  Arctic sea ice concentration is often coarsely observed and numerically
computed despite its importance for polar climate system. In this work we
present three machine-learning methods to recover the original high-resolution
images from the coarse-grained low-resolution counterparts. The promising
results indicate a possibility of extending the application to a broad range of
geophysical variables.
