Localization and the iterative ensemble Kalman smoother

@inproceedings{Bocquet2016LocalizationAT,
  title={Localization and the iterative ensemble Kalman smoother},
  author={Marc Bocquet},
  year={2016}
}
The iterative ensemble Kalman smoother (IEnKS) is a data assimilation method meant for tracking the state of nonlinear geophysical models efficiently. It combines an ensemble of model states to estimate the errors similarly to the ensemble square-root Kalman filter, with a four-dimensional variational analysis performed within the ensemble space. As such, it belongs to the class of four-dimensional ensemble variational methods. It could require the use of localization of the analysis when the… CONTINUE READING

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