Regional sensitivity patterns of Arctic Ocean acidification revealed with machine learning

Abstract

An unsupervised machine learning technique clustering carbonate outputs from two climate models indicates geographically consistent boundaries to ocean acidification patterns in the Arctic Ocean, with projected boundaries being sensitive to sea ice extent.