Articles | Volume 16, issue 14
https://doi.org/10.5194/gmd-16-4233-2023
https://doi.org/10.5194/gmd-16-4233-2023
Development and technical paper
 | 
27 Jul 2023
Development and technical paper |  | 27 Jul 2023

Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses

Bo Dong, Ross Bannister, Yumeng Chen, Alison Fowler, and Keith Haines

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Cited articles

Balmaseda, M. A., Mogensen, K., and Weaver, A. T.: Evaluation of the ECMWF ocean reanalysis system ORAS4, Q. J. Roy. Meteor. Soc., 139, 1132–1161, 2013. a
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive Sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical Aspects, Mon. Weather Rev., 129, 420–436, https://doi.org/10.1175/1520-0493(2001)129<0420:ASWTET>2.0.CO;2, 2001. a, b
Bocquet, M. and Sakov, P.: An iterative ensemble Kalman smoother, Q. J. Roy. Meteor. Soc., 140, 1521–1535, https://doi.org/10.1002/qj.2236, 2014. a, b
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Short summary
Traditional Kalman smoothers are expensive to apply in large global ocean operational forecast and reanalysis systems. We develop a cost-efficient method to overcome the technical constraints and to improve the performance of existing reanalysis products.
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