AISLENS (pronounced like “islands”) is an NSF-funded project within the GT Ice & Climate group to simulate many possible scenarios (i.e. a large ensemble, analogous to large climate simulation ensembles) of historical and future evolution of the Antarctic Ice Sheet under realistic variability in oceanic and atmospheric processes. To do so, we are developing novel statistical and machine learning tools to emulate output from state-of-the-art global climate models including high-resolution forcing of the Antarctic Ice Sheet from both the ocean and atmosphere. The purpose of this project is to understand the role of climate variability in the uncertainty of future sea level projections, and also to disentangle the role of internal vs. anthropogenic climate change in the observed rapid ice loss from Antarctica over the past several decades.
Collaborators: Dr. Matthew Hoffman (Los Alamos National Laboratory)
Current and past researchers: Shivaprakash Muruganandham (OSE PhD Student), Dr. John Erich Christian (EAS Postdoctoral Fellow)