Predicting weather is already a difficult statistical challenge, but it becomes even more complex when trying to predict rare weather events. Dan Cooley, a professor in the statistics department at Colorado State University, uses extreme value analysis to model these rare events. In today’s episode, we ask Dan how his work can help explain the changing frequency and severity of wildfires in Colorado and how climate change might be playing a key role.

Check out the episode here: LINK

Find our transcript here: LINK

Curious to learn more? Check out these additional links:

Hear Dan’s talk for IMSI’s Confronting Global Climate Change: https://www.imsi.institute/videos/transformed-linear-methods-for-multivariate-extremes-and-application-to-climate/

More on the Fire Weather Index: https://www.nwcg.gov/publications/pms437/cffdrs/fire-weather-index-system

Extreme Value Theory: https://towardsdatascience.com/extreme-value-theory-in-a-nutshell-with-various-applications-3260b6a84316

Previous Carry the Two episode on 100-year floods: https://podcasts.apple.com/us/podcast/richard-smith-on-100-year-floods/id1629115184?i=1000574780329

Follow more of IMSI’s work: www.IMSI.institute, (twitter) @IMSI_institute, (mastodon) https://sciencemastodon.com/@IMSI, (instagram) IMSI.institute

Follow Dan Cooley: https://www.stat.colostate.edu/~cooleyd/

This episode was audio engineered by Tyler Damme. Special thanks to Third Pod’s producer Jace Steiner.

Music by Blue Dot Sessions.

The Institute for Mathematical and Statistical Innovation (IMSI) is funded by NSF grant DMS-1929348.