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Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data AssimilationAn attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.
Document ID
20140011836
Acquisition Source
Goddard Space Flight Center
Document Type
Preprint (Draft being sent to journal)
Authors
Keppenne, Christian L.
(Science Systems and Applications, Inc. Lanham, MD, United States)
Rienecker, Michele
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Kovach, Robin M.
(Science Systems and Applications, Inc. Lanham, MD, United States)
Vernieres, Guillaume
(Science Systems and Applications, Inc. Lanham, MD, United States)
Date Acquired
September 17, 2014
Publication Date
January 1, 2014
Subject Category
Geosciences (General)
Report/Patent Number
GSFC-E-DAA-TN11540
Funding Number(s)
CONTRACT_GRANT: NNG12HP06C
WBS: WBS 802678.02.17.01.25
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Error Covariance
Kalman Filter
Data Assimilation
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