Category Archives: Flood

An Award-Winning U.S. Inland Flood Model

It was off to London’s Savoy Hotel for members of the RMS London team last Thursday, for the Eleventh Trading Risk Awards. And apart from the great hospitality, and the flowing conversation from colleagues and industry peers alike, RMS was also recognized by the award judges, receiving the “Initiative of the Year” award for the RMS U.S. Inland Flood HD model.

Without sounding like an Oscar acceptance speech, on behalf of the team that worked on the model, I would like to thank the judging panel made up of representatives from the media and the industry for selecting our entry. Released last October, the flood model is designed to help the private insurance market seize the opportunities presented by this peril, and to also ultimately help accelerate flood insurance take up in the U.S.

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The Value of Flood Protection: Quantifying the Benefits of Defenses Along U.K. Rivers

Whenever the U.K. is hit by major flooding, attention quickly turns to the performance of the nation’s flood defenses. Some defenses, such as London’s Thames Barrier, are regularly recognized for their vital role in protecting people and property. The value of other mitigation measures, however, has been frequently challenged, such as when defenses failed to prevent significant flooding in Cumbria during storm Desmond in 2015.

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Risk Modeler 1.11 Release: Accelerating Access to Powerful Insights From the RMS U.S. Inland Flood HD Model

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.

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Disaster Risk Reduction: Avoiding the Inevitable

While natural hazards are inevitable, their impact on any given community is not. This is the thrust of the #NoNaturalDisasters campaign.

There’s a truth behind the hashtag. Modern societies are increasingly capable of determining their resilience to natural hazards. We nowadays know enough to prevent extreme weather events from escalating into full-blown disasters. In developed nations, sophisticated forecasting systems, social media networks and engineering capabilities can make any weather-related death seem like pure bad luck.

So, if it’s all down to chance, no particular group in society should be at higher risk. The truth, however, is rather different.

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The All-Peril Cat Five

Why the Saffir-Simpson Hurricane Intensity Scale had five levels we don’t know. The digits on a hand? Better than three, but lower resolution than the dozen rungs for wind speeds or earthquake intensity? Whatever the reason it seems to work.

In the late 1960s, Herbert Saffir, a Florida building engineer, was sent by the United Nations to study the hurricane vulnerability of low-cost housing in the Caribbean. He realized something was needed to rank hurricane destructiveness. Saffir had some “Richter envy” from observing the ease with which seismologists now communicated with the public. In 1971, he contacted Robert Simpson, head of the National Hurricane Center to help link damage levels with wind speeds.

Seeing the opportunity to communicate evacuation warnings, Simpson also added details around the height of advancing storm surges. Better information was clearly needed, after the loss of life in Hurricane Camille on the Mississippi coast in 1969.

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European Floods and the Relationship with the North Atlantic Oscillation

Stefano Zanardo, Principal Modeler, RMS

Ludovico Nicotina, Senior Director – Modeling, RMS

Arno Hilberts, Vice President, Model Development, RMS

Steve Jewson, Scientific Research Consultant, RMS

The North Atlantic Oscillation (NAO) describes the fluctuations in the difference of atmospheric pressure at sea level between two semi-permanent centers of low and high pressure in the North Atlantic: the Icelandic Low and the Azores High. Fluctuations between these centers control the strength and direction of westerly winds and location of storm tracks across the North Atlantic.

Why is this important? The NAO signal is Europe’s dominant mode of climate variability and correlates highly with European precipitation patterns. Typically, when the NAO is positive – characterized by a higher than average pressure difference between low and high latitudes of the Northern Hemisphere, Northern Europe experiences strong westerly winds. This causes stormier and wetter than usual conditions in Northern Europe, while Southern Europe is drier and colder than usual.

In contrast, when the NAO is negative, Southern Europe experiences westerly winds and the meteorological pattern is somewhat opposite, with Southern Europe being generally wetter than average. The NAO is significantly stronger in winter than in the other seasons, therefore, most studies on the NAO focus on winter months, when the influence of the NAO on surface temperature and precipitation is highest.

When climate patterns result in changing prevailing conditions, such as increased storm activity and rainfall, it is important to understand their effect in relation to the severity of flood events – responsible for significant property damage, business disruption and loss of life in Europe. And there is a need to understand its ongoing impact as the climate and the distribution of exposures change over time.

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The Age of Innocence

Professor Ilan Noy holds a unique ”Chair in the Economics of Disasters” at the Victoria University of Wellington, New Zealand. He has proposed in a couple of research papers that instead of counting disaster deaths and economic costs, we should report the “expected life-years” lost, not only for human casualties but also for the life-years of work that will be required to repair all the damage to buildings and infrastructure.

The idea is based on the World Health Organization’s Disability Adjusted Life Years (DALYs) lost through disease and injury (WHO 2013). The motivation is to escape from the distortion introduced by measuring the impact of global disasters in dollars, as loss from the richest countries will always dominate this metric. Noy’s proposal converts injuries into life-years lost, based on how long it takes for the injured to return to complete health, while also factoring the degree of permanent disability multiplied by its duration. This is topped up by a “welfare reduction weight” for all those exposed to a disaster. The final component of the index attempts to capture how many years of human endeavor is lost to recovering the buildings and assets destroyed in the disaster.

There is plenty to argue over in terms of how deaths, injury and damage should be combined. In particular, the assumption that additional work to rebuild a city, is the same as a shortened life, seems somewhat reductive.

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Northern California: Fire and Water

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.

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Townsville in the Trough

Two people died and thousands of properties in the North Queensland coastal city of Townsville (pop. ~168,000) have been flooded, following an unprecedented rainfall event for the region, driven by a very active monsoon trough that is refusing to budge and a slow-moving tropical low dragging moist air down from the equator.

According to the Australian Government Bureau of Meteorology (BoM), Townsville has experienced record rainfall, with 1,153 millimeters (45 inches) – equivalent to a year’s worth of rainfall, falling over a seven-day period up to Monday, February 4.

To add to the city’s problems, on Sunday, February 3, the Ross River Dam at the mouth of Lake Ross, just five miles (eight kilometers) from the center of Townsville, reached 247 percent of its typical capacity, and a record-breaking height of 42.99 meters. With the river running through the city, the dam’s flood gates were opened allowing 1,900 cubic meters of water per second to flow downstream in order to prevent catastrophic dam collapse. Local authorities suggested this could have affected up to 2,000 homes in Townsville. More heavy rain is still forecast for the next few days and while the rainfall rate has eased the event is not over yet.

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Why Long-term NFIP Reform Is a Must

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.

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