Abstract: A Piece-Wise Regression (PWR) method is proposed for bias correction of sea surface temperature (SST) from the Fengyun-3C (FY-3C) MicroWave Radiation Imager (MWRI) products. In this method, a regression model is developed to match the associated in-situ SST with daily climatological SST, and the optimal matchups are selected through the error analysis of the associated variables in the model. SSTs are then recalculated by using these optimal matchups in the Piece-Wise Regression model. Compared with the traditional probability density function (PDF) matching technique for bias correction, the PWR method can better remove biases in the spatial-temporal domain, and the standard deviations (SDs) and RMSEs are decreased from 0.9—1.0℃ to 0.6℃. This result is much better than that from the PDF method, which reduces the SDs and RMSEs from 0.9—1.0℃ to about 0.8℃.