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Forecasting near-surface ocean winds with Kalman filter techniques

In English

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.

Publiceringsår

2005

Språk

Engelska

Sidor

273-291

Publikation/Tidskrift/Serie

Ocean Engineering

Volym

32

Issue

3-4

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