Focus: Define habitability as an Earth system problem that requires integrating Earth’s interior, surface processes, oceans, atmosphere, life, and the space environment. Introduce the course’s core questions about what makes Earth habitable and how we study it using an Earth system science perspective.

Required Reading

1. Past, Present and Future of a Habitable Earth, Chapter 1
2. Past, Present and Future of a Habitable Earth, Chapter 2
3. Past, Present, and Future of a Habitable Earth, Chapter 5 (focus on interdisciplinary approaches and the human Earth system as a coupled system)

Focus: Explain how deep Earth dynamics connect to surface environments over long timescales and why linking deep Earth and surface Earth perspectives matters for habitability.

Reading: Past, Present and Future of a Habitable Earth, Chapter 5, section emphasizing deep Earth, deep sea, deep space, and whole Earth system perspectives.

Focus: Connect energy systems and resource availability to Earth processes and environmental constraints, using oil and gas as an example, and link resource security to long-term habitability.

Reading: Past, Present, and Future of a Habitable Earth, Chapter 3 (resources and energy security; role of oil and gas).

Focus: Explain how habitability is assessed beyond Earth, including the role of liquid water and planetary and stellar properties, and how exoplanet science clarifies what is distinctive about Earth.

Reading: Past, Present, and Future of a Habitable Earth, Chapter 4 (exoplanet exploration; habitability constraints; liquid water).

Focus: Explain how Earth system research depends on observation, integration across sea and land atmosphere, and data sharing platforms that support quantitative Earth system analysis.

Reading: Past, Present, and Future of a Habitable Earth, Chapter 5 (integrated observation systems; data sharing mechanisms and platforms).

Focus: Introduce how AI supports the analysis of large Earth-relevant datasets from in situ and remote sensing, including summarization, dimensionality reduction, and clustering, and how to evaluate interpretability versus utility.

Reading: Artificial Intelligence and Systems of the Earth, Chapter 3 (AI across Earth system disciplines; examples such as PCA and clustering).

Focus: Address complex Earth system behaviors such as teleconnections, cross-talk, weak signals, and correlation versus causation, and apply these ideas to responsible AI-enabled research or decision support for sustainability and habitability.

Reading: Artificial Intelligence and Systems of the Earth, Chapter 4 (teleconnections; limits of correlation-based learning for scientific understanding).