We investigated the impact of Arctic ice-drifting buoys on an experimental ensemble reanalysis called ‘ALERA’. The ALERA, where the buoy data are assimilated, includes the analysis ensemble mean and spread for each prognostic variable. In the data set, ensemble spreads of surface variables were found to be small only in the regions of densely aggregated buoys. Comparing the ALERA and the data set without the assimilation of surface pressure data observed by the buoys, differences in the ensemble mean and spread between two data sets were locally large, modifying air temperature and winds near the surface. Examining the effect of Arctic-buoy distribution on long-term reanalysis data sets, it was found that the amount of cross-ensemble spreads derived from common reanalysis is very sensitive to the number of buoys. This suggests that data set accuracy might be more vulnerable to deterioration in the near future due to fewer opportunities for buoy deployments over the sea ice.