On October 31, IBES hosted Columbia professor Adam Sobel for “Usable Climate Science: Calculating Climate Risk in an Era of Extremes,” the second seminar in the Brown Seminar Series on Environment & Society organized by IBES graduate student affiliates. Speaking to a packed audience in Andrews House and online, Sobel examined one of the field’s most pressing challenges: how to turn vast amounts of climate data into insights that inform real-world decisions.

Rethinking climate science for an age of uncertainty

As the demand for climate risk information grows, traditional climate science is no longer enough, says Sobel. The need for “usable” climate science—information that can meaningfully guide adaptation, policy, and investment—has never been higher. But without standardized methods for assessing and communicating risk, the field could become fragmented and inaccessible, dominated by private companies offering expensive, proprietary tools with little transparency. 

Sobel laid out how his team—rather than relying solely on  historical records, traditional climate models, or private catastrophe models—builds open, peer-reviewed statistical-dynamic models that generate large sets of synthetic storms, then link them to exposure, vulnerability, and estimate loss.