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contributor authorYaremchuk, Max
contributor authorNechaev, Dmitri
contributor authorPan, Chudong
date accessioned2017-06-09T16:41:00Z
date available2017-06-09T16:41:00Z
date copyright2011/06/01
date issued2011
identifier issn0027-0644
identifier otherams-72152.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4214124
description abstracthybrid background error covariance (BEC) model for three-dimensional variational data assimilation of glider data into the Navy Coastal Ocean Model (NCOM) is introduced. Similar to existing atmospheric hybrid BEC models, the proposed model combines low-rank ensemble covariances with the heuristic Gaussian-shaped covariances to estimate forecast error statistics. The distinctive features of the proposed BEC model are the following: (i) formulation in terms of inverse error covariances, (ii) adaptive determination of the rank m of with information criterion based on the innovation error statistics, (iii) restriction of the heuristic covariance operator to the null space of , and (iv) definition of the BEC magnitudes through separate analyses of the innovation error statistics in the state space and the null space of .The BEC model is validated by assimilation experiments with simulated and real data obtained during a glider survey of the Monterey Bay in August 2003. It is shown that the proposed hybrid scheme substantially improves the forecast skill of the heuristic covariance model.
publisherAmerican Meteorological Society
titleA Hybrid Background Error Covariance Model for Assimilating Glider Data into a Coastal Ocean Model
typeJournal Paper
journal volume139
journal issue6
journal titleMonthly Weather Review
identifier doi10.1175/2011MWR3510.1
journal fristpage1879
journal lastpage1890
treeMonthly Weather Review:;2011:;volume( 139 ):;issue: 006
contenttypeFulltext


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