On data assimilation in a pseudo-spectral wave prediction model using a Kalman filter
Document Type
Conference Proceeding
Publication Date
10-1-2012
Abstract
A wave data assimilation scheme based on Kalman filtering combined with a nonlinear wave model is developed. Two state variables, the free surface elevation and the free surface velocity potential, are updated in time by solving the nonlinear evolution equations numerically using an efficient pseudo-spectral method while the error covariance matrix often computed numerically is determined analytically by solving the linear wave model in the wavenumber domain. Numerical experiments are performed with synthetic data with noise for one-dimensionally propagating irregular waves characterized by the JONSWAP spectrum. It is shown that the estimated free surface elevation using the present data assimilation scheme matches well the numerical solution of the nonlinear wave model in the absence of noise. The present data assimilation scheme improves greatly the stability and efficiency of the wave prediction system in comparison with that based on a purely numerical data assimilation scheme. © 2012 IEEE.
Identifier
84866708781 (Scopus)
ISBN
[9781457720895]
Publication Title
Program Book Oceans 2012 Mts IEEE Yeosu the Living Ocean and Coast Diversity of Resources and Sustainable Activities
External Full Text Location
https://doi.org/10.1109/OCEANS-Yeosu.2012.6263591
Recommended Citation
Yoon, Seongjin; Kim, Jinwhan; and Choi, Wooyoung, "On data assimilation in a pseudo-spectral wave prediction model using a Kalman filter" (2012). Faculty Publications. 18083.
https://digitalcommons.njit.edu/fac_pubs/18083
