The extreme temperature changes under a 0.5 °C global mean surface temperature warming increment is of great importance for climate change adaption and risk management on post-Paris-Agreement agenda. The impacts of the already happened 0.5 °C warming increment on extreme temperature can serve as essential references for the 1.5/2 °C projections. Quantifying the observed changes of climate extremes is hampered by the limitation of observational datasets in both spatial coverage and temporal continuity. The reanalysis datasets are hoped to be useful substitutes for the observations, but their performance over continental China remains unknown. In this study, we compare the extreme temperature changes associated with the past 0.5 °C warming derived from three reanalysis datasets including JRA-55, ERA and 20CR with the observation in China. Distinct increases (decreases) in warm (cold) extremes are detected in all three reanalyses in a spatially aggregated perspective as in the observation. On regional scales the reanalyses have evident spreads in regions with insufficient observational coverage such as the western China. JRA-55 shows good agreement with the observation in both spatial patterns and magnitudes of extreme temperature changes. Both ERA and 20CR show weaker consistency with the observation, particularly in western China, mainly due to less observational constraints in data assimilation. The different aerosol data used in reanalysis assimilation systems also influenced the data quality. Our results indicate that while the reanalyses can serve as useful substitutes to fill in the observational gaps, cautious should be taken in regions with sparse observations and large anthropogenic aerosol emissions.