Model intercomparison in the Mediterranean: MEDMEX simulations of the seasonal cycle

• Published in: Journal of marine systems Vol. 33; pp. 215 - 251
• Main Authors: Beckers, J.-M., Rixen, M., Brasseur, P., Brankart, J.-M., Elmoussaoui, A., Crépon, M., Herbaut, Ch, Martel, F., Van den Berghe, F., Mortier, L., Lascaratos, A., Drakopoulos, P., Korres, G., Nittis, K., Pinardi, N., Masetti, E., Castellari, S., Carini, P., Tintore, J., Alvarez, A., Monserrat, S., Parrilla, D., Vautard, R., Speich, S.
• Format: Journal Article Web Resource
• Language: English
• Published: Elsevier B.V 01.06.2002; Elsevier; Elsevier Science Bv
• Subjects: Aquatic sciences & oceanology; Engineering Sciences; Fluid mechanics; Fluids mechanics; Life sciences; Marine; Mechanics; Mediterranean; MEDMEX; Physical, chemical, mathematical & earth Sciences; Physics; Physique, chimie, mathématiques & sciences de la terre; Sciences aquatiques & océanologie; Sciences du vivant; Seasonal cycle; MED; Mediterranean; MEDMEX; Seasonal cycle
• ISSN: 0924-7963; 1879-1573
• DOI: 10.1016/S0924-7963(02)00060-X

The simulation of the seasonal cycle in the Mediterranean by several primitive equation models is presented. All models were forced with the same atmospheric data, which consists in either a monthly averaged wind-stress with sea surface relaxation towards monthly mean sea surface temperature and salinity fields, or by daily variable European Centre for Medium Range Weather Forecast (ECMWF) reanalysed wind-stress and heat fluxes. In both situations models used the same grid resolution. Results of the modelling show that the model behaviour is similar when the most sensitive parameter, vertical diffusion, is calibrated properly. It is shown that an unrealistic climatic drift must be expected when using monthly averaged forcing functions. When using daily forcings, drifts are modified and more variability observed, but when performing an EOF analysis of the sea surface temperature, it is shown that the basic cycle, represented similarly by the models, consists of the seasonal cycle which accounts for more than 90% of its variability.