The April release of Risk Modeler 1.11 marks a major milestone in both model science and software. For the first time at RMS, a complete high-definition (HD) model – the RMS U.S. Inland Flood (USFL) HD model with integrated storm surge, and an accompanying model validation workflow are now available to all users on the new platform. It also marks the release of exciting new capabilities including auditable exposure edits and data access via third-party business intelligence and database tools.
What is Different About Model Validation on Risk Modeler?
For the USFL model to produce detailed insights into risk, it must realistically simulate the interactions between antecedent environmental conditions, event clustering, exposures, and insurance contracts over tens of thousands of possible timelines. That requires a new financial engine, a more powerful model execution engine, and a purpose-built database to handle the processing of and metrics calculation against the vast amounts of data that an HD model produces. Although the current RiskLink solution can perform some of these tasks and processes well and efficiently, Risk Modeler was especially built for these new requirements.
In addition to simply running this next-generation model, Risk Modeler has several features to quickly surface insights into the model and ultimately allow users to make business decisions faster.
From major wildfires just over four months ago, and now major flooding, Northern California seems to leap from one perilous state to another. This time, rainfall from a “potent atmospheric river”, as described by the National Weather Service, caused flooding to over 3,000 properties in Sonoma County. This atmospheric river – a flowing column of condensed water vapor pumped up from the Tropics which can be up to 375 miles (603 kilometers) wide – started delivering rain and snow into the region late on Sunday, February 24.
The small town of Guerneville (pop. ~4,500) fared worst, reporting nearly 21 inches (529 millimeters) of rainfall in just 72 hours by 5 p.m. local time on Wednesday, February 27. The source of the town’s flooding was the Russian River, which flows from Mendocino County through to Sonoma County, reaching a maximum level of 45.5 feet (13.9 meters) at Johnson’s Beach, near Guerneville. This exceeded the defined 40 feet (12.1 meters) threshold for a major flood at this point, with local media reports stating that this is the worst flooding since New Year’s Day in 1997, when the river rose to 45 feet (13.7 meters). The nearby Napa River also crested at 26 feet (7.92 meters), one foot above the flood stage.
The town of Guerneville, which was originally built on a meander in the river, on February 27 was declared by the Sonoma County Sheriff’s Office “… [as] officially an island …” as all roads in an out of the town were flooded. 4,000 residents in both Guerneville and Monte Rio (pop. ~1,200) were under evacuation orders until Friday, March 1.
In my recent article in Reactions entitled Why Long-term NFIP Reform is a Must, I looked back at the flood events of 2018 through the lens of the need to reform the National Flood Insurance Program (NFIP). I made the argument that the NFIP is not effectively covering communities at risk or supporting the development of a private market that support that same goal.
Looking at Hurricane Florence, its impacts exemplify the type of event from which our communities need to recover from by leveraging the NFIP and a more robust private market. Both North Carolina and South Carolina each broke records for the amount of rainfall caused by a tropical cyclone. While the flooding due to storm surge was significant in areas such as New Bern, the majority of the flood damage was driven by that record rainfall in the inland areas.
The areas most impacted had the lowest take-up rates for flood insurance – the take-up rate for NFIP policies is less than two percent in the inland counties of North Carolina and South Carolina, while take-up rates in most coastal counties generally range from 10 to 25 percent. As a result, RMS analysis found that Florence caused US$3 billion to US$6 billion in uninsured losses, or about 4-5 times the losses expected to be incurred by the NFIP.