A Gulf Stream model and an altimetry assimilation scheme
Author(s) -
Mellor George L.,
Ezer Tal
Publication year - 1991
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/91jc00383
Subject(s) - altimeter , data assimilation , geology , gulf stream , coordinate system , geodesy , shallow water equations , mean squared error , anomaly (physics) , temperature salinity diagrams , elevation (ballistics) , interpolation (computer graphics) , climatology , sea surface height , meteorology , mathematics , salinity , geometry , frame (networking) , statistics , computer science , telecommunications , oceanography , physics , condensed matter physics
A continuous data assimilation scheme and a multilayer, primitive equation, numerical model are described. The model is an eddy‐resolving, coastal ocean model that has been extended to include the Gulf Stream region. It has complete thermohaline dynamics, a bottom‐following, sigma, vertical coordinate system, and a coastal‐following, curvilinear orthogonal, horizontal coordinate system. Calculated model fields are used to provide a model climatology and correlations between subsurface temperature and salinity anomalies and surface elevation anomalies. An optimal interpolation method, the surface to subsurface correlations, and estimated model and data errors are the basis of the assimilation technique. Altimetry anomaly data extracted from the model calculations according to the Geosat orbital schedule are used to test the assimilation scheme and to provide nowcasts and forecasts. Sensitivity studies are performed to test the effects of various parameters of the scheme. It is found that the scheme is less efficient in the shallow continental shelf area than in the deeper regions of the model. The results show significant nowcast skill, with area‐averaged rms error for surface elevation and subsurface properties of about 40–50% of the corresponding error of the unassimilated case. Good forecast skill, better than persistence, is demonstrated for 10–20 days; there is little skill after 30–40 days. Increasing the density of the satellite altimetry data (especially by decreasing the separation distance between tracks) should decrease the nowcast rms error to about 15% and improve the forecast.
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