Understanding Differences in Sea Surface Temperature Intercomparisons

Abstract

Our study shows that the intercomparison among sea surface temperature (SST) products is influenced by the choice of SST reference, and the interpolation of SST products. The influence of reference SST depends on whether the reference SSTs are averaged to a grid or in pointwise in situ locations, including buoy or Argo observations, and filtered by first-guess or climatology quality control (QC) algorithms. The influence of the interpolation depends on whether SST products are in their original grids or preprocessed into common coarse grids. The impacts of these factors are demonstrated in our assessments of eight widely used SST products (DOISST, MUR25, MGDSST, GAMSSA, OSTIA, GPB, CCI, CMC) relative to buoy observations: (i) when the reference SSTs are averaged onto 0.258 × 0.258 grid boxes, the magnitude of biases is lower in DOISST and MGDSST (<0.038C), and magnitude of root-mean-square differences (RMSDs) is lower in DOISST (0.388C) and OSTIA (0.438C); (ii) when the same reference SSTs are evaluated at pointwise in situ locations, the standard deviations (SDs) are smaller in DOISST (0.388C) and OSTIA (0.398C) on 0.258 × 0.258 grids; but the SDs become smaller in OSTIA (0.348C) and CMC (0.378C) on products’ original grids, showing the advantage of those high-resolution analyses for resolving finer-scale SSTs; (iii) when a loose QC algorithm is applied to the reference buoy observations, SDs increase; and vice versa; however, the relative performance of products remains the same; and (iv) when the drifting-buoy or Argo observations are used as the reference, the magnitude of RMSDs and SDs become smaller, potentially due to changes in observing intervals. These results suggest that high-resolution SST analyses may take advantage in intercomparisons.