Accelerating actionable climate information through machine learning

The Aspen Global Change Institute (AGCI) proudly presents this Walter Orr Roberts Memorial Public Lecture, presented by Hannah Christensen (Wadham College, University of Oxford).

To improve societal and environmental wellbeing, decision-makers need climate information that is actionable. Actionable climate information needs to be timely; sufficiently detailed as to describe the region and processes of interest; trustworthy and truthful in acknowledging uncertainties; and policy- or decision-relevant.

We have already begun to observe the transformative power of machine learning (ML) to produce actionable knowledge in weather forecasting (where we can conveniently check whether our predictions are correct). How could ML to do the same, and more, in the context of climate change?

This talk will introduce how we make climate predictions, and then describe ways in which ML can enable us to make more trustworthy and more detailed climate predictions, at a faster pace. We’ll also explore how ML can provide a bridge between climate simulators and the idealized models used to develop climate policy, to provide a more complete understanding of the coupled Human-Earth system.

Register to attend via Zoom.