A model study of the seasonality of sea surface temperature and circulation in the Atlantic North-eastern Tropical Upwelling System

The climatological seasonal cycle of the sea surface temperature (SST) in the north-eastern tropical Atlantic (7-25°N, 26-12°W) is studied using a mixed layer heat budget in a regional ocean general circulation model. The region, which experiences one of the larger SST cycle in the tropics, forms the main part of the Guinea Gyre. It is characterized by a seasonally varying open ocean and coastal upwelling system, driven by the movements of the intertropical convergence zone (ITCZ). The model annual mean heat budget has two regimes schematically. South of roughly 12°N, advection of equatorial waters, mostly warm, and warming by vertical mixing, is balanced by net air-sea flux. In the rest of the domain, a cooling by vertical mixing, reinforced by advection at the coast, is balanced by the air-sea fluxes. Regarding the seasonal cycle, within a narrow continental band, in zonal mean, the SST early decrease (from September, depending on latitude, until December) is driven by upwelling dynamics off Senegal and Mauritania (15°-20°N), and instead by air-sea fluxes north and south of these latitudes. Paradoxically, the later peaks of upwelling intensity (from March to July, with increasing latitude) essentially damp the warming phase, driven by air-sea fluxes. The open ocean cycle to the west, is entirely driven by the seasonal net air-sea fluxes. The oceanic processes significantly oppose it, but for winter north of ~18°N. Vertical mixing in summer-autumn tends to cool (warm) the surface north (south) of the ITCZ, and advective cooling or warming by the geostrophic Guinea Gyre currents and the Ekman drift. This analysis supports previous findings on the importance of air-sea fluxes offshore. It mainly offers quantitative elements on the modulation of the SST seasonal cycle by the ocean circulation, and particularly by the upwelling dynamics. Keywords: SST, upwelling, circulation, heat budget, observations, modeling