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Massively Parallel Assimilation of TOGA/TAO and Topex/Poseidon Measurements into a Quasi Isopycnal Ocean General Circulation Model Using an Ensemble Kalman FilterA massively parallel ensemble Kalman filter (EnKF)is used to assimilate temperature data from the TOGA/TAO array and altimetry from TOPEX/POSEIDON into a Pacific basin version of the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. The EnKF is an approximate Kalman filter in which the error-covariance propagation step is modeled by the integration of multiple instances of a numerical model. An estimate of the true error covariances is then inferred from the distribution of the ensemble of model state vectors. This inplementation of the filter takes advantage of the inherent parallelism in the EnKF algorithm by running all the model instances concurrently. The Kalman filter update step also occurs in parallel by having each processor process the observations that occur in the region of physical space for which it is responsible. The massively parallel data assimilation system is validated by withholding some of the data and then quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The distributions of the forecast and analysis error covariances predicted by the ENKF are also examined.
Document ID
19990111519
Document Type
Conference Paper
Authors
Keppenne, Christian L. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Rienecker, Michele (NASA Goddard Space Flight Center Greenbelt, MD United States)
Borovikov, Anna Y. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Suarez, Max (NASA Goddard Space Flight Center Greenbelt, MD United States)
Date Acquired
August 19, 2013
Publication Date
January 1, 1999
Subject Category
Oceanography
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.