A two-stage ensemble Kalman filter for smooth data assimilation |
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Authors: | Craig J Johns Jan Mandel |
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Institution: | (1) Milliman, Inc., Denver, CO, USA;(2) Department of Mathematical Sciences, University of Colorado at Denver and Health Sciences Center, Denver, CO, USA |
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Abstract: | The ensemble Kalman Filter (EnKF) applied to a simple fire propagation model by a nonlinear convection-diffusion-reaction
partial differential equation breaks down because the EnKF creates nonphysical ensemble members with large gradients. A modification
of the EnKF is proposed by adding a regularization term that penalizes large gradients. The method is implemented by applying
the EnKF formulas twice, with the regularization term as another observation. The regularization step is also interpreted
as a shrinkage of the prior distribution. Numerical results are given to illustrate success of the new method. |
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Keywords: | Data assimilation Ensemble Kalman filter State-space model Penalty Tikhonov regularization Wildfire Convection-reaction-diffusion Shrinkage Bayesian |
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