Boyko Dodov

New model framework coming from AIR can be used to evaluate climate change risk on short- and long-term time horizons.

For this fifth and penultimate article in our series, we lay out the framework for overcoming those limitations and arriving at a solution purpose-built for the catastrophe modeling community.

AIR is exploring and implementing machine learning-based approaches in a wide range of problems covering the spectrum of catastrophe modeling

This article is the fourth in a series about AIR's efforts to build a new generation of catastrophe models capable of providing a global view of all weather-related perils in a manner efficient from a technological point of view.

Numerical climate models help us better understand how weather & climate are related and how this relationship changes as Earth's surface temperatures rise.