Please join us for a UW Data Science Seminar featuring UW Earth and Space Sciences Research Scientist Mira Berdahl and UW Environmental and Forest Sciences graduate student Masha Vernik on Tuesday, September 30th from 4:30 to 5:20 p.m. PT.The seminar will be held in IEB G109.
“High-Resolution Modeling of Antarctic Ocean–Ice Interactions”
Abstract: Antarctic ice loss is accelerating, driven by warm circumpolar deep water (CDW) melting ice shelves from below. Yet the processes that deliver CDW to the ice sheet remain uncertain. Traditional climate models lack the resolution to capture the dynamics necessary to resolve the processes leading to CDW delivery to ice shelves. In this presentation, I will explore how novel global high-resolution climate simulations offer new insights into the drivers of CDW dynamics, while also posing significant computational challenges.
Biography: Mira Berdahl is a Research Scientist at the University of Washington whose work focuses on cryosphere–climate interactions. She combines climate and ice sheet modeling with in situ observations to understand how glaciers and ice sheets respond to climate change.
“Exploring the relationship between land access and perceived adaptive capacity to climate change among organic farmers in the United States: A Bayesian modeling approach”
Abstract: As seasons become less predictable and extreme weather events become more frequent and intense, farmers learn to adapt. This challenge is no less for organic farmers, who make important contributions to social well-being and ecological regeneration through their food production practices. Thus, it is vital to understand the constraints that affect the extent to which organic farmers can engage in climate adaptive practices. This research uses Bayesian structural equation modeling to assess the relationship between land access and perceived adaptive capacity to climate change among certified organic farmers in the United States. Survey data collected by the Organic Farming Research Foundation are integrated with meteorological data measuring drought, temperature extremes, and climatic variability. Perceived ability to adapt to climate change is used as the outcome variable to reflect the cognitive dimensions of adaptation decision-making. A latent variable is created that represents both current land access and future land needs. The model results suggest that at the population level, increased land access and land needs have a moderately negative, albeit uncertain, association with challenges adapting to climate change. Precipitation variability, relative heat extremes, challenges accessing financial capital, and increasing number of sales channels are positively associated with challenges adapting to climate change with more certainty, while increased sales through wholesale channels has a more certain, negative association. This research more broadly signals how Bayesian approaches offer a promising way to integrate qualitative findings into quantitative analyses, while accounting for uncertainty inherent in complex socio-ecological systems.
Biography: Masha is a graduate student at the University of Washington’s School of Environmental and Forest Sciences. She studies the factors that influence how farmers are adapting to climate change and is especially interested in the role of seed diversity in climate resilience. She employs qualitative and quantitative methods that include conducting interviews, evaluating survey data, and analyzing satellite imagery. Her learning extends beyond the classroom and into the field as an avid gardener and part-time farmworker. Before graduate school, she was a communications professional at a legal advocacy organization focused on building a more just food system.
The 2025-2026 seminars will be held in person, and are free and open to the public.