Super Resolution of Arctic Sea Ice Concentration

TL;DR

This paper introduces three machine-learning techniques to enhance the resolution of Arctic sea ice concentration images, enabling more detailed observations critical for climate studies.

Contribution

It presents novel machine-learning methods specifically designed for super-resolution of coarse Arctic sea ice data, improving detail and accuracy.

Findings

High-resolution images successfully reconstructed from low-resolution data

Methods show potential for broader geophysical variable applications

Results demonstrate significant enhancement in image detail

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 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.