Hurricanes are getting wetter, slower, and stronger. In 2017, Hurricane Harvey dumped 60 inches of rain on Houston, TX. It was the most extreme rain event in US history. Just last year, Hurricane Ian produced 1-in-1,000 year rainfall.
This precipitation is driving extreme flood damage in areas that are largely uninsured against flood risk, and unprepared for the economic fallout:
- Hurricane Ian: $17b in uninsured flood loss; 82% of homes uninsured
- Hurricane Harvey: $25b in uninsured flood loss; 70% of homes uninsured
- Hurricane Irma: $20b-$30b in uninsured flood loss; 80% of homes uninsured
The NFIP can’t address this protection gap on its own. We need more, and more efficient, flood insurance.
Floodbase provides an end-to-end data solution for enabling parametric flood insurance. Parametric insurance can offer corporations and residential portfolios broader protection against business interruption as well as physical flood damage.
Today we’re excited to announce a new solution on our platform specifically for supplementing parametric wind covers with flood protection, enabling broader parametric hurricane insurance. This solution is powered by our newest technology, which fuses our earth observation-based flood data with hydrologic inputs to map floods every hour. This solution is now available for parametric hurricane policies in the United States.
How it works
The insurance market has broadened coverage for hurricanes through parametric wind cover. However, the most economically impactful hurricanes are often not covered by parametric schemes that are structured using only wind intensity and wind speed from the insured location because the most damage is driven by flooding, not wind.
Notably, Hurricane Harvey, which caused 125 billion USD of damage in Houston and its surrounding areas; and is the second most economically impactful storm in history, did not have high wind-speeds and passed more than 100 miles away from Houston.
Floodbase’s data platform provides flooded area estimates as frequently as every 3 hours in the continental United States. Over 40 years of historical data further allows Floodbase to be used for developing a parametric flood index based on actual historical events. This technology enables the addition of a flood layer atop existing parametric wind covers, making complete hurricane protection finally possible.
We do this by fusing meteorological, hydrologic, and environmental data with direct satellite observations using AI to estimate water extent maps, similar to those derived directly from satellite observations. This approach leverages the robustness and scalability of satellite observations and combines them with the spatial completeness of physically-based inundation models in order to produce gap-free flood maps as frequently as every 3 hours. This in turn, enables us to produce flood maps like the ones we made for the floods in California for each day from December 25th, 2022 to January 15th, 2023 , where we estimate daily flooding over huge swaths of land.
To build a parametric flood index, we use probability distributions to estimate return periods with historical, rather than simulated data. Using 43 years of history, we back-test thresholds against historical data and iterate on threshold selection until the payout history matches the expected loss of the policy, as in the figure below.
When monitoring an area, the model runs automatically in near-real time. The estimated flooded area within the policy area is automatically compared to the predetermined thresholds, and alerts are sent out when thresholds are exceeded.
We are excited to put this solution into that market as we prepare for another unpredictable hurricane season. To learn more about how you can work with Floodbase, contact our sales team, or send a note to firstname.lastname@example.org.