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- Philip A. Browne
- European Centre for Medium-Range Weather Forecasts (ECMWF), Shinfield Road, Reading RG2 9AX, UK
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- Patricia de Rosnay
- European Centre for Medium-Range Weather Forecasts (ECMWF), Shinfield Road, Reading RG2 9AX, UK
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- Hao Zuo
- European Centre for Medium-Range Weather Forecasts (ECMWF), Shinfield Road, Reading RG2 9AX, UK
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- Andrew Bennett
- European Centre for Medium-Range Weather Forecasts (ECMWF), Shinfield Road, Reading RG2 9AX, UK
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- Andrew Dawson
- European Centre for Medium-Range Weather Forecasts (ECMWF), Shinfield Road, Reading RG2 9AX, UK
書誌事項
- 公開日
- 2019-01-23
- 権利情報
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- https://creativecommons.org/licenses/by/4.0/
- DOI
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- 10.3390/rs11030234
- 公開者
- MDPI AG
説明
<jats:p>Numerical weather prediction models are including an increasing number of components of the Earth system. In particular, every forecast now issued by the European Centre for Medium-Range Weather Forecasts (ECMWF) runs with a 3D ocean model and a sea ice model below the atmosphere. Initialisation of different components using different methods and on different timescales can lead to inconsistencies when they are combined in the full system. Historically, the methods for initialising the ocean and the atmosphere have been typically developed separately. This paper describes an approach for combining the existing ocean and atmospheric analyses into what we categorise as a weakly coupled assimilation scheme. Here, we show the performance improvements achieved for the atmosphere by having a weakly coupled ocean–atmosphere assimilation system compared with an uncoupled system. Using numerical weather prediction diagnostics, we show that forecast errors are decreased compared with forecasts initialised from an uncoupled analysis. Further, a detailed investigation into spatial coverage of sea ice concentration in the Baltic Sea shows that a much more realistic structure is obtained by the weakly coupled analysis. By introducing the weakly coupled ocean–atmosphere analysis, the ocean analysis becomes a critical part of the numerical weather prediction system and provides a platform from which to build ever stronger forms of analysis coupling.</jats:p>
収録刊行物
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- Remote Sensing
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Remote Sensing 11 (3), 234-, 2019-01-23
MDPI AG