Leaving it all behind: Evacuation lessons from wildfires in Colorado

Digital model of how winds contribute to the progression of a wildfire
Special Event
Aug. 2, 2023

5:30 – 7:00 pm MDT

NSF NCAR Mesa Lab and Online

Do I have to leave? That is often the question when there are wildfires and other extreme weather events. Issuing orders of evacuation requires understanding both social and environmental factors. Understanding the delicate interconnection between fire and human behavior can improve emergency communication while supporting evacuation plans that better reflect local community and ecological needs.

In this NSF NCAR Explorer Series special event, a team from the Innovator Program shares lessons learned from community evacuation experiences with two recent fires: the 2020 East Troublesome Fire and the 2021 Marshall Fire. They will expand on modeling fire behavior, visualization for each fire’s progression, and what was learned from sharing these tools with residents who evacuated.

Catrin Edgeley

Early Career Faculty Innovator, Northern Arizona University

Dr. Catrin Edgeley is an Assistant Professor of Natural Resource Sociology in the School of Forestry at Northern Arizona University and an Early Career Faculty Innovator with NCAR in the program’s second cohort. As a wildfire social scientist, she explores how communities are adapting to and recovering from wildfire. Her research to date has spanned nine US states and several notable wildfires, including the 2019 Camp Fire in California. She earned her PhD in Natural Resources from the University of Idaho, and holds a MSc in Risk and Environmental Hazards and a BSc in Geography from Durham University in the UK.

William Cannon

Northern Arizona University

William Cannon is currently a Ph.D. student in The School of Forestry at Northern Arizona University (NAU), working with Dr. Catrin Edgeley as part of the Early Career Faculty Innovator Program. His current work in wildfire social science explores how socially diverse communities interpret and respond to fire in evacuation and recovery contexts. Using a qualitative interview approach, he investigates the diverse perspectives, knowledge, and experiences of communities affected by wildfires, aiming to identify effective strategies and approaches that can facilitate a more inclusive and informed decision-making process. He earned an MSc in geography at NAU and a BSc in geography from the University of Utah.

Timothy Juliano

Research Applications Laboratory (RAL)

Dr. Timothy Juliano is a Project Scientist at the Research Applications Laboratory of NSF NCAR. Timothy joined NSF NCAR in 2019 as a Postdoctoral Fellow after earning his B.S. degree in Meteorology from Millersville University (2013) and his M.S. (2015) and Ph.D. (2018) degrees in Atmospheric Science from the University of Wyoming. His research focuses on numerical weather prediction, with interests spanning a variety of lower atmospheric problems including boundary layer dynamics and turbulence, wildland fire prediction, meteorological impacts on renewable energy, and aerosol-cloud interactions.

Scott Pearse

Computational and Information Systems Laboratory (CISL)

Scott Pearse is a software engineer at NSF NCAR, where he helps develop the VAPOR 3D visualization package for the geophysical sciences.  Before joining NSF NCAR, Scott designed and deployed remote sensing systems for atmospheric physicists, and produced Quantitative Precipitation Estimation (QPE) analyses for various government agencies.  He holds a BS in Electrical Engineering, and an MS in Computer Science from the University of Colorado Boulder.

Branko Kosović

Research Applications Laboratory (RAL)

Dr. Branko Kosović is the Director of the Weather Systems and Assessment Program and the Program Manager for Renewable Energy for the Research Applications Laboratory (RAL). Dr. Kosović’s expertise is in boundary layer meteorology with a focus on high-resolution simulations of boundary layer flows. He has done research and development activities in atmospheric transport and dispersion, turbulence simulations and modeling for renewable energy applications, and has worked on inverse problems using nonlinear optimization and Bayesian inference with stochastic sampling. His current interests involve extending multiscale modeling capabilities in numerical weather prediction models for wind and solar energy and wildland fire prediction applications.

Event Recording