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With the release of the Version 21 (V21) updates to the RMS® North Atlantic Hurricane Models this summer, clients will be able to apply to their business the most current view of hurricane risk and market conditions throughout the North Atlantic Basin. This update incorporates new data and learnings from recent impactful seasons, including over US$6 billion of new claims data and insight, as well as the latest statistics on recent hurricane activity in the basin. RMS will also be the first model vendor to introduce a new view of Florida residential vulnerability that incorporates a range of impactful claims signals.

A new separately licensed Climate Change Model for the North Atlantic Hurricane Models V21 will also be released in June. It will enable clients to quantify the near- and long-term financial impact of climate change on wind risk from the North Atlantic Hurricane Models across multiple Representative Concentration Pathway scenarios up to the year 2100. Lastly, Version 21 includes updates to each component of the model, including both our long-term rates (LTR) and medium-term rates (MTR), which I am excited to discuss in this blog.

Hurricane Irma
Image: Satellite imagery of Hurricane Irma approaching the Caribbean in September 2017 - visualization using NASA satellite data. Source: Adobe Stock

How Do Event Rates Impact My Model Runs?

With 30 named storms formed during the 2020 season and 12 of them making landfall in the U.S., last year was the most active Atlantic hurricane season on record and the fifth consecutive season with above-average activity. Thankfully, insured losses were limited due to most landfalling hurricanes missing major exposure centers.

Still, it has reinvigorated discussions about the state of the Atlantic Basin and the overall hurricane risk landscape relative to the long-term average, to what extent it could be changing due to climate change or natural climate variability, and how these perspectives are reflected within catastrophe models.

Historically, the number of hurricanes in the Atlantic Basin has exhibited significant variability within and across decades. Debate continues around whether variability is driven by the complex interplay of atmospheric and oceanic climate variability, or climate change. Many scientists suggest a combination of both. So, how to account for long-term cycles as well as the changing near-term reality?

To capture this complexity while giving our clients the flexibility to select a view of risk that best aligns with their own, the RMS North Atlantic Hurricane Models include both a historical, long-term, perspective and a forward-looking, medium-term perspective on hurricane occurrence. As is common among catastrophe models, our long-term rates (LTR) represent the historical average of hurricane landfalls since 1900.

Since 2006, RMS is the only model vendor that also offers a medium-term rate (MTR) forecast, which gives a rolling five-year forecast of future activity. To inform both perspectives, in the North Atlantic Hurricane Models V21 we have incorporated new data on hurricane activity from recent impactful seasons, including storms such as Hurricanes Harvey, Irma, Florence, and Michael from 2017-2018.

Long-Term Rates (LTR) in Version 21

The changes to the LTR within Version 21 primarily reflect updates to the HURDAT2 dataset – the official historical record of hurricane activity provided by the National Hurricane Center (NHC) – as available in July 2019. This vintage of HURDAT2 introduces two new seasons (2017–18) of hurricane landfall and intensity data, as compared to Version 18.1.

The updated rates yield overall increases in landfall rates in the U.S. whole, but the exact direction and magnitude of rate change varies by U.S. region. Generally, if a U.S. region was impacted by a landfalling hurricane from the 2017-2018 seasons, it exhibits long-term rate increases in Version 21. Outside of the U.S., landfall rates increase in Mexico due to the impacts of Hurricanes Franklin (2017) and Katia (2017), and many Caribbean regions, such as the Antilles, Puerto Rico, Bahamas, and Turks and Caicos, due to Hurricanes Irma (2017) and Maria (2017). Rates remain stable or decrease for other non-U.S. regions and territories.

Medium-Term Rates (MTR) in Version 21

Where the LTR give a long-term historical average, the MTR provide a five-year forecast of future event frequency based on the current state of the Atlantic Basin and near-term climate trends. To best capture the five-year view, the MTR framework incorporates the latest-available data on hurricane activity, including historical and projected sea surface temperatures (SST) as well as published scientific theories on the physical drivers of multidecadal hurricane variability observed throughout the historical record.

Version 21 includes a new default MTR forecast for all Atlantic hurricane regions, covering the 2021 to 2025 period. This new forecast includes hurricane intensity and landfall data from two additional seasons (2019–20), updated historical SST data in areas of the Atlantic and Indo-Pacific regions, and updated forecast SST models projections for Atlantic and Indo-Pacific temperatures between 2021 and 2025 to align with the MTR forecast period. RMS is the only model vendor to provide a view of event frequency informed by the 2020 hurricane season.

These scientific theories are incorporated into thirteen statistical rate models, each generating a five-year hurricane activity forecast. The final near-term forecast of hurricane frequency is a weighted combination of all the underlying rate models based on their predictive skill in hindcasting portions of the historical record.

When combining the thirteen contributing rate models to provide the overall MTR forecast, RMS weights models according to their skill in predicting historical landfall rates. In Version 21, the resulting rate model combination yields higher landfall rates relative to the Version 18.1 forecast. As a result, the Version 21 MTR forecast increases in all North Atlantic regions, largely driven by the rate model updates informed by the incorporation of new data from 2019 to 2020.

Providing Flexibility for Views of Risk

Hurricane models strive to reflect the current risk landscape as effectively as possible, and event frequency is a critical component underpinning that framework. Relying on the stable, long-term view to quantify future risk has the advantage of simplicity, but the forward-looking, medium-term view provides a clear understanding of the relationship between perceived and actual risk.

Our long-term rates provide a view that is common in the insurance industry and critical for rate filing in U.S. states that mandate the use of a historical perspective. The RMS medium-term rates reflect the current state of the Atlantic Basin and its impact on near-term event frequency, giving clients a better understanding of future risk in a changing world.

Providing both options in the RMS North Atlantic Hurricane Models gives users the flexibility to stress test, compare, and ultimately select a view of event frequency that best aligns with their view of risk or their specific business application. For more information, please contact your client success representative or email sales@rms.com.

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jeff waters
Jeff Waters
Meteorologist and Senior Product Manager, Global Climate, RMS

Jeff Waters is a meteorologist who specializes in tropical meteorology, climatology, and general atmospheric science. At RMS, Jeff is responsible for guiding the insurance market’s understanding and usage of RMS models including the North American hurricane, severe convective storm, earthquake, winter storm, and terrorism models. In his role he assists the development of RMS model release communications and strategies, and regularly interacts with rating agencies and regulators around RMS model releases, updates, and general model best practices.

Jeff is a member of the American Meteorological Society, the International Society of Catastrophe Managers, and the U.S. Reinsurance Under 40s Group, and has co-authored articles for the Journal of Climate. Jeff holds a bachelor's degree in geography and meteorology from Ohio University and an masters in meteorology from Penn State University. His academic achievements have been recognized by the National Oceanic and Atmospheric Administration (NOAA) and the American Meteorological Society.

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