Dan Chavas

Associate Professor of Earth, Atmospheric, and Planetary Sciences, Co-Lead of Risk and Resilience Research Community

Contact Info

Email

dchavas@purdue.edu

Websites

Dan Chavas is Professor of Atmospheric Science at Purdue University in the Department of Earth, Atmospheric, and Planetary Sciences. His lab does use-inspired fundamental and applied research on extreme weather in a warming world. Specifically, his research advances basic understanding of hurricanes, tornadoes, and severe thunderstorms, and uses this understanding to help make society more resilient to their hazards. He is also the lead of “Midwest Agrivoltaics for Resilient Communities”, a new NSF-funded Regional Resilience Innovation Incubator for the Midwest region with additional support from the Purdue Institute for a Sustainable Future, integrating weather, agriculture, economics, and energy engineering to advance agrivoltaics as a transformative resilience solution.

At ISF, Dan is co-lead of the Risk & Resilience research community.

Education

Dan was an NSF Postdoctoral Research Fellow in Civil and Environmental Engineering at Princeton University. He received his PhD in Atmospheric Science from MIT and his B.S. in Atmospheric and Oceanic Sciences and Applied Mathematics at the University of Wisconsin-Madison.

Research Interests

Extreme weather, hurricanes, tornadoes, climate, risk, impacts, resilience.

Research Impact

Dan’s lab has made numerous advances in the basic physical understanding of extreme weather, including hurricanes, severe thunderstorms, and tornadoes, and how those physics translate to societal impacts in a warming world. In 2020, Dan received the NSF Faculty Early Career Development (CAREER) award, and in 2024 he was awarded the Outstanding Early Career Award from the American Meteorological Society Committee on Tropical Meteorology and Tropical Cyclones. Under his CAREER award, he founded the Purdue Weather Risk Internship program, which links students to internship opportunities in the emerging job market of weather-dependent decision-making.


Research Area