DOI: 10.1175/JCLI-D-11-00110.1
Scopus记录号: 2-s2.0-84858599251
论文题名: Quantifying the predictive skill in long-range forecasting. Part II: Model error in coarse-grained Markov models with application to ocean-circulation regimes
作者: Giannakis D. ; Majda A.J.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2012
卷: 25, 期: 6 起始页码: 1814
结束页码: 1826
语种: 英语
Scopus关键词: Ensembles
; Model errors
; Ocean model
; Probability forecasts/models/distribution
; Statistical forecasting
; Classification (of information)
; Climatology
; Forecasting
; Markov processes
; Climate models
; climate classification
; climate modeling
; climate prediction
; ensemble forecasting
; error analysis
; long range forecast
; Markov chain
; numerical model
; oceanic circulation
; probability
英文摘要: Aninformation-theoretic framework is developed to assess the predictive skill and model error in imperfect climate models for long-range forecasting. Here, of key importance is a climate equilibrium consistency test for detecting false predictive skill, as well as an analogous criterion describing model error during relaxation to equilibrium. Climate equilibrium consistency enforces the requirement that long-range forecasting models should reproduce the climatology of prediction observables with high fidelity. If a model meets both climate consistency and the analogous criterion describing model error during relaxation to equilibrium, then relative entropy can be used as an unbiased superensemble measure of the model's skill in long-range coarse-grained forecasts. As an application, the authors investigate the error in modeling regime transitions in a 1.5-layer ocean model as a Markov process and identify models that are strongly persistent but their predictive skill is false. The general techniques developed here are also useful for estimating predictive skill with model error for Markov models of low-frequency atmospheric regimes. © 2012 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/52518
Appears in Collections: 气候变化事实与影响
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作者单位: Courant Institute of Mathematical Sciences, New York University, New York, NY, United States
Recommended Citation:
Giannakis D.,Majda A.J.. Quantifying the predictive skill in long-range forecasting. Part II: Model error in coarse-grained Markov models with application to ocean-circulation regimes[J]. Journal of Climate,2012-01-01,25(6)