Sea surface temperature (SST) is a key climate variable in oceanographic and meteorological research, widely applied in studies of ocean-atmosphere interactions, ocean mixing, boundary layer processes, and ocean state forecasting. The hourly SST data provided by the European geostationary meteorological satellite Meteosat-8/SEVIRI (M8) is an important data source for these studies. However, the spatiotemporal variations in the errors of SST data from M8 are not yet clear. To assess the reliability and applicability of SST data from M8, this study uses in-situ SST data from the iQuam quality monitoring platform which includes data from ships, drifting buoys, and Argo floats, to validate the hourly SST data from M8 in the Indian Ocean region. The results show that the average bias between M8 and the three types of in-situ data ranges from -0.06 to -0.10 ℃, the root mean square error ranges from 0.48 to 1.03 ℃, and the coefficient of determination ranges from 0.96 to 0.99. Among these, drifting buoys have the most matchups with M8 and the widest coverage, making them an ideal validation data source. Analysis of the spatiotemporal distribution of SST data biases from M8 reveals a -0.6 ℃ bias at night in the northwestern Arabian Sea and northwestern Bay of Bengal, with larger negative biases during the day in these areas, and a bias exceeding -1.0 ℃ during the day in parts of the 40°S-60°S region. SST data from M8 tends to show maximum positive biases in summer and minimum negative biases during the spring-to-summer transition period.