DOI: 10.1002/2016MS000838
Scopus记录号: 2-s2.0-85011298959
论文题名: A new method for determining the optimal lagged ensemble
作者: Trenary L ; , DelSole T ; , Tippett M ; K ; , Pegion K
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2017
卷: 9, 期: 1 起始页码: 291
结束页码: 306
语种: 英语
英文关键词: Climatology
; Covariance matrix
; Errors
; Parameterization
; Analytic functions
; CFSv2
; Climate forecasts
; Ensemble members
; Error covariance matrix
; General methodologies
; Madden-Julian oscillation
; Methodology
; Forecasting
; climate modeling
; data set
; ensemble forecasting
; Madden-Julian oscillation
; methodology
; numerical method
; weather forecasting
英文摘要: We propose a general methodology for determining the lagged ensemble that minimizes the mean square forecast error. The MSE of a lagged ensemble is shown to depend only on a quantity called the cross-lead error covariance matrix, which can be estimated from a short hindcast data set and parameterized in terms of analytic functions of time. The resulting parameterization allows the skill of forecasts to be evaluated for an arbitrary ensemble size and initialization frequency. Remarkably, the parameterization also can estimate the MSE of a burst ensemble simply by taking the limit of an infinitely small interval between initialization times. This methodology is applied to forecasts of the Madden Julian Oscillation (MJO) from version 2 of the Climate Forecast System version 2 (CFSv2). For leads greater than a week, little improvement is found in the MJO forecast skill when ensembles larger than 5 days are used or initializations greater than 4 times per day. We find that if the initialization frequency is too infrequent, important structures of the lagged error covariance matrix are lost. Lastly, we demonstrate that the forecast error at leads ≥10 days can be reduced by optimally weighting the lagged ensemble members. The weights are shown to depend only on the cross-lead error covariance matrix. While the methodology developed here is applied to CFSv2, the technique can be easily adapted to other forecast systems. © 2017. The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75824
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: George Mason University, Fairfax, VA, United States; Center of Ocean-Land-Atmosphere Studies, Fairfax, VA, United States; Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, United States; Department of Meteorology, Center of Excellence for Climate Change Research, King Abdulaziz University, Jeddah, Saudi Arabia
Recommended Citation:
Trenary L,, DelSole T,, Tippett M,et al. A new method for determining the optimal lagged ensemble[J]. Journal of Advances in Modeling Earth Systems,2017-01-01,9(1)