This article focuses on evaluating the quality of sea surface temperature(SST) observed by satellite remote sensing. Under the premises that the scarcity of field measurement data and the abundant but overlapped multiple satellites detect information, in this article the consistency of multiple source information is used to verify the accuracy and reliability of satellite remote sensing data. Due to the limitation of Grubbs test when analyzing multi-source satellites SST, an improved algorithm is proposed, which is found to be more effectively than the traditional variance method when quantifying the differences and conflicts of SST. And the method is applied to the data extracted from 11 SST products in East China Sea, so a large amount of points set with high consistent can be confirmed, the outlying data can be discovered and eliminated, the waters (not include the outlying data) with confliction can be dig out and the conflicting level also can be quantized. It provides reference for the subsequent researchers to evaluate the quality of marine information.