatures: Methodology and application for the southeast US[J]. Climate Dynamics,2014-01-01,42(2017-11-12)