The Next Sandy

As we have seen with recent events such as Hurricane Katrina, Hurricane Ike, and most recently Superstorm Sandy, coastal flood damage can be disproportionately large compared to wind damage.

See the recent RMS infographic on hurricanes, which highlights the risk of storm surge.

Following the flooding in Manhattan and along the New Jersey shores, Sandy highlighted the need for comprehensive, high-resolution coastal flood modeling solutions. Sandy also provided deeper insights into flood coverage terms and assumptions across various lines of business throughout the insurance industry.

With the anniversary of Superstorm Sandy (October 29) approaching, RMS identified which coastal cities may be hit with a major coastal flood event.

Using RiskLink 13.0, the latest version of our North Atlantic Hurricane model suite, RMS calculated the 100-year return period (RP) surge loss contribution (%) for 12 coastal central business districts, which ranged from Galveston to New York City.

Baltimore and Biloxi are at highest risk, driven by 100-year RP surge contributions of 61% and 51%, respectively, across all lines of business.

Believe it or not, cities like Miami and the Outer Banks in North Carolina exhibited some of the lowest risk against a major surge event, with 100-year RP contributions of 5% each.

Consistent across all high-risk cities:

• Located in fairly low-lying areas at or below sea level
• Close to shallow-sloping sea beds

These characteristics, among others like wind intensity and angle of landfall, effectively allow for surge to gradually build throughout an approaching storm and impact nearby coastal regions with little or no resistance.

In RiskLink 13.0, the RMS view of coastal flood risk remains up-to-date. With the core hazard modeling methodology in place since 2011, RMS has integrated the latest science, data, and industry development into the high-resolution (as high as 180 meters along coastlines and within regions of high exposure densities), hydrodynamic storm surge model from DHI known as MIKE 21.

The inclusion of these updates effectively reduces the uncertainty associated with surge hazard and loss, and ensures that the RMS coastal flood model continues to be the only credible model for quantifying surge risk accurately.

The market has taken notice. In July 2013, RMS was selected by First Mutual Transportation Authority to model the risk for the first ever storm surge catastrophe bond.

With these advancements and over 30,000 stochastic events that impact the U.S.  comes a deeper insight  into when and where the next major coastal flood event could occur. For instance, Superstorm Sandy surge losses contributed to 65% of total insured losses.

In RiskLink 13.0, there are over 3,000 stochastic events that do the same, which translates to an annual likelihood of about 10% across all U.S. hurricane states, based on long-term hurricane frequencies. This annual likelihood nearly triples in the Northeast (29%) and doubles in the Gulf (17%), the two regions at highest risk of experiencing the next Sandy-like event.

Similarly, given that a hurricane impacts the U.S., there is a 30% annual chance that the full insured surge loss will exceed $1 billion USD, and nearly a 14% chance that the same losses exceed $5 billion USD.

Regardless of when or where the next major surge event occurs the industry needs to have the right tools available in order to model the magnitude and severity of catastrophic storm surge accurately. For instance, coastal flood models such as MIKE 21 simulate surge characteristics throughout the lifetime of the event, not just at landfall, because it is well known that hurricanes with similar landfalling characteristics do not always produce the same surge risk.

Equally as important is the need for coastal flood models like MIKE 21 to be able to capture the localized nature of key geographical and geological features such as topography, land use, land cover, and bathymetry.

As the industry continues to gain a better understanding of their coastal flood risk landscape, especially on the local scale, RMS will continue to help by incorporating the latest available data and research into our model, investigating the underlying uncertainties and modeling challenges, and investing in future modeling capabilities.