Abstract. Precipitation extremes are localized and spatially heterogeneous events. Magnitude of precipitation extreme p is expected to be spatial resolution dependent. Heavy precipitation extremes tend to be less intensive at coarser resolutions due to the averaging effect of the neighbouring less extreme events. Given the resolution dependent p, this study aims to investigate how spatial resolutions affect projected changes in precipitation extremes between future and historical periods, i.e. p_fut − p_his, which is a commonly used metric in climate projections. Our results show that although p is sensitive to spatial resolutions, differences in p_fut − p_his among various spatial resolutions are relatively small. Assessments of performances of GCMs in simulating p and p_fut − p_his are conducted based on three commonly used strategies that account for differences in spatial resolutions between GCMs and observations, i.e. the site-scale, the grid-scale, and the grid-point (i.e. direct comparison of grid-against scale-extremes) comparisons. Performances of GCMs in the site-scale comparison outperform those in the grid-scale and grid-point comparisons, because the statistical downscaling method incorporates the site-scale information to the future values when downscaling the GCMs. Assessment results of the grid-point comparison are comparable to those of the grid-scale comparison, even though the former has been criticized for not accounting for the difference in spatial resolutions between GCMs and observations. The spatial distributions of p_fut − p_his under RCP8.5 show that their differences between the site scale and the GCMs’ original resolutions are marginal. Given the considerable discrepancies among GCM outputs, the effects of spatial resolutions on projected changes are negligible.