Ensemble Data Assimilation without Perturbed Observations

@inproceedings{Whitaker2002EnsembleDA,
  title={Ensemble Data Assimilation without Perturbed Observations},
  author={Jeffrey S. Whitaker and Thomas M. Hamill},
  year={2002}
}
The ensemble Kalman filter (EnKF) is a data assimilation scheme based on the traditional Kalman filter update equation. An ensemble of forecasts are used to estimate the background-error covariances needed to compute the Kalman gain. It is known that if the same observations and the same gain are used to update each member of the ensemble, the ensemble will systematically underestimate analysis-error covariances. This will cause a degradation of subsequent analyses and may lead to filter… CONTINUE READING
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