CAREER: Advancing Understanding of Hadley Cell Dynamics from Foundational Theory to Large Language Models

The Hadley cells are planetary-scale atmospheric circulations that span Earth's tropics, lifting warm, moist air near the equator and pushing dry, sinking air over the subtropics. The circulations govern the location of monsoons that sustain billions of people and impact the extent of the world's subtropical deserts. Despite this fundamental importance, theoretical understanding of where these cells terminate, and why their boundaries swing so dramatically with the seasons, remains incomplete. This project develops and tests a unified theory of the Hadley cell boundaries. This research will advance foundational atmospheric science and food and water security tied to monsoon variability. Another goal of the project is to prepare students for an AI-influenced future, which will be accomplished through mentorship, course development, and creation of open-source teaching modules on critical literacy of generative Artificial Intelligence (AI). For decades, theories of the Hadley cell extent have rested on either the angular-momentum-conserving axisymmetric limit or an opposite, eddy-dominated limit. Neither of these is a good fit for the Earth, where upper-tropospheric zonal winds correspond to local Rossby numbers of roughly 0.1 to 0.6. The Principal Investigator has recently extended a current baroclinic-instability framework into this regime by approximating each cell's Rossby number as a single, cell-averaged scalar, yielding realistic zonal winds and accurate descending-edge predictions across the seasonal cycle. The framework currently diagnoses the cell-mean Rossby number from the equilibrated flow, however, rather than predicting it from planetary parameters. The central goal here is thus to develop a predictive theory for the cell-mean Rossby number and use it to explain the Hadley cell seasonal cycle. The work consists of targeted simulations using a hierarchy of models with a wide range of mean states and configurations, accompanied by work extending the theoretical framework, for instance extending the classical equal-area energy balance to include eddy stresses. A complementary effort, in collaboration with the Critical AI Literacy Interest group at the City University of New York, will construct and administer a formal large language model benchmark for atmospheric dynamics, mapping the "jagged frontier" of current model capabilities and informing the project's educational modules. 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. NSF Award ID: 2544433 | Program: 01002930DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT,01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Spencer Hill | Institution: CUNY City College, NEW YORK, NY | Award Amount: $621,179 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2544433 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2544433.html