| Topic: | Earth System Predictability across Scales |
| Date: | July 20th - 31st, 2026 |
| Application timeline: | Application opens on Mar 2nd (Mon), 2026 |
| Application closes on Apr 24th (Fri), 2026 | |
| Results will be announced in May, 2026 | |
| Participants: | The application is open to graduate students and postdocs. International candidates are also eligible to apply. |
| Description: | Rossbypalooza is a two-week-long project-oriented summer school for people from a broad field of atmospheric, oceanic, and planetary sciences. The goal is to provide a platform for interaction among students and faulty, fostering a deep understanding of the dynamical processes governing predictability, offering hands-on experience with cutting-edge tools, and connecting these advances to broader climate and societal relevance. The school will consist of lectures and projects where participants will work in groups to address a question of their choice, mentored by one of the faculty members. |
| Acknowledgement: | Rossbypalooza is funded by National Science Fundation (NSF), AI for Climate (AICE), and Department of the Geophysical Sciences. The computational resources are provided by the Research Computing Center (RCC) at UChicago. The organizers want to thank their generous support for making the event possible. |
Rossbypalooza is a student-led summer school at the University of Chicago. It is named after the Swedish meteorologist Carl Gustav Rossby and Lollapalooza, the annual music festival of Chicago. Carl Gustav Rossby was the head of the department of meteorology in the University of Chicago when he did his pioneering work on the Rossby waves of Earth’s atmosphere. In the spirit of celebrating climate science with fun, Rossbypalooza brings together people from different fields to understand the climate of Earth and other planets. Check out the past Rossbypalooza held in 2016, 2018, 2022, and 2024!
This year’s topic is “Earth System Predictability across Scales”. Improving the predictability of the Earth system is essential for enhancing societal resilience to environmental changes. Achieving this requires a deeper understanding of the processes across a wide range of spatial and temporal scales in each component of the Earth system. The field is at a particularly exciting moment due to recent breakthroughs in data-driven forecasting that transform how we approach prediction. These advances, being carefully re-examined and combined with continued progress in physical-based modeling, make this a timely opportunity to revisit fundamental questions about the sources, limits, and opportunities for Earth system predictability across scales.
The summer school aspires to address this pressing need by engaging the next-generation climate scientists and statisticians in cross-cutting research activities and tackling the problem by understanding, practicing, and applying our knowledge of predictability.
The summer school will consist of lecture series by faculty in the first week, introducing their experience of tackling problems related to predictions and risk assessments. However, the focus of the program is a hackathon, where participants will work in groups throughout the two weeks to solve problems in consultation with the faculty members. At the end of the program, participants will present their results and get feedback from the faculty.
This school is open to graduate students and postdocs working in atmospheric, oceanic, sea ice, glacier, and (exo)planetary sciences. Last time, we accepted 31 external students in total. People interested in climate research with applied math or physics background are also encouraged to apply. Please contact us at rossbypalooza@uchicago.edu for further details.
Click on a faculty member to see their research interests and Rossbypalooza contributions!
University of ChicagoFaculty and project mentorMy research interests are in the large-scale circulation of the atmosphere, transport and mixing, diabatic sources of Rossby waves. |
University of ChicagoFacultyProf. 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. |
University of ChicagoFaculty and project mentorMy research interests fall in two main threads. The first includes the use of the isotopic composition of atmospheric water vapor as a tracer of convective processes, cirrus formation, and stratosphere-troposphere exchange; and the design of spectroscopic techniques for in-situ trace gas measurements. The second includes climate (and human) response to greenhouse-gas forcing; development of tools for impacts assessment; statistical emulation of climate model output; and climate and energy policy evaluation. |
Stanford UniversityFaculty and project mentorMy research interests are in the physics of rainstorms and atmospheric circulations in a changing climate. I am particularly interested in what environmental factors control the temporal and spatial scales of rainstorms, how will the characteristic scales of rainstorms change in a warmer climate, and how the collective effects of individual rainstorms, in turn, shape Earth's climate. |
University of ChicagoFaculty and project mentorMy research aims to improve our understanding of the dynamics of the oceans, the atmosphere, and the coupled climate system. I am particularly interested in the processes that govern the transport of heat and other constituents in the atmosphere and ocean. Understanding the mechanisms of these transport processes is key to our understanding of changes in the climate system during Earth’s past and future. I tackle these questions using a combination of theoretical fluid dynamics, numerical simulations and data analysis. |
University of ChicagoFaculty and project mentorI use mathematical and computational models to understand and explain fundamental problems in Earth and Planetary Sciences. I have worked on problems related to climate, paleoclimate, planetary habitability, and exoplanets. Of most relevance to this Rossbypalooza, I have collaborated with Jon Weare and others to apply rare event simulation techniques to geophysical problems. |
University of ChicagoFaculty and project mentorI lead the Climate Extremes Theory and Data (CeTD) group, which focuses on integrating theory, simulations, observations, and machine learning (ML) techniques to understand the dynamics and future changes of extreme weather events in a changing climate. My group is also interested in developing new scientific ML techniques for improving the modeling and analysis of the climate system and turbulent flows, and more broadly, multi-scale, nonlinear dynamical systems. In addition, I am the Faculty Director of the AI for Climate Initiative and Co-director of the Human-centered Weather Forecasts Initiative |
University of ChicagoFaculty and project mentorMy research seeks to improve our understanding of ice sheet dynamics, with the ultimate goal of improving projections of ice sheet and glacier change. I am interested in integrating concepts from materials science, solid earth geophysics, and applied mathematics to characterize (1) how ice sheet dynamics are governed by microphysical processes, (2) how microphysics gives rise to macroscale behavior (such as ice flow and fracture), and (3) how we can include these physical processes into ice sheet models that ultimately produce projections of sea-level rise. This research unites laboratory data, satellite and field observations, and numerical modeling. |
University of ChicagoFaculty and project mentorI am interested in the Earth’s climate system, biogeochemical cycles, and their relationship to humanity at the global scale. Much of my research pairs elementary models with statistical analyses of observational products. Specific research foci include the ocean’s biological pump, climate and carbon cycle feedbacks from decadal to multimillennial timescales, extreme events, and the effectiveness and potential harmfulness of proposed climate intervention strategies. I’m also fascinated by the fractal geometry of geographical features. |
Massachusetts Institute of TechnologyKeynote speaker and project mentorIn recent years, I have become very interested in the idea of bringing atmospheric physics to bear on the quantitative assessment of climate risk. For more than 20 years, I have served on the boards of various insurance and re-insurance companies, and this has been a window into how these industries assess the risk of various weather hazards, from severe convective storms to heatwaves and droughts. Broadly, these risks are assessed mostly by examining the statistics of historical events. Unsurprisingly, it turns out that historical records are not long enough to do this well, and because of climate change, the statistics are not stationary. I believe that atmospheric science is well positioned to bring physical modeling to bear on the problem of extreme events and long-term risk assessment, and have devoted much time and effort to doing that for the case of tropical cyclones. Recently, I have become interested in doing that for severe convective storms. I strongly believe that making citizens acquainted with their own climate risks...risks to their possessions and livelihood, is key to giving us the knowledge we need to make informed decisions about mitigating and adapting to climate change. To accomplish this, we need to train a subset of atmospheric scientists to understand the fundamentals of risk science, and to understand how insurance can be an efficient way of communicating weather and climate risk to the public. |
Fudan UniversityFaculty and project mentorI am interested in the fundamental aspects of the dynamical processes in atmosphere-ocean-climate systems (e.g., squall line, tropical cyclone, ENSO, NAO, sudden stratospheric warming), atmospheric predictability, uncertainty production, information flow, causal discovery, causal machine learning and forecasting, etc. Originated from atmospheric predictability and uncertainty propagation, information flow proves to be a natural measure of causality. The resulting causality analysis, which traditionally is classified as a statistical problem, is hence put on a rigorous footing of physics. The formalism has been widely applied to problems in the diverse disciplines such as climate science, neuroscience, financial economics, artificial intelligence, quantum mechanics, etc. Currently we are working on the development of information flow-based causal AI algorithm for interpretability enhancement, and to apply it to tropical cyclone forecasting. |
National Center for Atmospheric ResearchFaculty and project mentorIsla's research interests lie in Earth System Modeling and in the use of these models to understand and predict Earth System variability at spatial scales ranging from the planetary to the regional and on timescales from seasonal to multi-decadal. She focuses on comparing model representation of climate variability and long term trends with observations in the context of both free running historical simulations and initialized seasonal or decadal predictions with an overall aim of identifying model mis-representations and understanding how they may be impacting on prediction skill and long-term climate projections. In this context, she has worked on the dynamics of the tropospheric mid-latitude circulation, the hydrological cycle, the coupled stratosphere-troposphere system, and land-atmosphere coupling. |
University of ChicagoFaculty and project mentorKatie Kowal is the Director of AI for Weather at the Data Science Institute, working closely with the Climate Extremes Theory and Data (CeTD) group led by Professor Pedram Hassanzadeh in the Geophysical Sciences Department and the Human Centered Weather Forecasts Initiative (HCWF). She manages large interdisciplinary projects, conducts research on AI forecasts at weather and subseasonal timescales, and supports strategic planning across multiple initiatives. As part of HCWF, she coordinates research and operational teams to help bridge the gap between AI advances in weather and subseasonal-to-seasonal forecasting and their practical usefulness for decision-makers in low- and middle- income countries. Previously, as the Weather Forecast Lead for the Human Centered Weather Forecasts Initiative Indian Monsoon Onset project, she managed the operational deployment of the Indian monsoon onset forecasts in 2025 and led curriculum development for AIM for Scale’s first AI weather training program.. |
Nanjing UniversityFaculty and project mentorY. Qiang Sun’s research centers on the predictability of the atmosphere and the broader climate system, with a particular focus on extreme weather events such as tropical cyclones and intense rainfall. He investigates how multiscale physical processes interact within chaotic systems to drive forecast error growth and shape the limits of prediction. His work integrates physics-based numerical models, high-resolution simulations, and data-driven machine learning approaches to better understand the dynamics governing high-impact extremes. A key aspect of his research is identifying the mechanisms that constrain or enhance predictability, and evaluating the potential of emerging AI weather models to extend forecast skill, especially for rare and unprecedented events. Overall, his work seeks to advance fundamental understanding of atmospheric predictability while improving the forecasting of societally critical extremes. |
National Center for Atmospheric ResearchFaculty and project mentorMy research focuses on seasonal to decadal variability and predictability of the coupled Earth system. I use a combination of models and observations to understand the ocean and coupled dynamics that contribute to initial condition predictability on climate timescales. The end goal of my research is to improve our ability to reliably forecast regional environmental change from months to decades in advance. |
Application opens on Mar 2nd (Mon), 2026
Application closes on Apr 24th (Fri), 2026
Results will be announced in May, 2026
1. Curriculum Vitae: Please make it no more than 2 pages. Accepted formats: doc/docx/pdf.
2. Research statement: Please describe your research for scientists outside of your field within 300 words.
3. Statement of purpose: Please describe how you will benefit from Rossbypalooza within 200 words.
4. You will also be asked in the application form if you would like to work on a research idea of your own for the group project (not required). If you do, please also prepare a paragraph of idea description.
Click here to open the application!Rossbypalooza is free for all participants. This includes tuition, housing in Hyde Park, breakfast, and lunch. Funding for travel reimbursements is available for some applicants, especially for groups underrepresented in climate sciences (e.g., women, people of color, people with disabilities, and LGBTQ scientists/students). Please indicate your membership in any of these groups, as well as your desire for travel reimbursement, in the application form.
Rossbypalooza will be held on The University of Chicago campus in Chicago's historic Hyde Park neighborhood. Midway Airport is connected directly to Hyde Park by the #55 bus. For those flying into O'Hare, take the Blue line to downtown Chicago, and then transfer to the #2 / #6 bus, which go to Hyde Park. Uber and Lyft also serve the city of Chicago, between airports and the campus.
All students will be housed in single rooms or double rooms on The University of Chicago campus in Hyde Park. Rooms are fully furnished, and the details of the location and room amenities will be available soon. If you have any questions or special housing needs, please contact us directly at rossbypalooza@uchicago.edu.
Breakfast and lunch will be provided in the university cafeteria each weekday. Participants are responsible for their own dinner. There are many fantastic resturants for you to explore in Hyde Park and downtown Chicago!
Rossbypalooza is dedicated to providing a harassment-free workshop experience for everyone, regardless of gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age or religion. We do not tolerate harassment of workshop participants in any form. Workshop participants violating these rules may be sanctioned or expelled from the workshop at the discretion of the workshop organizers. Read the full code of conduct here.
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2. Paradise, Adiv, Cesar B. Rocha, Pragallva Barpanda, and Noboru Nakamura. "Blocking statistics in a varying climate: Lessons from a “traffic jam” model with pseudostochastic forcing." Journal of the Atmospheric Sciences 76, no. 10 (2019): 3013-3027.
3. Williams, Daniel A., Xuan Ji, Paul Corlies, and Juan M. Lora. "Clouds and Seasonality on Terrestrial Planets with Varying Rotation Rates." The Astrophysical Journal 963, no. 1 (2024): 36.
4. Loftus, Kaitlyn, Yangcheng Luo, Bowen Fan, and Edwin S. Kite. "Extreme weather variability on hot rocky exoplanet 55 Cancri e explained by magma temperature–cloud feedback." Proceedings of the National Academy of Sciences 122, no. 17 (2025): e2423473122.
