Abstract:Arctic sea ice concentration is often coarsely observed and numerically computed despite its importance for polar climate system. In this work we present three machinelearning 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.
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