AI for Climate Initiative (AICE)

AI for Climate Initiative (AICE) is sponsored by University of Chicago (Polsky Center and Data Science Institute). AI for Climate aims to accelerate and transform climate research with a focus on both scientific advances and societal impacts.

AICE: AI for Climate | DSI Climate change, particularly the exacerbation of extreme events, is among the most pressing challenges facing humanity and the scientific community.

Effectively addressing climate change requires rapid advances in Improving prediction capabilities and understanding of climate physics Developing quantitative models for climate change’s socioeconomic impacts, and Creating new climate adaptation and mitigation strategies.

The AI for Climate Initiative (AICE) combines staggering innovations in AI with a rapid increase in data availability and fundamental domain knowledge to significantly advance the key thrusts of AICE in a highly synergistic and interdisciplinary manner.

Close collaboration between different disciplines, such as climate science, computer science, economics, mathematics, physics, public health, social science, and statistics, is essential for innovating or properly adapting AI methods to develop novel tools, such as physics-informed predictive models, and trustworthy datasets for training or analysis.

From developing foundation AI climate and weather models to large language models, AICE aims to synergize and support the UChicago, Argonne National Laboratory, and Toyota Technological Institute communities, as well as external partners, to transform climate research.

AICE complements, supports, and closely connects existing initiatives, most notably, the DSI’s AI+Science Initiative (led by advisory board member Becca Willett), the Climate and Energy Institute, the Climate Systems Engineering Initiative (CSEi), the Innovation Commission and Development Innovation Lab (led by advisory board member Michael Kremer), and the Trillion Parameter Consortium for AI+Science (Co-led by Co-PI Ian Foster).

Postdoctoral scholars to work at the intersection of AI and human-centered weather forecasting. More information here Postdoctoral scholars to work on advancing the theoretical understanding and trustworthiness of AI climate emulators.

More information here Forecasting the Onset of the Indian Monsoon Training program to strengthen forecasting in low- and middle-income countries Human-Centered Weather Forecasts Associate Professor, Geophysical Sciences; Member, Committee of Computational and Applied Mathematics; Faculty Director, AI for Climate Deputy Division Director, Environmental Science Division, Argonne National Laboratory; UChicago CASE Senior Scientist Affiliate; Faculty Co-Director, AI for Climate Arthur Holly Compton Distinguished Service Professor, Department of Computer Science; Distinguished Fellow, MCS Division, Argonne; Senior Scientist, MCS Division, Argonne; Faculty Co-Director, AI for Climate Assistant Professor, Harris School of Public Policy; Senior Fellow, Energy Policy Institute of Chicago; Faculty Co-Director, AI for Climate Professor, Geophysical Sciences; Faculty Director, AI for Climate I lead the Climate Extremes Theory and Data (C e TD) group focused on integrating theory, simulations, observations, and machine learning techniques to understand the dynamics and future changes of extreme weather events in a changing climate.

Dr. Jiwen Fan is the Deputy Division Director and Senor Earth Scientist of the Environmental Science Division. She also holds a joint appointment as a senior scientist at University of Chicago. She is a Fellow of American Meteorological Society (AMS).

Dr. Fan’s research encompasses atmospheric chemistry and aerosols, cloud physics, convective systems, severe weather, aerosol-precipitation-climate interactions, land-atmosphere interactions, and human-earth system interactions.

Her primary foci in recent years include the impacts of environmental (e.g., urbanization, anthropogenic aerosols, wildfires) and climate change on convective storms and weather hazards and model developments of cloud microphysics and aerosol-cloud interactions.

Pertaining to AICE, she has been working with data scientists to develop machine learning models for predicting precipitation and hail, analyzing observational data, and building ML emulators for complex cloud microphysical processes.

Dr. Ian Foster is Senior Scientist and Distinguished Fellow, and also director of the Data Science and Learning Division, at Argonne National Laboratory, and the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago. Ian received a BSc degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science.

His research deals with distributed, parallel, and data-intensive computing technologies, and innovative applications of those technologies to scientific problems in such domains as materials science, climate change, and biomedicine. Foster is a fellow of the AAAS, ACM, BCS, and IEEE, and an Office of Science Distinguished Scientists Fellow.

In his research, he seeks to develop tools and techniques that allow people to use high-performance computing technologies to do qualitatively new things. This involves investigations of parallel and distributed languages, algorithms, and communication; and also focused work on applications.

He is particularly interested in using high-performance networking to incorporate remote compute and information resources into local computational environments. Amir Jina is an Assistant Professor at Harris Public Policy. Amir’s research focuses on the role of the environment in shaping how societies develop.

This research combines economics with methods from climate science and remote sensing to understand the impacts of climate, and has involved fieldwork on climate change adaptation with communities in India, Bangladesh, Kenya, and Uganda.

Amir is a founding member of the Climate Impact Lab – researching the socioeconomic impacts of climate change around the world – and scientific advisor to the Innovation Commission on Climate Change, Food Security, and Agriculture – promoting the use of weather services for climate change adaptation in low-income countries Amir received a Ph. D. in Sustainable Development and M.

A. in Climate and Society both from Columbia University, B. A.

s in Mathematics and Theoretical Physics from Trinity College, Dublin, and previously worked with the Red Cross/Red Crescent in South Asia. Prof. Shaw ’s research focuses on the physics of the atmosphere and climate system past, present and future. She seeks to understand the underlying mechanisms controlling the response to climate changes so that we can have greater confidence in future projections.

Her approach combines theory (primarily conservation laws), numerical modeling across a hierarchy of complexity and observational data analysis. Prof. Shaw is excited to take advantage of AI/ML tools for increasing our understanding and prediction of the impacts of climate change. She is working to ensure these methods get the right answer for the right reasons.

University Professor, Economics and the College and the Harris School of Public Policy; Director, Development Innovation Lab; Faculty Director, Development Economics Center at the University of Chicago Professor, Geophysical Sciences William E.

Wrather Distinguished Service Professor, Astronomy & Astrophysics and Physics, Enrico Fermi Institute, and Harris School of Public Policy Associate Laboratory Director, Computing, Environment and Life Sciences, Argonne; Professor of Computer Science, University of Chicago Faculty Director of AI, Data Science Institute; Worah Family Professor in the Wallman Society of Fellows, Department of Statistics, Computer Science, and the College Michael Kremer is the University Professor in the Kenneth C.

Griffin Department of Economics. He directs the Development Innovation Lab at the University of Chicago and chairs the Innovation Commission for Climate Change, Food Security, and Agriculture. He is Scientific Director of USAID’s Development Innovation Ventures.

Kremer is the 2019 co-recipient of the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel. He is a Member of the National Academy of Sciences, a recipient of a MacArthur Fellowship and a Presidential Faculty Fellowship, and was named a Young Global Leader by the World Economic Forum. Professor Nakamura has been on the faculty at the Department of the Geophysical Sciences since 1992.

He studies fluid dynamics of the atmosphere. Robert Rosner is a theoretical physicist, on the faculty of the University of Chicago since 1987, where he is the William E. Wrather Distinguished Service Professor in the departments of Astronomy & Astrophysics and Physics, as well as in the Enrico Fermi Institute and the University of Chicago Harris School of Public Policy.

He served as Argonne National Laboratory’s Chief Scientist and Associate Laboratory Director for Physical, Biological and Computational Sciences (2002–2005), and was Argonne’s Laboratory Director from 2005 to 2009; he was the founding chair of the U.S. Department of Energy’s National Laboratory Directors’ Council (2007–2009). His degrees are all in physics (BA, Brandeis University; PhD, Harvard University).

He was elected to the American Academy of Arts and Sciences in 2001, and to the Norwegian Academy of Science and Letters (as a Foreign Member) in 2004; he is also a Fellow of the American Physical Society.

Most of his scientific work has been related to fluid dynamics and plasma physics problems, as well as in applied mathematics and computational physics, especially in the development of modern high-performance computer simulation tools, with a particular interest in complex systems (ranging from astrophysical systems to nuclear fission reactors).

Within the past few years, he has been increasingly involved in energy technologies, and in the public policy issues that relate to the development and deployment of various energy production and consumption technologies, including especially nuclear energy, the electrification of transport, and energy use in urban environments.

He is the founding director of the Energy Policy Institute at the University of Chicago (EPIC), located at the University of Chicago Harris School of Public Policy and Booth School of Business.

Rick Stevens is the Associate Laboratory Director of the Computing, Environment and Life Sciences Directorate at Argonne National Laboratory, and a Professor of Computer Science at the University of Chicago, with significant responsibility in delivering on the U.S. national initiative for Exascale computing and developing the DOE initiative in Artificial Intelligence (AI) for Science.

At Argonne, he is leading the Laboratory’s AI for Science initiative and currently focusing on high-performance computing systems which includes leading a significant collaboration with Intel and Cray to launch Argonne’s first exascale computer, Aurora 21, which will pursue some of the farthest-reaching science and engineering breakthroughs ever achieved with supercomputing, as well as a partnership with Cerebras Systems to bring hardware on site to advance the massive deep learning experiments being pursued at Argonne for basic and applied science and medicine with supercompute-scale AI.

Prof. Stevens is a member of the American Association for the Advancement of Science and has received many national honors for his research, including an R&D 100 award. Rebecca Willett is a Worah Family Professor in the Wallman Society of Fellows and the Departments of Statistics and Computer Science at the University of Chicago .

She completed her PhD in Electrical and Computer Engineering at Rice University in 2005 and was an Assistant then tenured Associate Professor of Electrical and Computer Engineering at Duke University from 2005 to 2013. She was an Associate Professor of Electrical and Computer Engineering , Harvey D. Spangler Faculty Scholar, and Fellow of the Wisconsin Institutes for Discovery at the University of Wisconsin-Madison from 2013 to 2018.

Prof. Willett received the National Science Foundation CAREER Award in 2007, was a member of the DARPA Computer Science Study Group 2007-2011, and received an Air Force Office of Scientific Research Young Investigator Program award in 2010.

Prof. Willett has also held visiting researcher positions at the Institute for Pure and Applied Mathematics at UCLA in 2004, the University of Wisconsin-Madison 2003-2005, the French National Institute for Research in Computer Science and Control (INRIA) in 2003, and the Applied Science Research and Development Laboratory at GE Medical Systems (now GE Healthcare) in 2002.

Her research interests include network and imaging science with applications in medical imaging, wireless sensor networks, astronomy, and social networks. She is also an instructor for FEMMES (Females Excelling More in Math Engineering and Science; news article here ) and a local exhibit leader for Sally Ride Festivals .

She was a recipient of the National Science Foundation Graduate Research Fellowship , the Rice University Presidential Scholarship , the Society of Women Engineers Caterpillar Scholarship, and the Angier B. Duke Memorial Scholarship .

Research Administrator, Willett Research Group Research Professional, Department of the Geophysical Sciences Research Scientist, Data Science Institute Postdoctoral Scholar, Development Innovation Lab Postdoctoral Research Associate, Climate Systems Engineering initiative Postdoctoral Scholar, Data Science Institute Director, AI for Weather, AI For Climate Research Initiative PhD student, Harris School of Public Policy Postdoctoral scholar, Department of Geophysical Sciences Bing Gong is a research scientist at the Data Science Institute of the University of Chicago.

Her research focuses on developing state-of-the-art, scalable deep learning neural networks in weather prediction applications. Prior to joining the University of Chicago, Bing Gong held a position as an assistant professor at Shanghai Normal University in China and was a postdoctoral researcher at the Jülich Supercomputing Center in Germany. She obtained her Ph.

D. in the field of artificial intelligence in the application of environmental science and energy from the Technical University of Madrid, Spain, in July 2017. Research focus: Deep learning for Earth Systems, weather prediction Colin Aitken is a Postdoctoral Scholar at the Development Innovation Lab, working on projects related to safe water, weather, innovation policy, and education.

His other research interests include econometrics, meta-science, and homotopy theory. He received his PhD in Mathematics from the University of Chicago in 2023. Jessica Wan is a Postdoctoral Research Associate in the Climate Systems Engineering initiative at The University of Chicago.

Her research aims to understand how climate engineering proposals might reduce regional climate impacts by combining interdisciplinary analysis frameworks and modeling tools ranging from global climate models to AI emulators. Prior to joining UChicago, Jessica received her Ph. D.

in Earth Sciences from Scripps Institution of Oceanography at the University of California San Diego where her work focused on modeling the effects to regional marine cloud brightening. While completing her graduate degree, Jessica was a National Defense Science and Engineering Graduate fellow and an Achievement Rewards for College Scientists scholar. She also holds a B.

S. in Environment & Sustainability from Cornell University. Justin Finkel works on advancing the science of extreme weather and its relationship to climate, drawing on classic and new tools from applied mathematics to (1) sample extreme events more efficiently, (2) statistically analyze extreme weather ensembles to infer physical mechanisms and sources of predictability, and (3) inform model development as a result.

Following an interest in math, physics and climate sparked during high school, he obtained a Bachelor’s degree in physics and mathematics at Washington University in St. Louis, followed by a PhD in Computational and Applied Mathematics (the first cohort) at the University of Chicago, but with a long extended visit to the Courant Institute at New York University.

His PhD focused on highly idealized models of stratospheric variability, after which he moved “closer to earth” in a postdoctoral appointment at MIT, where he has worked on developing rare event sampling methods for extreme precipitation.

In the process, he rediscovered the value of idealized modeling, and in returning to UChicago for a second postdoc, he plans to leverage the hard-earned insight from both realistic and idealized ends of the model spectrum.

In his spare time, he enjoys contemplative runs along streets and water; minimalist cooking while pondering analogies between bread and the atmosphere; and unicycling along the lakefront, all while concocting elaborate puns and double entendres.

Prior to coming to the University of Chicago, she was a scientist at the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center International Desk, supporting multiple national meteorological services in Latin America and the Pacific Islands with operational forecasts, training, and research on improving subseasonal to seasonal forecasts.

Katie holds a DPhil in Hydrology and an MSc in Environmental Change and Management from the University of Oxford as a Rhodes Scholar and a BA in Physics and Political Science from Lewis & Clark College.

Earlier in her career, she was a science policy fellow at the Science and Technology Policy Institute, supporting the White House Office of Science and Technology Policy to develop national policy on regulating nuclear space launch approvals and improving critical infrastructure resilience to extreme events including space weather. Ozma Houck is a PhD Student at the Harris School of Public Policy.

Ozma’s research focuses on understanding how innovations in weather forecasting can be used to increase climate adaptation and accelerate the transition to renewable energy. Her work leverages traditional economic methods alongside tools from climate science and machine learning to study the socioeconomic impacts of climate and weather. Ozma received B.

A. s in Mathematics and Economics from Carleton College. She previously worked as a research professional at the Booth School of Business.

Rajat Masiwal is a postdoctoral scholar in the Department of Geophysical Sciences at the University of Chicago. His research focuses on improving sub-seasonal forecasts by integrating artificial intelligence with dynamical models. He earned his Ph.

D. from the Indian Institute of Science, Bangalore, where he investigated the dynamics of the Indian monsoon using observations, theory, and idealized modeling. His broader interests include understanding climate system processes through a hierarchy of models, combining physics-based approaches with emerging AI techniques.

Additionally he maintains an active interest in the meteorology of renewable energy resources, such as wind and solar, and how better forecasting of these can support a transition to a decarbonized electricity grid Related News, Insights, and Past Events AICE Speaker Series: Tapio Schneider (Caltech) AICE Speaker Series: Baylor Fox-Kemper (Brown University) AICE Speaker Series: Daniel C Reuman (University of Kansas) AICE Speaker Series: Colm-cille P.

Caulfield (Cambridge) AICE Speaker Series: Libby Barnes (Boston University) Nature Highlights Research on AI for Extreme Weather Forecasting AICE Speaker Series: V. Balaji (Schmidt Sciences) Weather Forecasting Training Program Bringing the Power of AI to Low- and Middle-Income Countries AICE Speaker Series: Pierre Gentine (Columbia) A Bet Worth Placing: Computing and Data Science at UChicago