| G. Evensen. Inverse methods and data assimilation in nonlinear ocean models. Physica D, 77:108--129. |
....of the forecast distribution. Next we present a sample based forecasting and assimilation scheme utilizing the KF mean update equation. 4 2. 3 Ensemble Kalman Filter A forecasting and data assimilation algorithm recently advanced in the atmospheric sciences is the ensemble Kalman filter (EnsKF) [8] [12] The EnsKF is a Monte Carlo based approach to forecasting and data assimilation. Along with its real time e#ciency, it is employed in the atmospheric sciences for its relative ease of implementation in high dimensional systems. The method has also been shown to perform well in low order ....
G. Evensen. Inverse methods and data assimilation in nonlinear ocean models. Physica D, 77:108--129.
.... This requires the forward integration of an error covariance equation for the error statistics, e.g. by using an Extended Kalman Filter (EKF) 6,7] or, as a better alternative, one can integrate an ensemble of ocean states as is done in the recently proposed Ensemble Kalman Filter (EnKF) [8,9,12]. The recent developments related to so called advanced methods like the EnKF, and the significant improvement of available computer resources, now suggest that such advanced methods should be implemented also with OGCMs. These methodologies have proven very successful when used with less ....
G. Evensen, Inverse methods and data assimilation in nonlinear ocean models, Physica D, 77, 108--129, 1994.
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Evensen, G., 1994a: Inverse methods and data assimilation in nonlinear ocean models, Physica D, 77, 108--129.
No context found.
Evensen, G., Inverse methods and data assimilation in nonlinear ocean models, Physica D, 77, 108--129, 1994a.
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