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• W2804452562 abstract "Artificial ensemble inflation is a common technique in ensemble data assimilation, whereby the ensemble covariance is periodically increased in order to prevent deviation of the ensemble from the observations and possible ensemble collapse. This manuscript introduces a new form of covariance inflation for ensemble data assimilation based upon shadowing ideas from dynamical systems theory. We present results from a low order nonlinear chaotic system that supports using shadowing inflation, demonstrating that shadowing inflation is more robust to parameter tuning than standard multiplicative covariance inflation, outperforming in observation-sparse scenarios and often leading to longer forecast shadowing times." @default.
• W2804452562 created "2018-06-01" @default.
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• W2804452562 date "2018-10-01" @default.
• W2804452562 modified "2023-10-15" @default.
• W2804452562 title "A shadowing-based inflation scheme for ensemble data assimilation" @default.
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• W2804452562 doi "https://doi.org/10.1016/j.physd.2018.05.002" @default.
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