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gmd-16-4233-2023.pdf
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Summary

A simplified Kalman smoother and ensemble Kalman smoother are developed for improving reanalyses, which can be run as a post-processing step using minimal stored information from a Kalman filter analysis. The method applies a simple decay assumption to cross-time error covariances and is demonstrated in the Lorenz idealized system, achieving up to 70% of the full smoother error reduction with respect to the extended filter and 40% with respect to the ensemble filter. The uncertainties derived for the new smoother agree well with the actual root mean square error values, making it a useful tool for large model reanalysis products, especially ensemble products.

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Description

A simplified Kalman smoother and ensemble Kalman smoother are developed for improving reanalyses, which can be run as a post-processing step using minimal...

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  • File Format: PDF
  • File Size: 4.24 MB
  • Pages: 15
  • Language: EN
  • Total Downloads: 184
  • Last Updated: 2 hours ago

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