Nonglobal Parameter Estimation Using Local Ensemble Kalman Filtering

Thomas Bellsky School of Mathematics and Statistical Sciences, Arizona State University, Tempe, Arizona

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Jesse Berwald Institute for Mathematics and Its Applications, University of Minnesota, Minneapolis, Minnesota

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Lewis Mitchell Department of Mathematics and Statistics, University of Vermont, Burlington, Vermont

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Abstract

The authors study parameter estimation for nonglobal parameters in a low-dimensional chaotic model using the local ensemble transform Kalman filter (LETKF). By modifying existing techniques for using observational data to estimate global parameters, they present a methodology whereby spatially varying parameters can be estimated using observations only within a localized region of space. Taking a low-dimensional nonlinear chaotic conceptual model for atmospheric dynamics as a numerical test bed, the authors show that this parameter estimation methodology accurately estimates parameters that vary in both space and time, as well as parameters representing physics absent from the model.

Corresponding author address: Thomas Bellsky, School of Mathematics and Statistical Sciences, Arizona State University, Physical Sciences, A-Wing, P.O. Box 871804, Tempe, AZ 85287-1804. E-mail: bellskyt@asu.edu

Abstract

The authors study parameter estimation for nonglobal parameters in a low-dimensional chaotic model using the local ensemble transform Kalman filter (LETKF). By modifying existing techniques for using observational data to estimate global parameters, they present a methodology whereby spatially varying parameters can be estimated using observations only within a localized region of space. Taking a low-dimensional nonlinear chaotic conceptual model for atmospheric dynamics as a numerical test bed, the authors show that this parameter estimation methodology accurately estimates parameters that vary in both space and time, as well as parameters representing physics absent from the model.

Corresponding author address: Thomas Bellsky, School of Mathematics and Statistical Sciences, Arizona State University, Physical Sciences, A-Wing, P.O. Box 871804, Tempe, AZ 85287-1804. E-mail: bellskyt@asu.edu
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