Physical Sciences and Mathematics Commons^™

Identifying Clouds With Convolutional Neural Networks, Jeff Mullins, Sean Richardson, Peter Drake

Portland Institute for Computational Science Publications

The greatest source of uncertainty in model estimates of projected climate change involve clouds and aerosols. Photographic images of clouds in the sky are simple to acquire and archive, but climate scientists need an automated process for identifying clouds in these images. We bring machine learning to bear on this problem. Specifically, we use convolutional neural networks, which to our knowledge have not previously been applied to this task. We trained a network to identify clear sky, thin cloud, thick cloud, and non-sky pixels in photos taken by the Total Sky Imager. The trained network is capable of classifying 91.9% …