Catastrophe modeling has historically been conducted primarily in the private sector, while academia and government scientists have taken the lead on the science of climate change. This has generally worked well in previous decades. However, it has left blind spots in our ability to fully understand climate risk, and the time to fix those is now.

Most mainstream climate science focus has been on averages across the largest space and time scales. While there has been ample academic research on how extreme events are changing, the results have not necessarily been “plug and play” for the re/insurance industry. Changes in return periods for events of a given magnitude, for example, are not typically found in our research papers.

For its part, the re/insurance industry has been slow to recognize the need to incorporate climate science. The argument has been that because contracts are written one year at a time, climate change can be priced as it happens. Thus, catastrophe models can continue to be closely based on the historical record without explicitly incorporating predictive climate science. To properly price climate risk, though, we have to detect and attribute the climate change signal in extreme weather. We cannot do that using history alone, because there’s too much “noise” from natural variability.

To understand how climate change is influencing losses, we need to untangle the climate change signal from the noise. Climate science gives us some tools, but we need to build more.

To represent climate change itself, we need earth system models, such as those in the ongoing Sixth Coupled Model Intercomparison Project (CMIP6). But those models generally do not well represent extreme weather events, so we need careful “downscaling” on their results. That means building catastrophe models that are climate-sensitive: include output from climate models that describe the changing climate and generate extreme weather events that are consistent with those changes. For these models to be credible, they should be based on open, peer-reviewed research.

The science here is at the bleeding edge. The uncertainty involved is larger than what the industry is used to, but also a different type. Scientists in re/insurance will need to learn about climate sensitivity, multi-model ensembles, emissions scenarios, and other things outside of their past practices. At the same time, more scientists in academia and government need to understand the nature of risk, and why a lot of our work doesn’t address it. Particularly, much academic work does not focus tightly enough on extreme event probabilities.

The climate crisis demands a broad range of solutions. Re/insurance will play a critical role, but for it to fulfill its potential, both the underlying science and the way the industry uses that science needs to evolve. The best path forward is insurance, academia, and government working together to see past the blind spots and develop realistic climate scenario-based solutions.

About the Author

Adam Sobel is a professor at Columbia University’s Lamont-Doherty Earth Observatory and Engineering School. He studies the dynamics of climate and weather, particularly in the tropics. In recent years he has become particularly focused on understanding the risks to society from extreme weather events and climate change. He directs the Columbia Initiative on Extreme Weather and Climate. In recent years Sobel has received awards from the American Meteorological Society, the AXA Research Fund, and the American Geophysical Union. He is author or co-author of over 175 peer-reviewed scientific articles; a popular book, Storm Surge, about Hurricane Sandy; and numerous op-eds.