The Maximum Likelihood Ensemble Filter
development at the Colorado State University
Colorado State University
Abstract:
The Maximum
Likelihood Ensemble Filter (MLEF) is an ensemble filter which combines
ensemble filtering and control theory. It calculates the maximum
likelihood analysis solution (as in the variational methods), rather
than the minimum variance estimate (as in the Kalman filtering
and the ensemble Kalman filtering). The analysis error covariance,
which is used to define the initial perturbations for the ensuing
ensemble forecast, is obtained as a minimization by-product, employing
a relation between the analysis error covariance and the inverse
Hessian matrix.
The
new method is being developed with NOAA THORPEX support and will be
tested in the NCEP GFS system. Preliminary results of the MLEF will be
presented, in various applications ranging from the one-dimensional
models to the primitive equation models. Implications
of a double-resolution MLEF to a potential operational use will also be
discussed.
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