Open AccessApproximation of ensemble members in ocean wave prediction
Author(s) -
FARINA LEANDRO,
MENDONÇA ANTÔNIO M.,
BONATTI JOSÉ P.
Publication year - 2005
Publication title -
tellus a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.016
H-Index - 77
eISSN - 1600-0870
pISSN - 0280-6495
DOI - 10.1111/j.1600-0870.2005.00113.x
Subject(s) - data assimilation , linearization , wave model , ensemble forecasting , fraction (chemistry) , ensemble learning , computer science , approximations of π , wind wave , algorithm , mathematics , meteorology , nonlinear system , artificial intelligence , physics , chemistry , organic chemistry , quantum mechanics , thermodynamics
An efficient method for generating members in a ocean wave ensemble prediction system is proposed. A linearization of the wave model WAM is used to obtain approximations of the ensemble members. This procedure was originally introduced in a dynamical assimilation scheme where Green's functions play a central role. The evaluation of member approximations can be carried out in a fraction of the time required by the full model integration. This aspect of the method suggests a way of increasing the ensemble size as well as refining the model resolution without increasing computational costs.