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Surface salinity response to changes in the model parameters and forcings in a climatological simulation of the eastern North-Atlantic Ocean

AutorMourre, Baptiste ; Ballabrera-Poy, Joaquim ; García-Ladona, Emilio ; Font, Jordi
Palabras claveSea surface salinity
Sensitivity experiments
Regional ocean model
Atmospheric forcing
Eastern subtropical North-Atlantic
Fecha de publicación28-mar-2008
CitaciónOcean Modelling 23(1-2): 21-32 (2008)
ResumenThe surface salinity response to changes of various external forcings and model parameters is investigated in a regional 1/3° configuration of the NEMO-OPA model implemented over the eastern North-Atlantic subtropical Ocean. Fourteen realistic climatological simulations are run. By default, neither relaxation to climatological surface salinity nor temperature is included. Forcing fields and parameters expected to impact the surface salinity are modified. These include: the wind stress, the surface temperature, wind speed and relative humidity entering the bulk calculation for sensible and latent heat fluxes, the precipitation, the data specified at open boundaries, the lateral viscosity operator, the salt lateral diffusivity, the vertical mixing scheme, the on/off switch of the double diffusion parameterization, the river runoffs and the SSS/SST restoring terms. The SSS standard deviation over this ensemble of model simulations is of the order of 0.1 psu, which is also the order of the annual cycle of the surface salinity field in this area.
In this experimental framework, the wind stress is found to have the largest impact on the model SSS, both in terms of mean field and annual variability. The sensitivity to the precipitation, atmospheric temperature, open boundary external data, and to the relaxation to climatological SSS and SST, is also significant. Of all the model parameterizations, the lateral salt diffusivity is the one associated to the strongest surface salinity model response. This work allows the identification of the main sources of error for model surface salinity. It paves the way for a more comprehensive investigation of SSS model error statistics, which is needed for future data assimilation experiments motivated by the close launch of the new SSS-observing SMOS and Aquarius satellite missions
Descripción12 pages, 13 figures, 1 table
Versión del editorhttp://dx.doi.org/10.1016/j.ocemod.2008.03.002
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