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.
ATMOSPHERIC INFLUENCE ON SOUTHERN OCEAN HEAT UPTAKE
The Southern Ocean is a critical player in global climate due to its ability to absorb, store, and transport heat. It has absorbed the majority of the excess heat associated with anthropogenic greenhouse gas emissions. The Southern Ocean is also one of the cloudiest places in the world, so I am interested in how clouds affect the mechanisms of ocean heat loss and gain in this region.
ADDRESSING CLIMATE CHANGE QUESTIONS WITH MACHINE LEARNING
Machine learning is a powerful and relatively new 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.