DOI: 10.1175/JCLI-D-14-00302.1
Scopus记录号: 2-s2.0-84961287957
论文题名: ENSO Prediction in Project Minerva: Sensitivity to atmospheric horizontal resolution and ensemble size
作者: Zhu J. ; Huang B. ; Cash B. ; Kinter J.L. ; Manganello J. ; Barimalala R. ; Altshuler E. ; Vitart F. ; Molteni F. ; Towers P.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2015
卷: 28, 期: 5 起始页码: 2080
结束页码: 2095
语种: 英语
Scopus关键词: Atmospheric pressure
; Atmospheric thermodynamics
; Climate change
; Climate models
; Climatology
; Forecasting
; Mean square error
; Oceanography
; Probability distributions
; Anomaly correlations
; Atmosphere-ocean interactions
; Center for ocean-land-atmosphere studies
; ENSO
; European centre for medium-range weather forecasts
; Horizontal resolution
; Root mean square errors
; Seasonal forecasting
; Weather forecasting
; air-sea interaction
; climate modeling
; climate prediction
; El Nino-Southern Oscillation
; ensemble forecasting
; weather forecasting
英文摘要: This study examines El Niño-Southern Oscillation (ENSO) prediction in Project Minerva, a recent collaboration between the Center for Ocean-Land-Atmosphere Studies (COLA) and the European Centre for Medium-Range Weather Forecasts (ECMWF). The focus is primarily on the impact of the atmospheric horizontal resolution on ENSO prediction, but the effect from different ensemble sizes is also discussed. Particularly, three sets of 7-month hindcasts performed with ECMWF prediction system are compared, starting from 1 May (1 November) during 1982-2011 (1982-2010): spectral T319 atmospheric resolution with 15 ensembles, spectral T639 with 15 ensembles, and spectral T319 with 51 ensembles. The analysis herein shows that simply increasing either ensemble size from 15 to 51 or atmospheric horizontal resolution from T319 to T639 does not necessarily lead to major improvement in the ENSO prediction skill with current climate models. For deterministic prediction skill metrics, the three sets of predictions do not produce a significant difference in either anomaly correlation or root-mean-square error (RMSE). For probabilistic metrics, the increased atmospheric horizontal resolution generates larger ensemble spread, and thus increases the ratio between the intraensemble spread and RMSE. However, there is little change in the categorical distributions of predicted SST anomalies, and consequently there is little difference among the three sets of hindcasts in terms of probabilistic metrics or prediction reliability. © 2015 American Meteorological Society. 资助项目: NSF, National Science Foundation
; NOAA, National Science Foundation
; NASA, National Science Foundation
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50663
Appears in Collections: 气候变化事实与影响
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作者单位: Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, VA, United States; Center for Ocean-Land-Atmosphere Studies, Department of Atmospheric, Oceanic, and Earth Sciences, College of Science, George Mason University, Fairfax, VA, United States; European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
Recommended Citation:
Zhu J.,Huang B.,Cash B.,et al. ENSO Prediction in Project Minerva: Sensitivity to atmospheric horizontal resolution and ensemble size[J]. Journal of Climate,2015-01-01,28(5)