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University of Miami scientists launch accessible global climate modeling framework

Designed for education, adaptable for research—the new Python-based framework makes climate dynamics more approachable for students and researchers

2025-09-30
(Press-News.org) University of Miami scientists launch accessible global climate modeling framework
Designed for education, adaptable for research—the new Python-based framework makes climate dynamics more approachable for students and researchers

Miami, FL — A team of researchers at the University of Miami has developed a global atmospheric modeling framework that blends powerful research capabilities with accessibility for students and scientists alike. Written entirely in Python, a high-level, general-purpose programming language, and designed to run on an interactive Jupyter Notebook, the new tool removes longstanding technical barriers, allowing anyone with a standard laptop to explore cutting-edge climate experiments.

Most existing climate models rely on legacy Fortran code and complicated setups that are costly and time-consuming for students to use. By contrast, this open-source framework simplifies the process. Users can run experiments, analyze data, and visualize results directly within a notebook environment. Educators can tailor classroom exercises to different levels of complexity, while advanced researchers can adapt the model for original investigations into atmospheric dynamics.

“Python’s widespread use—and its clarity for beginners—were critical to our decision,” said Ben Kirtman, dean of the University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science and lead author of the study. “It also supports advanced features like machine learning and artificial intelligence for handling large datasets, which simply aren’t as accessible in traditional Fortran models.”

Kirtman’s motivation to re-code models in Python came after watching his students spend hours troubleshooting code just to get experiments running. The delays often hindered their progress and slowed research momentum.

Marybeth Arcodia, a co-author of the study and assistant professor in the Department of Atmospheric Sciences at the Rosenstiel School, experienced those setbacks firsthand as a graduate student in Kirtman’s lab. Her research explored long-term climate scenarios and weather patterns such as the El Niño–Southern Oscillation (ENSO), a recurring climate pattern that involves changes in the temperature of waters in the central and eastern tropical Pacific Ocean. Teleconnections like ENSO, where climate anomalies in one region affect distant parts of the globe, require models that can capture large-scale interactions.

“In its first demonstrations, the model successfully replicated global climate patterns associated with El Niño events, highlighting its ability to capture these complex phenomena,” Arcodia said.

Several innovations set this framework apart. Its Python-based core makes it easy to learn and modify. Adjustable atmospheric settings allow users to experiment with different levels of complexity, from simplified backgrounds to detailed formulations. The model can also simulate real-world influences such as heat sources, land features, and ocean conditions, opening opportunities for both classroom exercises and advanced research.

The team collaborated with the Frost Institute for Data Science and Computing to handle the substantial datasets needed for development. With its successful initial demonstrations, the framework shows strong potential for both education and scientific discovery.

Looking ahead, Kirtman is developing an experiential climate modeling course for undergraduate and graduate students, enabling them to design and test their own climate scenarios with the new tool. To maximize impact, the framework is available as open-source software on GitHub, ensuring global access for educators, students, and researchers.

The study, “A Simplified-Physics Atmosphere General Circulation Model for Idealized Climate Dynamics Studies,” was published August 22, 2025 online in the Bulletin of the American Meteorological Society.

Funding for the study was provided by the National Oceanic Atmospheric Administration (NA20OAR4320472, NA22OAR4310603, NA23OAR4590384 & NA23OAR4310457) and the National Science Foundation (AGS2241538 & AGS2223263). The authors wish to thank Brian Mapes, professor of atmospheric sciences at the University of Miami Rosenstiel School for helpful discussions. Ben P. Kirtman is the William R Middelthon Chair of Earth Sciences and is grateful for the associated support.

The authors are Ben. P. Kirtman1,2,3, Marybeth. C. Arcodia5, Emily. J. Becker1,2, Kayla. Besong7, Jackson. S. Boyd1, Houraa Daher1, Ian. Gifford1, Johnna. Infanti8, Josiah. Kaiser1, Samantha. Kramer7, Sarah. M. Larson10, Lucas. C. Laurindo2, Hosmay. Lopez9, Kelsey. Malloy6, Cait. Martinez1, Karen. Papazian1, Kathy. Pegion4, Natalie. Perlin11, Christina. Schuler1, Victoria. Schoenwald1, Leo. S. P. Siqueira1,3, Breanna. Zavadoff2  & Wei. Zhang1

1University of Miami, Rosenstiel School of Marine, Atmospheric, and Earth Science, Department of Atmospheric Sciences, Miami, FL, 2University of Miami, Rosenstiel School of Marine, Atmospheric, and Earth Science, Cooperative Institute for Marine and Atmospheric Studies, Miami, FL, 3University of Miami, Frost Institute for Data Science and Computing, Miami, FL, 4University of Oklahoma, School of Meteorology, Norman, OK, 5Colorado State University, Department of Atmospheric Science, Fort Collins, CO, 6Columbia University, Department of Applied Physics and Applied Mathematics, New York, NY., 7Sonoma Technology, LLC, Petaluma, CA, 8National Oceanic and Atmospheric Administration - Climate Prediction Center, College Park, MD, 9National Oceanic and Atmospheric Administration – Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, 10North Carolina State University – Department of Marine, Earth and Atmospheric Sciences, Raleigh, NC, 11RedLine Performance Solutions, LLC, Gaithersburg, MD.

About the University of Miami and Rosenstiel School of Marine, Atmospheric and Earth Science

 The University of Miami is a private research university and academic health system with a distinct geographic capacity to connect institutions, individuals, and ideas across the hemisphere and around the world. The University’s vibrant academic community comprises 12 schools and colleges serving more than 19,000 undergraduate and graduate students in more than 180 majors and programs. Located within one of the most dynamic and multicultural cities in the world, the University is building new bridges across geographic, cultural, and intellectual borders, bringing a passion for scholarly excellence, a spirit of innovation, and a commitment to tackling the challenges facing our world. The University of Miami is a member of the prestigious Association of American Universities (AAU).

Founded in 1943, the Rosenstiel School of Marine, Atmospheric, and Earth Science is one of the world’s premier research institutions in the continental United States. The school’s basic and applied research programs seek to improve understanding and prediction of Earth’s geological, oceanic, and atmospheric systems by focusing on four key pillars:

*Saving lives through better forecasting of extreme weather and seismic events.  *Feeding the world by developing sustainable wild fisheries and aquaculture programs.  *Unlocking ocean secrets through research on climate, weather, energy and medicine.  *Preserving marine species, including endangered sharks and other fish, as well as protecting and restoring threatened coral reefs.  

 

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[Press-News.org] University of Miami scientists launch accessible global climate modeling framework
Designed for education, adaptable for research—the new Python-based framework makes climate dynamics more approachable for students and researchers