RESEARCH
ARCTIC CLOUD - SEA ICE FEEDBACKS
The Arctic is the fastest-warming region on Earth in response to increasing anthropogenic greenhouse gas emissions. Sea ice loss is one of the most visible manifestations of this amplified warming. Due to their radiative impacts on the surface, clouds have the potential to accelerate or reduce the rate of observed sea ice loss. I am interested in feedbacks between clouds and sea ice in the context of present-day variability and future Arctic climate change.
CLIMATE INTERVENTION IMPACTS IN THE ARCTIC
Stratospheric aerosol injection (SAI) is a proposed climate intervention strategy for stabilizing or cooling Earth's surface temperature in an attempt to mitigate climate change impacts. I use global climate models to study projected impacts of hypothetical SAI scenarios on parts of the Arctic climate system. I currently focus on whether SAI could delay or prevent permafrost tipping points, and how sea ice changes after SAI deployment may affect the navigability of Arctic Ocean shipping routes.
ADDRESSING CLIMATE CHANGE QUESTIONS WITH MACHINE LEARNING
Machine learning is a powerful tool in the geosciences. I am interested in developing and using neural networks and other machine learning tools to investigate complex Earth system relationships and patterns, such as when the influence of certain climate intervention strategies may be detectable on permafrost and Arctic Ocean temperature.
TEACHING CLIMATE SCIENCE IN HIGHER EDUCATION
Teaching about climate science can be difficult because it is a complex and interdisciplinary science, but also because students may have preconceptions about the subject. I am interested in finding the most effective teaching methods to engage undergraduate and graduate students in learning about climate science. I use quantitative biometrics and qualitative surveys to assess the impacts of different active learning strategies on student engagement and knowledge retention.
