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• W82080766 abstract "This article introduces the algorithm of ensemble-based data assimilation (EDA) and the main issues in its application to atmospheric sciences. EDA is drawing increasing attentions in data assimilation community mainly due to its flow-dependent background error covariance determined using a short-range ensemble forecast and ease of implementation. Many types of EDA have been applied with different models at different scales in both research and operational or quasi-operational communities. Various aspects involved in EDA are discussed including observations, ensemble initialization, sampling error, covariance inflation and localization, model error, verification, nonlinearity and non-Gaussian errors, intercomparison, and hybrid with variational schemes." @default.
• W82080766 created "2016-06-24" @default.
• W82080766 creator A5034851045 @default.
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• W82080766 date "2015-01-01" @default.
• W82080766 modified "2023-10-16" @default.
• W82080766 title "DATA ASSIMILATION AND PREDICTABILITY | Ensemble-Based Data Assimilation" @default.
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• W82080766 doi "https://doi.org/10.1016/b978-0-12-382225-3.00495-3" @default.
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