Open-Source Hurricane Wind Swaths for U.S. Climate Change Risk Assessment

With global warming, catastrophe modeling increasingly needs to evolve from considering a stationary to a non-stationary climate. Tropical cyclones (called hurricanes in the North Atlantic) are key to consider in this context, as they are some of the most costly natural disasters with impacts generally expected to worsen with climate change. Unfortunately, most datasets that exist to facilitate the climate-conditioned assessment of hurricane risk are proprietary and rely on methods that are not open-source. This poses challenges for entities, whether in the private or public sector, that are interested in quantitatively considering the impacts of hurricanes in a changing climate on their practices, but may not be ready or able to invest in a proprietary dataset. It also hampers scientific dialogue regarding hurricane risk assessment methods. To take a step towards resolving these issues, here we document a new open-source dataset of climate-conditioned hurricane wind swaths, available through the openly accessible Oasis Loss Modeling Framework platform. This dataset is composed of ~64k wind swaths from hurricanes that make landfall on or nearly miss the Continental United States. Tracks are downscaled from six different climate models using the Columbia tropical cyclone hazard model (CHAZ) for both recent historical and end-of-21st-century time periods. We provide initial analysis of both changing return levels for wind and economic impacts using openly available exposure data (LitPop) and a simplified representation of vulnerability. Results demonstrate general increases in extreme wind speeds and associated losses in the coastal United States with climate change. However, uncertainty amongst the 6 climate models is large, highlighting the need for further dialogue between climate researchers and catastrophe modelers about appropriate consideration of climate model structural uncertainty in tropical cyclone risk analysis.