Biography
Dr. Aaron Hill is a professor of meteorology in the School of Meteorology at the University of Oklahoma. His research interests include weather forecasting, data assimilation, numerical weather prediction, predictability of severe convective weather, artificial intelligence and machine learning, Python programming, innovative observing systems, and operational weather forecasting tools. Dr. Hill leads the CHAOS research group which specializes in Convection and weather Hazards with Artificial intelligence, Observations, and Simulations. The group is currently involved in developing machine learning tools for high-impact weather forecasting, exploring predictability of storms in warming climates, and understanding the dynamics of tornadogenesis in Quasi-Linear Convective Systems. Interested in joining the CHAOS group? Contact Dr. Hill: ahill@ou.edu
- Numerical Weather Prediction and Weather Forecasting
- Artificial Intelligence, Machine Learning, and Data Science
- Severe Storm Dynamics
PhD in Geosciences, 2019
Texas Tech University
MS in Atmospheric Science, 2014
Texas Tech University
BS in Atmospheric Science; Minor in Applied Mathematics, 2012
University of Washington
Group Announcements
02/2026
Congratulations to Nathan Erickson and Evan Sudler for winning presentation awards at the recent AMS Annual Meeting! The CHAOS group had over 10 presentations at the recent national meeting
In January, former undergraduate researcher Evan White had his work on postprocessing AI weather prediction models published in AIES - read more here!
08/01/2025
Congratulations to Christian McGinty for winning a presentation award for his poster on TORFF outlooks at the recent AMS Mesoscale conference! Hanna McDaniel and Kelly Geiger also presented their M.S. work at AMS Mesoscale for their first graduate school conference presentations!
In July, Evan White became the first student in the CHAOS group to submit a manuscript to a science journal, AIES - Evan’s project on postprocessing AI weather prediction models adds to a growing list of prediction systems for severe weather hazards.
Our summer REU student Ian Shank presented his final REU project in late July before we had to say goodbye for the summer. Ian completed an in-depth quantitative analysis of machine learning-based forecasts of severe weather and their utility at extended ranges.
05/22/2025
This summer, Ian Shank from UNC Charlotte will be an REU student in the group! Ian will be evaluating machine learning forecasts of severe weather to generate additional statistics and value for our operational partners.
04/25/2025
Welcome Mandy Voth and Braelyn Long to the group, two new undergraduate researchers! Both will be working on understanding the environmental evolution preceeding tornadogenesis with QLCS mesovortices.
Experience
Classes taught:
- METR 4970/5970: Numerical Weather Prediction (Fall 2025)
- METR 1313: Introduction to Programming for Meteorology (Spring 2024, 2025, 2026)
- METR 5970: AI for Environmental Science (Fall 2024, 2026)
Research Areas
Recent Publications
Recent Presentations
Full list of presentations here
Shank, I. and A. J. Hill, 2026: Assessing Machine Learning Probabilistic Forecast Utility for Severe Weather Forecasting. 25th Annual Student Conference, Houston, TX.
Sudler, E., A. J. Hill, and C. R. Homeyer, 2026: Artificial Intelligence Weather Prediction Model Performance for Hurricane Helene (2024). 25th Conference on Artificial Intelligence for Environmental Science, Houston, TX.
Schumacher, R. S., A. J. Hill, A. J. Tomanek, and J. A. Smith, 2026: Extreme Short-Term Precipitation in Gridded Precipitation Analyses and the CONUS404 Regional Climate Simulation. 40th Conference on Hydrology, Houston, TX.
McDaniel, H. J. and A. J. Hill, 2026: An Assessment of Mesovortices in Quasi-Linear Convective Systems from 2013-2023 Using GridRad-Severe. 16th Conference on Transition of Research to Operations, Houston, TX.
Vicens-Miquel, M., A. McGovern, A. J. Hill, E. G. Foufoula-Georgiou, C. Guilloteau, and S. S. Shen, 2026: A Diffusion-Based Framework for 1-km Spatial Resolution Precipitation Forecasting over CONUS. 25th Conference on Artificial Intelligence for Environmental Science, Houston, TX.
Spicer, E., P. M. Klein, A. J. Hill, and C. Wang, 2026: A Novel Approach to Nocturnal Heat Risk Analysis Using Machine Learning and the Unrestricted Mesoscale Analysis. 16th Symposium on Urban Environment, Houston, TX.
Hill, A. J., M. Voth, and B. Long, 2026: Characterizing Environmental Evolution in Advance of Tornadic and Non-Tornadic Mesovortices with PERiLS Field Campaign Datasets and High-Resolution Simulations. 16th Conference on Transition of Research to Operations, Houston, TX.
Erickson, N., A. McGovern, and A. J. Hill, 2026: Deep Learning for Probabilistic Nowcasting of Radar Reflectivity in Tornadic Storms. 25th Conference on Artificial Intelligence for Environmental Science, Houston, TX.
Geiger, K. M., A. J. Hill, and R. S. Schumacher, 2026: Environmental Influences on Extreme and Less-Extreme Nocturnal Summertime Extreme Rainfall Events in the United States. 40th Conference on Hydrology, Houston, TX.
Fellman, B. J., H. E. Brooks, J. T. Ripberger, P. T. Marsh, S. R. Ernst, A. J. Hill, and M. Krocak, 2026: The Calm Before the Storm: A Climatological Overview of the Storm Prediction Center’s Day 4-8 Severe Weather Outlook. Third Symposium on the Future of Weather, Forecasting and Practice, Houston, TX.
White, E. and A. J. Hill, 2026: AI-MLP: Severe Weather Probabilities from Global AI Weather Models. 16th Conference on Transition of Research to Operations, Houston, TX.
Williams, J. K., A. McGovern, P. E. Tissot, J. L. Demuth, D. J. Gagne, D. R. Harrison, A. J. Hill, K. Musgrave, and C. D. Wirz, 2026: R2O lessons learned from the NSF AI Institute AI2ES. 16th Conference on Transition of Research to Operations, Houston, TX.
Contact
- ahill@ou.edu
- 120 David L. Boren Blvd Suite 5900, Norman, OK 73072