Open Educational Resources
Document Type
Assignment
Publication Date
Fall 12-7-2025
Abstract
This assignment introduces students to conceptual models of the El Niño–Southern Oscillation (ENSO) and guides them through a structured investigation of their physical and mathematical foundations. Students analyze the recharge–oscillator and delayed–oscillator frameworks, explore how differential equations capture ocean–atmosphere interactions, and evaluate parameter-driven changes in oscillatory behavior. A key component of the work is the guided use of generative AI as a research tool: students employ AI models to locate peer-reviewed literature, interrogate model extensions, and refine their understanding of complex mechanisms, while synthesizing all final explanations in their own words. By blending classical climate modeling with modern AI-supported inquiry, the assignment cultivates both technical fluency and critical skills for navigating contemporary scientific research.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
CUNY OER Funding
CUNY OER Initiative
Included in
Atmospheric Sciences Commons, Climate Commons, Dynamical Systems Commons, Dynamic Systems Commons, Oceanography Commons, Ordinary Differential Equations and Applied Dynamics Commons, Other Applied Mathematics Commons, Other Environmental Sciences Commons
Comments
OER Acknowledgment
Funding for this OER project was provided by the CUNY OER initiative, coordinated by the Teaching and Learning Center. This assignment is part of the course materials for Math A1200: Topics of Applied Mathematics — Mathematical Climate Models.
This project integrates conceptual climate modeling with structured Generative AI–assisted research, offering students an accessible and modern framework for exploring ENSO dynamics.