EnKF
EnKF-The Ensemble Kalman Filter The EnKF is a sophisticated sequental data assimilation method. It applies an ensemble of model states to represent the error statistics of the model estimate, it applies ensemble integrations to predict the error statistics forward in time, and it uses an analysis scheme which operates directly on the ensemble of model states when observations are assimilated. The EnKF has proven to efficiently handle strongly nonlinear dynamics and large state spaces and is now used in realistic applications with primitive equation models for the ocean and atmosphere. A recent article in the Siam News Oct. 2003 by Dana McKenzie suggests that the killer heat wave that hit Central Europe in the summer 2003 could have been more efficiently forecast if the EnKF had been used by Meteorological Centers. See the article ”Ensemble Kalman Filters Bring Weather Models Up to Date” on http://www.siam.org/siamnews/10-03/tococt03.htm This page is established as a reference page for users of the EnKF, and it contains documentation, example codes, and standardized Fortran 90 subroutines which can be used in new implementations of the EnKF. The material on this page will provide new users of the EnKF with a quick start and spinup, and experienced users with optimized code which may increase the performence of their implementations.
Keywords for this software
References in zbMATH (referenced in 156 articles , 1 standard article )
Showing results 1 to 20 of 156.
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- Iglesias, Marco A.: A regularizing iterative ensemble Kalman method for PDE-constrained inverse problems (2016)
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- Tong, Xin T.; Majda, Andrew J.; Kelly, David: Nonlinear stability of the ensemble Kalman filter with adaptive covariance inflation (2016)
- van Essen, G.M.; Kahrobaei, S.; van Oeveren, H.; Van den Hof, P.M.J.; Jansen, J.D.: Determination of lower and upper bounds of predicted production from history-matched models (2016)
- Butler, T.; Huhtala, A.; Juntunen, M.: Quantifying uncertainty in material damage from vibrational data (2015)
- C^ındea, Nicolae; Imperiale, Alexandre; Moireau, Philippe: Data assimilation of time under-sampled measurements using observers, the wave-like equation example (2015)
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- Iglesias, Marco A.: Iterative regularization for ensemble data assimilation in reservoir models (2015)
- Manoli, Gabriele; Rossi, Matteo; Pasetto, Damiano; Deiana, Rita; Ferraris, Stefano; Cassiani, Giorgio; Putti, Mario: An iterative particle filter approach for coupled hydro-geophysical inversion of a controlled infiltration experiment (2015)