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Abstract As marine heatwaves and mass coral bleaching events rise in frequency and severity, there is an increasing need for high-resolution satellite products that accurately predict reef thermal environments over large spatio-temporal scales. Deciding which global sea surface temperature (SST) dataset to use for research or management depends in part on the desired spatial resolution. Here, we evaluate two SST datasets – the lower-resolution CoralTemp v3.1 (0.05° ~ 5 km grid) and the Multiscale Ultra-high Resolution MUR v4.1 (0.01° ~ 1 km grid) – in their ability to predict in situ reef thermal environments (nightly mean and daily maximum) and the severity of past bleaching in Palau, western Pacific Ocean. We expected higher-resolution data to improve prediction accuracy, yet CoralTemp data explained 10% additional variability of in situ temperatures and 70% additional variance in past bleaching. This likely relates to differential data protocols; despite MUR using a higher spatial resolution grid, CoralTemp achieves higher raw satellite observation density in coastal areas by utilising geostationary satellites. MUR SSTs were also consistently more variable. These results reinforce calls to develop more accurate high-resolution SST products for coral reefs. Our paper demonstrates that higher spatial resolution SST data is not necessarily better at predicting in situ thermal environments of coral reefs and local marine heatwave impacts.