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LiveCyc study links neighborhood forecasting to pre-hurricane payouts
The study reconstructs LiveCyc outputs ahead of 16 U.S. hurricanes from 2017 to 2024, finding 87% of surface wind gust observations fell within the model’s 90% confidence interval at the Day-2 decision window.
Artemis reports on a new study co-authored by Reask and researchers from the US Naval Research Laboratory and NOAA, published in the Bulletin of the American Meteorological Society, that aims to reduce basis risk in parametric insurance by funding protective actions before a hurricane makes landfall.
The paper introduces LiveCyc, a probabilistic forecasting system that converts any agency forecast into a wind distribution at 1-kilometer resolution for a specific neighborhood. To test underwriting reliability for automated payouts, researchers back-tested the system ahead of 16 major U.S. landfalls between 2017 and 2024, including Hurricanes Laura, Michael, Ian, Ida, and Milton, using real-time NHC forecasts and validating against 1,840 surface wind gust observations.
At the Day-2 decision window, 30 to 48 hours before landfall, the study says 87% of observations fell within the modeled 90% confidence interval, alongside a median bias of 0.5 kt and a Continuous Ranked Probability Score of 7.5 kt.
Reask said the system can reliably generate 1,000 realizations at the 1-kilometer scale, providing the mathematical foundation for automated pre-landfall parametric triggers. The paper also outlines how the trigger can be tuned to the cost of action, illustrating two scenarios tied to the US Navy’s Tropical Cyclone Conditions of Readiness framework, with evacuating non-essential personnel shown to pay off at an 8% chance of exceeding 60 kt, while holding a ship sortie until that chance reaches 33%.