A comprehensive comparison is made among four sea surface temperature (SST) datasets: the optimum interpolation (OI) and the empirical orthogonal function reconstructed SST analyses from the National Centers for Environmental Prediction (NCEP), the Global Sea-Ice and SST dataset (GISST, version 2.3b) from the United Kingdom Meteorological Office, and the optimal smoothing SST analysis from the Lamont-Doherty Earth Observatory (LDEO). Significant differences exist between the GISST and NCEP 1961–90 SST climatologies, especially in the marginal sea-ice zones and in regions of important small-scale features, such as the Gulf Stream, which are better resolved by the NCEP product. Significant differences also exist in the SST anomalies that relate strongly to the number of in situ observations available. In recent years, correlations between monthly anomalies are less than 0.75 south of about 10°N and are lower still over the southern oceans and parts of the tropical Pacific where root-mean-square dif... Abstract A comprehensive comparison is made among four sea surface temperature (SST) datasets: the optimum interpolation (OI) and the empirical orthogonal function reconstructed SST analyses from the National Centers for Environmental Prediction (NCEP), the Global Sea-Ice and SST dataset (GISST, version 2.3b) from the United Kingdom Meteorological Office, and the optimal smoothing SST analysis from the Lamont-Doherty Earth Observatory (LDEO). Significant differences exist between the GISST and NCEP 1961–90 SST climatologies, especially in the marginal sea-ice zones and in regions of important small-scale features, such as the Gulf Stream, which are better resolved by the NCEP product. Significant differences also exist in the SST anomalies that relate strongly to the number of in situ observations available. In recent years, correlations between monthly anomalies are less than 0.75 south of about 10°N and are lower still over the southern oceans and parts of the tropical Pacific where root-mean-square dif...