Lorenzo Zampieri et al. illustrate in this preprint , a novel method based on ML for reducing the surface temperature errors of atmospheric reanalyses in sea-ice-covered regions of the Arctic. The corrected temperature can be employed to support polar research activities, and to better simulate the evolution of the interacting sea ice and ocean systems in numerical models.