DOI: 10.1002/2015GL063930
论文题名: Real-time estimation of Arctic sea ice thickness through maximum covariance analysis
作者: Dirkson A. ; Merryfield W.J. ; Monahan A.
刊名: Geophysical Research Letters
ISSN: 0094-8665
EISSN: 1944-8396
出版年: 2015
卷: 42, 期: 12 起始页码: 4869
结束页码: 4877
语种: 英语
Scopus关键词: Climatology
; Sea ice
; Sea level
; Assimilation system
; Inter-annual predictions
; Maximum covariance analysis
; Mean absolute error
; Real-time estimation
; Sea ice concentration
; Seasonal prediction
; Statistical modeling
; Ice
; covariance analysis
; estimation method
; ice thickness
; prediction
; real time
; sea ice
; sea level pressure
; seasonality
; Arctic Ocean
英文摘要: A challenge for model-based seasonal predictions of sea ice is an accurate representation of sea ice initial conditions, particularly sparsely observed sea ice thickness (SIT). The Canadian Seasonal to Interannual Prediction System (CanSIPS) currently initializes SIT by nudging simulated values toward a model-based climatology. To improve on this, we use sea ice data from Pan-Arctic Ice Ocean Modeling and Assimilation System to investigate how accurately SIT can be estimated in real time using better observed and physically relevant predictors. We (1) test the skill of several predictors using maximum covariance analysis (MCA), (2) apply an approach which blends sea ice concentration and lagged (4 month averaged) sea level pressure, and (3) compare this method against the current CanSIPS initialization scheme over 1981-2012. The MCA-based statistical model reduces SIT areal mean and temporal mean absolute errors by 48% relative to the current CanSIPS initialization and shows consistent skill estimating ice volume in all months (r = 0.95). © 2015. American Geophysical Union. All Rights Reserved. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84948720828&doi=10.1002%2f2015GL063930&partnerID=40&md5=26c6c33d35941dd3eef8462fcf3f7220
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/8281
Appears in Collections: 科学计划与规划 气候变化与战略
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作者单位: School of Earth and Ocean Sciences, University of Victoria, Victoria, BC, Canada
Recommended Citation:
Dirkson A.,Merryfield W.J.,Monahan A.. Real-time estimation of Arctic sea ice thickness through maximum covariance analysis[J]. Geophysical Research Letters,2015-01-01,42(12).