AbstractWe have designed a method for testing the quality of multidecadal analyses of sea surface temperature (SST) in regional seas by using a set of high-quality local SST observations. In recognizing that local data may reflect local effects, we focus on the dominant empirical orthogonal functions (EOFs) of the local data and of the localized data of the gridded SST analyses. We examine the patterns, variability, and trends of the principal components. This method is applied to examine three different SST analyses, i.e., HadISST1, ERSST, and COBE SST. They have been assessed using a newly constructed high-quality dataset of SST at 26 coastal stations along the Chinese coast in 1960–2015, which underwent careful examination with respect to quality and a number of corrections for inhomogeneities. The three gridded analyses perform generally well from 1960 to 2015, in particular since 1980. However, for the pre-satellite period prior to the 1980s, the analyses differ among each other and show some inconsistencies with the local data, such as artificial break points, periods of bias, and differences in trends. We conclude that gridded SST analyses need improvement in the pre-satellite period (prior to the 1980s) by reexamining in detail archives of local quality-controlled SST data in many data-sparse regions of the world.