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Ensemble Kalman Filter Analyses of the . . .
, 2011
"... The performance of ensemble Kalman filter (EnKF) analysis is investigated for the ..."
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The performance of ensemble Kalman filter (EnKF) analysis is investigated for the
Data Assimilation Using an Ensemble Kalman Filter Technique
, 1998
"... The possibility of performing data assimilation using the flowdependent statistics calculated from an ensemble of shortrange forecasts (a technique referred to as ensemble Kalman filtering) is examined in an idealized environment. Using a threelevel, quasigeostrophic, T21 model and simulated ob ..."
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Cited by 411 (5 self)
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The possibility of performing data assimilation using the flowdependent statistics calculated from an ensemble of shortrange forecasts (a technique referred to as ensemble Kalman filtering) is examined in an idealized environment. Using a threelevel, quasigeostrophic, T21 model and simulated
An Adaptive Ensemble Kalman Filter
, 2000
"... To the extent that model error is nonnegligible in numerical models of the atmosphere, it must be accounted for in 4D atmospheric data assimilation systems. In this study, a method of estimating and accounting for model error in the context of an ensemble Kalman filter technique is developed. The ..."
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Cited by 53 (0 self)
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To the extent that model error is nonnegligible in numerical models of the atmosphere, it must be accounted for in 4D atmospheric data assimilation systems. In this study, a method of estimating and accounting for model error in the context of an ensemble Kalman filter technique is developed
Analysis Scheme in the Ensemble Kalman Filter
, 1998
"... This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter. It is shown that the observations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct st ..."
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Cited by 141 (1 self)
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This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter. It is shown that the observations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct
Resampling the Ensemble Kalman Filter
"... Ensemble Kalman filters (EnKF) based on a small ensemble tend to provide collapse of the ensemble over time. It is demonstrated that this collapse is caused by positive coupling of the ensemble members due to use of the estimated Kalman gain for the update of all ensemble members at each time step. ..."
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Ensemble Kalman filters (EnKF) based on a small ensemble tend to provide collapse of the ensemble over time. It is demonstrated that this collapse is caused by positive coupling of the ensemble members due to use of the estimated Kalman gain for the update of all ensemble members at each time step
Cluster ensemble Kalman filter
 Tellus
"... A modified ensemble Kalman filter (KF) is proposed which can enhance performance for highly nonlinear prognostic models. The algorithm differs from the traditional ensemble KF by the addition of an expectation maximization step, which estimates the parameters of a Gaussian mixture model for the ens ..."
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Cited by 4 (0 self)
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A modified ensemble Kalman filter (KF) is proposed which can enhance performance for highly nonlinear prognostic models. The algorithm differs from the traditional ensemble KF by the addition of an expectation maximization step, which estimates the parameters of a Gaussian mixture model
Resampling the Ensemble Kalman Filter
"... Ensemble Kalman filters (EnKF) based on a small ensemble tend to provide collapse of the ensemble over time. It is shown that this collapse is caused by positive coupling of the ensemble members due to use of one common estimate of the Kalman gain for the update of all ensemble members at each time ..."
Abstract
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Ensemble Kalman filters (EnKF) based on a small ensemble tend to provide collapse of the ensemble over time. It is shown that this collapse is caused by positive coupling of the ensemble members due to use of one common estimate of the Kalman gain for the update of all ensemble members at each
On the Convergence of the Ensemble Kalman Filter
, 2009
"... Convergence of the ensemble Kalman filter in the limit for large ensembles to the Kalman filter is proved. In each step of the filter, convergence of the ensemble sample covariance follows from a weak law of large numbers for exchangeable random variables, Slutsky’s theorem gives weak convergence of ..."
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Cited by 13 (5 self)
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Convergence of the ensemble Kalman filter in the limit for large ensembles to the Kalman filter is proved. In each step of the filter, convergence of the ensemble sample covariance follows from a weak law of large numbers for exchangeable random variables, Slutsky’s theorem gives weak convergence
ON THE CONVERGENCE OF THE ENSEMBLE KALMAN FILTER
"... Abstract. Convergence of the ensemble Kalman filter in the limit for large ensembles to the Kalman filter is proved. In each step of the filter, convergence of the ensemble sample covariance follows from a weak law of large numbers for exchangeable random variables, Slutsky’s theorem gives weak conv ..."
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Abstract. Convergence of the ensemble Kalman filter in the limit for large ensembles to the Kalman filter is proved. In each step of the filter, convergence of the ensemble sample covariance follows from a weak law of large numbers for exchangeable random variables, Slutsky’s theorem gives weak
Morphing ensemble kalman filters
 Tellus 60A (2007) 131
"... A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF) with the ideas of morphing and registration from image processing. This results in filters suitable for nonlinear problems whose solutions exhibit moving coherent features, such as thin interfaces in wildfire ..."
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Cited by 17 (6 self)
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A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF) with the ideas of morphing and registration from image processing. This results in filters suitable for nonlinear problems whose solutions exhibit moving coherent features, such as thin interfaces in wildfire
Results 1  10
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