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A real-time assimilation algorithm applied to near-surface ocean winds

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Author

Summary, in English

Marine operations depend on the ability to forecast suddenly appearing storms and failures often cause great damage. As a part of a sea state alarm study, meteorological forecasts overlaid with satellite measurements sent to ships have been found to be a useful tool. In this paper we present a real-time assimilation algorithm that extends this tool using statistical methods. The algorithm is applied to near-surface ocean zonal wind speeds.

The meteorological model is emulated using a Kalman filter technique. Together with a spatio-temporal state-space model the filter allows us to obtain forecasts which are overlaid with satellite measurements using a kriging method. Examples of overlays together with their statistical uncertainties are presented and discussed.

Publishing year

2004

Language

English

Publication/Series

Preprint without journal information

Issue

2004:34

Document type

Journal article

Publisher

Manne Siegbahn Institute

Topic

  • Probability Theory and Statistics

Status

Unpublished

ISBN/ISSN/Other

  • ISSN: 0348-7911