Improving the Ensemble Estimate of the Kalman Gain by Bootstrap Sampling

By Yanfen Zhang, Dean S. Oliver. 2010

61 citations recorded by the source corpus.

Subfields: Atmospheric Science, Ocean Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/f1f4e50fa47a319ea6f77ef6e5f8d6d5eb3be958

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Yan Chen
2. Dean S. Oliver
3. Jeffrey L. Anderson
4. Geir Evensen
5. Marc Bocquet
6. Pavel Sakov
7. Takemasa Miyoshi
8. Laurent Bertino

In Ocean Engineering

1. Yan Chen
2. Dean S. Oliver
3. Jeffrey L. Anderson
4. Albert C. Reynolds
5. Alexandre Anozé Emerick
6. Louis J. Durlofsky
7. Jan Dirk Jansen
8. Andrew M. Stuart

In Water Science and Technology

1. Yan Chen
2. Jeffrey L. Anderson
3. Dean S. Oliver
4. Wolfgang Nowak
5. Albert C. Reynolds
6. Dongxiao Zhang

Citations in the corpus

• Localization and Sampling Error Correction in Ensemble Kalman Filter Data Assimilation (2012, methodology): “A bootstrap method presented in Zhang and Oliver (2010) for estimating errors in ensemble covariances is also similar.”
• Ensemble Randomized Maximum Likelihood Method as an Iterative Ensemble Smoother (2011, methodology): “oil contact and the layer mean of permeability, are not localized, although the update of them could be regularized using adaptive localization methods (Anderson 2007; Zhang and Oliver 2010).”