DOI: 10.1007/s00382-017-3766-y
Scopus记录号: 2-s2.0-85025128014
论文题名: Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users
作者: Alessandri A. ; Felice M.D. ; Catalano F. ; Lee J.-Y. ; Wang B. ; Lee D.Y. ; Yoo J.-H. ; Weisheimer A.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2018
卷: 50, 期: 2018-07-08 起始页码: 2719
结束页码: 2738
语种: 英语
英文关键词: Coupled general circulationmodels
; Energy application
; Multi-model ensembles
; Seasonal climate prediction
Scopus关键词: climate prediction
; comparative study
; demand analysis
; energy budget
; ensemble forecasting
; general circulation model
; regional climate
; seasonality
; Europe
; Pacific Ocean
; Pacific Rim
英文摘要: Multi-model ensembles (MMEs) are powerful tools in dynamical climate prediction as they account for the overconfidence and the uncertainties related to single-model ensembles. Previous works suggested that the potential benefit that can be expected by using a MME amplifies with the increase of the independence of the contributing Seasonal Prediction Systems. In this work we combine the two MME Seasonal Prediction Systems (SPSs) independently developed by the European (ENSEMBLES) and by the Asian-Pacific (APCC/CliPAS) communities. To this aim, all the possible multi-model combinations obtained by putting together the 5 models from ENSEMBLES and the 11 models from APCC/CliPAS have been evaluated. The grand ENSEMBLES-APCC/CliPAS MME enhances significantly the skill in predicting 2m temperature and precipitation compared to previous estimates from the contributing MMEs. Our results show that, in general, the better combinations of SPSs are obtained by mixing ENSEMBLES and APCC/CliPAS models and that only a limited number of SPSs is required to obtain the maximum performance. The number and selection of models that perform better is usually different depending on the region/phenomenon under consideration so that all models are useful in some cases. It is shown that the incremental performance contribution tends to be higher when adding one model from ENSEMBLES to APCC/CliPAS MMEs and vice versa, confirming that the benefit of using MMEs amplifies with the increase of the independence the contributing models. To verify the above results for a real world application, the Grand ENSEMBLES-APCC/CliPAS MME is used to predict retrospective energy demand over Italy as provided by TERNA (Italian Transmission System Operator) for the period 1990–2007. The results demonstrate the useful application of MME seasonal predictions for energy demand forecasting over Italy. It is shown a significant enhancement of the potential economic value of forecasting energy demand when using the better combinations from the Grand MME by comparison to the maximum value obtained from the better combinations of each of the two contributing MMEs. The above results demonstrate for the first time the potential of the Grand MME to significantly contribute in obtaining useful predictions at the seasonal time-scale. © 2017, Springer-Verlag GmbH Germany.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/109388
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Royal Netherlands Meteorological Institute, P.O. Box 201, De Bilt, 3730 AE, Netherlands; Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile, Rome, Italy; Interdisciplinary Program of Climate Sciences and IBS Center for Climate Physics, Pusan National University, Busan, South Korea; International Pacific Research Center, Honolulu, HI, United States; Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS), Barcelona, Spain; Asian-Pacific Economic Cooperation Climate Center (APCC), Busan, South Korea; European Center For Medium Range Weather Forecasts, Shinfield, United Kingdom
Recommended Citation:
Alessandri A.,Felice M.D.,Catalano F.,et al. Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users[J]. Climate Dynamics,2018-01-01,50(2018-07-08)