RAPID: Hurricane Helene (2024) Rainfall, Brown Ocean Signature, AI and Physics Model Guidance, and Social Media Sentiment

Hurricane Helene made landfall in Florida on September 26, 2024, and proceeded to produce extreme damage and casualties from wind and flooding after moving inland. This Rapid Response Research (RAPID) study seeks to determine the role that land surface conditions may have played in the maintenance of Helene after landfall. The researchers intend to further investigate the theory that wet conditions prior to a landfall can slow the decay of hurricanes.

The overall project will offer insights into how different meteorological, land-based, and public perception factors interact during hurricanes, contributing to improved prediction models and better disaster preparedness strategies.

The research team intends to examine precipitation and land-atmosphere feedbacks during Hurricane Helene to further address the Brown Ocean Effect, which is a phenomenon where wet soil surfaces contribute to the maintenance of a tropical system after it makes landfall. The research team will pull together surface, radar, and satellite measurements of precipitation to produce a detailed view of key rainfall parameters.

Satellite-based soil moisture data will be examined and numerical weather modeling will be used to simulate how soil moisture influenced the storm’s intensity post-landfall. The project will also compare precipitation forecasts from AI-based models with traditional weather models. Finally, the project has a social media component, where the researchers will analyze social media posts to understand how public perception evolves in response to hurricanes, which can be critical for future disaster communication strategies.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.