Role of Net Surface Heat Flux in Seasonal Variations of Sea Surface Temperature in the Tropical Atlantic Ocean

The present study used a new net surface heat flux (Q net) product obtained from the Objective Analyzed Air–Sea Fluxes (OAFlux) project and the International Satellite Cloud Climatology Project (ISCCP) to examine two specific issues—one is to which degreeQ netcontrols seasonal variations of sea surface temperature (SST) in the tropical Atlantic Ocean (20°S–20°N, east of 60°W), and the other is whether the physical relation can serve as a measure to evaluate the physical representation of a heat flux product. To better address the two issues, the study included the analysis of three additional heat flux products: the Southampton Oceanographic Centre (SOC) heat flux analysis based on ship reports, and the model fluxes from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40). The study also uses the monthly subsurface temperature fields from the World Ocean Atlas to help analyze the seasonal changes of the mixed layer depth (h MLD). The study showed that the tropical Atlantic sector could be divided into two regimes based on the influence level ofQ net. SST variability poleward of 5°S and 10°N is dominated by the annual cycle ofQ net. In these regions the warming (cooling) of the sea surface is highly correlated with the increased (decreased)Q netconfined in a relatively shallow (deep)h MLD. The seasonal evolution of SST variability is well predicted by simply relating the localQ netwith a variableh MLD. On the other hand, the influence ofQnet diminishes in the deep Tropics within 5°S and 10°N and ocean dynamic processes play a dominant role. The dynamicsinduced changes in SST are most evident along the two belts, one of which is located on the equator and the other off the equator at about 3°N in the west, which tilts to about 10°N near the northwestern African coast. The study also showed that if the degree of consistency between the correlation relationships ofQ net,h MLD, and SST variability serves as a measure of the quality of theQ netproduct, then theQ netfrom OAFlux + ISCCP and ERA-40 are most physically representative, followed by SOC. The NCEP–NCARQ netis least representative. It should be noted that theQ netfrom OAFlux + ISCCP and ERA-40 have a quite different annual mean pattern. OAFlux + ISCCP agrees with SOC in that the tropical Atlantic sector gains heat from the atmosphere on the annual mea