気象集誌. 第2輯
Online ISSN : 2186-9057
Print ISSN : 0026-1165
ISSN-L : 0026-1165

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Tailored Ensemble Prediction Systems: Application of Seamless Scale Bred Vectors
HERMOSO AlejandroHOMAR VictorGREYBUSH Steven J.STENSRUD David J.
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ジャーナル オープンアクセス 早期公開

論文ID: 2020-053

この記事には本公開記事があります。
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 Uncertainty in numerical weather forecasts arising from an imperfect knowledge of the initial condition of the atmospheric system and the discrete modelling of physical processes is addressed with ensemble prediction systems. The breeding method allows the creation of initial condition perturbations in a simple and computationally inexpensive way. This technique uses the full nonlinear dynamics of the system to identify fast-growing modes in the analysis fields, obtained from the difference between control and perturbed runs rescaled at regular time intervals. This procedure is more suitable for the high resolution ensemble forecasts required to reproduce small scale high impact weather events, as the complete nonlinear model is applied to generate the perturbations. The underdispersion commonly found in ensemble forecasts emphasizes the need to develop methods that increase ensemble spread and diversity at no cost to forecast skill. In this sense, we investigate the benefits of different breeding techniques in terms of ensemble diversity and forecast skill for a mesoscale ensemble over the Western Mediterranean region. In addition, we propose a new method, Bred Vectors Tailored Ensemble Perturbations designed to control the scale of the perturbations and indirectly the ensemble spread. The combination of this method with orthogonal bred vectors shows significant improvements in terms of ensemble diversity and forecast skill with respect to the current arithmetic methods.

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© The Author(s) 2020. This is an open access article published by the Meteorological Society of Japan under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
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