Insights

View of risk: Hurricane Irma wind field and post-event modeling reviewBy Ian Libby and Adam Miron

October 2017

In the wake of Hurricane Irma’s catastrophic impacts across the Caribbean and Southeastern United States, modeling agencies created wind field reconstructions for the purpose of estimating property loss. Through analyzing these loss estimates, it became evident that a better understanding of the uncertainties present in post-event modeling was desired. What are the reasons behind the discrepancies seen in “best estimates” of property loss, both for carrier-specific portfolios and the industry at large?

Wind field reconstructions reflect data recorded periodically over the life of the storm, such as maximum wind speed, transition speed and size. Due to limited available data, modeling agencies must rely on their scientific knowledge and judgment in creating their reconstructions. Examples of such judgment include handling limitations associated with the completeness and accuracy of the storm’s recorded parameters, representing the relative surface roughness surrounding a specific location, interpreting how wind speed decreases as the storm moves inland and interacts with land, making assumptions on how the storm may have interacted with other weather systems and deciding how to appropriately incorporate these judgments with available data points to produce a reconstruction of an event’s wind field. Amid these challenges, modeling companies can distinguish themselves by providing timely and reliable guidance to those impacted by the event.

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Insights | October 2017

Willis Re was provided event footprint reconstructions in the days following Irma’s dissipation from AIR Worldwide (AIR), Risk Management Solutions (RMS), Kinetic Analysis Corporation and KatRisk. Willis Re conducted an analysis contrasting the vendors’ reconstructions to get a perspective of variations in Irma’s modeled wind field, and to better understand the variances among the loss estimates produced. In comparing the wind footprints, there were considerable differences. In general, Kinetic Analysis estimated the highest wind speeds, KatRisk estimated the lowest; AIR and RMS fit between the extremes, with AIR generally estimating higher wind speeds than RMS. While all models recognized the extreme winds recorded in the Florida Keys, notable disparities were seen following the second landfall near Naples. Additional differences could also be seen in coastal areas, with higher wind speeds extending inland to varying degrees. Also of interest were estimated wind speeds on the periphery of the storm, with significant variations seen around the Tri-County and Jacksonville areas.

Differences in the post-event footprint combined with the distinct vulnerability curves present in each model can result in significant variances in loss estimates. As an example, Figure 1 shows total insured value (TIV) for a mock portfolio exposed to a hypothetical event. Model A shows a greater portion of TIV exposed to higher wind speeds where the modeled damage ratio is also higher. This combination of exposure and damage ratio would result in significantly higher loss generated from model A relative to model B in this hypothetical scenario.

The motivation for this analysis was to investigate the drastic ranges seen in portfolio-specific post-event loss estimates calculated through various vendor models. Irma provides a unique opportunity for model hazard and vulnerability validation by utilizing claims data, recorded wind speed observations, and a diversity of vendor model resources. The Willis Re View of Risk brings clarity and transparency to models through research, reports, tools and model adjustments. For a complete Irma hazard profile and claims analysis, please contact your Willis Re representative.

Contacts

For more information or to discuss our observations, please contact:

Ian Libby+1 813 490 6846ian.libby@willistowerswatson.com

Adam Miron+1 952 841 6689adam.miron@willistowerswatson.com

Figure 1. TIV for a mock portfolio exposed to a hypothetical event

Copyright © 2017 Willis Towers Watson. All rights reserved.WTW-NA-2017-17517

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