DOI: 10.1175/JCLI-D-18-0189.1
Scopus记录号: 2-s2.0-85060976741
论文题名: Coupled data assimilation and ensemble initialization with application to multiyear ENSO prediction
作者: O'kane T.J. ; Sandery P.A. ; Monselesan D.P. ; Sakov P. ; Chamberlain M.A. ; Matear R.J. ; Collier M.A. ; Squire D.T. ; Stevens L.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2019
卷: 32, 期: 4 起始页码: 997
结束页码: 1024
语种: 英语
英文关键词: Climate prediction
; Climate variability
; Ensembles
; Kalman filters
; Lyapunov vectors
Scopus关键词: Climate models
; Climatology
; Forecasting
; Kalman filters
; Stream flow
; Surface waters
; Tropics
; Atmospheric response
; Climate prediction
; Climate variability
; Coupled general circulation models
; Ensembles
; Lyapunov vectors
; Optimal interpolation
; Sea surface temperature (SST)
; Oceanography
英文摘要: We develop and compare variants of coupled data assimilation (DA) systems based on ensemble optimal interpolation (EnOI) and ensemble transform Kalman filter (ETKF) methods. The assimilation system is first tested on a small paradigm model of the coupled tropical-extratropical climate system, then implemented for a coupled general circulation model (GCM). Strongly coupledDAwas employed specifically to assess the impact of assimilating ocean observations [sea surface temperature (SST), sea surface height (SSH), and sea surface salinity (SSS), Argo, XBT, CTD, moorings] on the atmospheric state analysis update via the crossdomain error covariances from the coupled-model background ensemble. We examine the relationship between ensemble spread, analysis increments, and forecast skill in multiyear ENSO prediction experiments with a particular focus on the atmospheric response to tropical ocean perturbations. Initial forecast perturbations generated from bred vectors (BVs) project onto disturbances at and below the thermocline with similar structures to ETKF perturbations. BV error growth leads ENSO SST phasing by 6 months whereupon the dominant mechanism communicating tropical ocean variability to the extratropical atmosphere is via tropical convection modulating the Hadley circulation. We find that bred vectors specific to tropical Pacific thermocline variability were the most effective choices for ensemble initialization and ENSO forecasting. © 2019 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117214
Appears in Collections: 气候变化与战略
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Recommended Citation:
O'kane T.J.,Sandery P.A.,Monselesan D.P.,et al. Coupled data assimilation and ensemble initialization with application to multiyear ENSO prediction[J]. Journal of Climate,2019-01-01,32(4)