Predicting Intraseasonal Variability of Tropical Cyclone Frequency and Causal Interpretability Using Physics-Informed Machine Learning

Kim, Hyunjeong

The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.

Conveners will be contacted by the AGU25 Program Committee with any requests for mergers or edits to proposals. Conveners will be notified of the acceptance of their proposal in mid-June.

Abstract submissions will also open in mid-June and the deadline for abstract submissions is 30 July, 2025.

Please visit the AGU25 website for more information or please contact AGU with any questions.

Abstract: Predicting Intraseasonal Variability of Tropical Cyclone Frequency and Causal Interpretability Using Physics-Informed Machine Learning (AGU25)

Predicting Intraseasonal Variability of Tropical Cyclone Frequency and Causal Interpretability Using Physics-Informed Machine Learning

Hyunjeong Kim, Georgia Institute of Technology Main Campus, College of Computing, Atlanta, United States and Ali Sarhadi, Georgia Institute of Technology Main Campus, The School of Earth and Atmospheric Sciences, Atlanta, United States