ALBERT

Description: Author Posting. © American Meteorological Society 2006. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 19 (2006): 6153–6169, doi:10.1175/JCLI3970.1.

Description: The present study used a new net surface heat flux (Qnet) 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 degree Qnet controls 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 (hMLD). The study showed that the tropical Atlantic sector could be divided into two regimes based on the influence level of Qnet. SST variability poleward of 5°S and 10°N is dominated by the annual cycle of Qnet. In these regions the warming (cooling) of the sea surface is highly correlated with the increased (decreased) Qnet confined in a relatively shallow (deep) hMLD. The seasonal evolution of SST variability is well predicted by simply relating the local Qnet with a variable hMLD. On the other hand, the influence of Qnet diminishes in the deep Tropics within 5°S and 10°N and ocean dynamic processes play a dominant role. The dynamics-induced 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 of Qnet, hMLD, and SST variability serves as a measure of the quality of the Qnet product, then the Qnet from OAFlux + ISCCP and ERA-40 are most physically representative, followed by SOC. The NCEP–NCAR Qnet is least representative. It should be noted that the Qnet from 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 mean basis, where the ERA-40 and the NCEP–NCAR model reanalyses indicate that positive Qnet occurs only in the narrow equatorial band and in the eastern portion of the tropical basin. Nevertheless, seasonal variances of the Qnet from OAFlux + ISCCP and ERA-40 are very similar once the respective mean is removed, which explains why the two agree with each other in accounting for the seasonal variability of SST. In summary, the study suggests that an accurate estimation of surface heat flux is crucially important for understanding and predicting SST fluctuations in the tropical Atlantic Ocean. It also suggests that future emphasis on improving the surface heat flux estimation should be placed more on reducing the mean bias.

Description: This study is support by the NOAA CLIVAR Atlantic under Grant NA06GP0453 and NOAA Climate observations and Climate Change and Data Detection under Grant NA17RJ1223.

Description: Author Posting. © American Meteorological Society, 2009. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 22 (2009): 5527–5540, doi:10.1175/2009JCLI2961.1.

Description: A 5-yr climatology of the meteorology, including boundary layer cloudiness, for the southeast Pacific region is presented using observations from a buoy located at 20°S, 85°W. The sea surface temperature and surface air temperature exhibit a sinusoidal seasonal cycle that is negatively correlated with surface pressure. The relative humidity, wind speed, and wind direction show little seasonal variability. But the advection of cold and dry air from the southeast varies seasonally and is highly correlated with the latent heat flux variations. A simple model was used to estimate the monthly cloud fraction using the observed surface downwelling longwave radiative flux and surface meteorological parameters. The annual cycle of cloud fraction is highly correlated to that of S. A. Klein: lower-tropospheric stability parameter (0.87), latent heat flux (−0.59), and temperature and moisture advection (0.60). The derived cloud fraction compares poorly with the International Satellite Cloud Climatology Project (ISCCP)-derived low-cloud cover but compares well (0.86 correlation) with ISCCP low- plus middle-cloud cover. The monthly averaged diurnal variations in cloud fraction show marked seasonal variability in the amplitude and temporal structure. The mean annual cloud fraction is lower than the mean annual nighttime cloud fraction by about 9%. Annual and diurnal cycles of surface longwave and shortwave cloud radiative forcing were also estimated. The longwave cloud radiative forcing is about 45 W m−2 year-round, but, because of highly negative shortwave cloud radiative forcing, the net cloud radiative forcing is always negative with an annual mean of −50 W m−2.

Description: This research was supported by the Climate Prediction Program for the Americas (CPPA) of NOAA’s Climate Program Office. The Stratus Ocean Reference Station at 20°S, 85°W is supported by NOAA’s Climate Observation Program.