An intercomparison of eight bulk sea surface turbulent flux algorithms used in data set generation as well as weather and climate prediction is performed for the tropical Pacific and midlatitude Atlantic. The results show some significant differences in fluxes due to differences in the way the algorithms consider wave spectrum, convective gustiness, and salinity as well as the way the algorithms parameterize roughness lengths and turbulent exchange coefficients. For instance, for sea surface temperature between 27.75¿C and 28.25¿C, the maximum differences in monthly latent heat flux and wind stress among algorithms over the tropical Pacific are about 23 W m-2 (or 16% relative to the algorithm-averaged flux) and 0.013 N m-2 (or 19% relative to the algorithm-averaged value) respectively. Evaluation of these algorithms using 270 hourly samples of observed turbulent flux data over the midlatitude Pacific shows that algorithms are largely consistent with observations. However, some algorithms show significant deviations from observations under certain conditions (e.g., weak wind conditions). Insights from the above intercomparison are then used to evaluate ocean surface turbulent fluxes from two global data sets, one is derived from satellite remote sensing while the other is a reanalysis. Over two buoy sites in the eastern and western tropical Pacific, the mean heat flux differences between the two data sets are primarily caused by differences in bulk variables (e.g., wind speed) rather than by differences in bulk algorithms. However, bulk algorithm differences could contribute up to 17 W m-2 to the long-term averaged latent heat flux over the tropical Pacific if different algorithms were used. This suggests that both bulk algorithms and the deviation of environmental variables need to be further improved in order to produce ocean surface turbulent fluxes with an accuracy of 10 W m-2.