![Hier klicken, um den Treffer aus der Auswahl zu entfernen](images/unchecked.gif) |
Titel |
A Kalman filter application to a spectral wave model |
VerfasserIn |
J. P. Pinto, M. C. Bernadino, A. Pires Silva |
Medientyp |
Artikel
|
Sprache |
Englisch
|
ISSN |
1023-5809
|
Digitales Dokument |
URL |
Erschienen |
In: Nonlinear Processes in Geophysics ; 12, no. 6 ; Nr. 12, no. 6 (2005-08-09), S.775-782 |
Datensatznummer |
250010885
|
Publikation (Nr.) |
copernicus.org/npg-12-775-2005.pdf |
|
|
|
Zusammenfassung |
A sequential time dependent data assimilation scheme based on the Kalman
filter is applied to a spectral wave model. Usually, the first guess
covariance matrices used in optimal interpolation schemes are exponential
spreading functions, which remain constant. In the present work the first
guess correlation errors evolve in time according to the dynamic constraints
of the wave model. A system error noise is deduced and used to balance
numerical errors. The assimilation procedure is tested in a standard situation of swell
propagation, where the Kalman filter is used to assimilate the significant
wave height. The evolution of the wave field is described by a linear
two-dimensional advection equation and the propagation of the error
covariance matrix is derived according to Kalman's linear theory. Model simulations were performed in a 2-dimensional domain with deep-water
conditions, a relatively small surface area and without wind forcing or
dissipation. A true state simulation and a first guess simulation were used
to illustrate the assimilation outcome, showing a reasonable performance of
the Kalman filter. |
|
|
Teil von |
|
|
|
|
|
|