Forecasting near-surface ocean winds with Kalman filter techniques
Författare
Summary, in English
In this paper a statistical forecasting model designed for bounded areas of near-surface ocean wind speeds is implemented. Dimension reduction is achieved by decomposing the covariance structure into one large-scale and one small-scale component using empirical orthogonal functions. The large-scale component is modelled with an AR process and forecasts are calculated by applying a Kalman filter. The model is suited for stable weather situations as for unsteady situations it requires more frequent wind information. From the prediction variance fields it is possible to identify where unexpected weather usually enters the area.
Avdelning/ar
Publiceringsår
2005
Språk
Engelska
Sidor
273-291
Publikation/Tidskrift/Serie
Ocean Engineering
Volym
32
Issue
3-4
Länkar
Dokumenttyp
Artikel i tidskrift
Förlag
Elsevier
Ämne
- Probability Theory and Statistics
Nyckelord
- near-surface
- ocean winds
- forecasting
- filtering
- space-time Kalman
- dimension reduction
- principal components
Status
Published
ISBN/ISSN/Övrigt
- ISSN: 1873-5258