The year 2020 is just months away, and in the latest edition of EXPOSURE — the RMS magazine for risk management professionals, we consider some of the changes that the (re)insurance industry will have undergone in ten years’ time. Mohsen Rahnama, Cihan Biyikoglu and Moe Khosravy from RMS tackle the issues, examining the evolution of risk management, the drivers of technological change, and how all roads lead to a common, collaborative industry platform.Continue reading
The first half of 2019 had been unusually quiet in the western North Pacific tropical cyclone basin. Following the dissipation of the strongest-ever February typhoon – Wutip, there were no subsequent typhoons until Francisco reached Category 1 strength on August 4. A few days later, Typhoon Lekima strengthened significantly on its approach towards the China coastline and then became the strongest landfalling storm of the year so far.
Lekima Enters the Record Books
Typhoon Lekima made landfall in Wenling City, Zhejiang Province (pop. ~1.3 million), at 1:45 a.m. local time on Saturday, August 10, with an intensity equivalent to a Category 3 hurricane on the Saffir-Simpson Hurricane Wind Scale according to the China Meteorological Administration (CMA). With two-minute sustained winds of 116 miles per hour (187 kilometers per hour) and a central pressure at landfall of 930 millibars, Lekima became the third strongest tropical cyclone to impact eastern China after Saomai in 2006 and Wanda in 1956.Continue reading
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.
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.
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.
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.
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.
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.
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.
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.