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Michael C. Kruk, Ethan J. Gibney, David H. Levinson, and Michael Squires

Abstract

Tropical cyclones pose a significant threat to life and property along coastal regions of the United States. As these systems move inland and dissipate, they can also pose a threat to life and property, through heavy rains, high winds, and other severe weather such as tornadoes. While many studies have focused on the impacts from tropical cyclones on coastal counties of the United States, this study goes beyond the coast and examines the impacts caused by tropical cyclones on inland locations. Using geographical information system software, historical track data are used in conjunction with the radial maximum extent of the maximum sustained winds at 34-, 50-, and 64-kt (1 kt ≈ 0.5 m s−1) thresholds for all intensities of tropical cyclones and overlaid on a 30-km equal-area grid that covers the eastern half of the United States. The result is a series of maps with frequency distributions and an estimation of return intervals for inland tropical storm– and hurricane-force winds. Knowing where the climatologically favored areas are for tropical cyclones, combined with a climatological expectation of the inland penetration frequency of these storms, can be of tremendous value to forecasters, emergency managers, and the public.

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Philip J. Klotzbach, Michael M. Bell, Steven G. Bowen, Ethan J. Gibney, Kenneth R. Knapp, and Carl J. Schreck III

Abstract

Atlantic hurricane seasons have a long history of causing significant financial impacts, with Harvey, Irma, Maria, Florence, and Michael combining to incur more than 345 billion USD in direct economic damage during 2017–2018. While Michael’s damage was primarily wind and storm surge-driven, Florence’s and Harvey’s damage was predominantly rainfall and inland flood-driven. Several revised scales have been proposed to replace the Saffir–Simpson Hurricane Wind Scale (SSHWS), which currently only categorizes the hurricane wind threat, while not explicitly handling the totality of storm impacts including storm surge and rainfall. However, most of these newly-proposed scales are not easily calculated in real-time, nor can they be reliably calculated historically. In particular, they depend on storm wind radii, which remain very uncertain. Herein, we analyze the relationship between normalized historical damage caused by continental United States (CONUS) landfalling hurricanes from 1900–2018 with both maximum sustained wind speed (V max) and minimum sea level pressure (MSLP). We show that MSLP is a more skillful predictor of normalized damage than V max, with a significantly higher rank correlation between normalized damage and MSLP (r rank = 0.77) than between normalized damage and V max (r rank = 0.66) for all CONUS landfalling hurricanes. MSLP has served as a much better predictor of hurricane damage in recent years than V max, with large hurricanes such as Ike (2008) and Sandy (2012) causing much more damage than anticipated from their SSHWS ranking. MSLP is also a more accurately-measured quantity than is V max, making it an ideal quantity for evaluating a hurricane’s potential damage.

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Edward N. Rappaport, James L. Franklin, Andrea B. Schumacher, Mark DeMaria, Lynn K. Shay, and Ethan J. Gibney

Abstract

Tropical cyclone intensity change remains a forecasting challenge with important implications for such vulnerable areas as the U.S. coast along the Gulf of Mexico. Analysis of 1979–2008 Gulf tropical cyclones during their final two days before U.S. landfall identifies patterns of behavior that are of interest to operational forecasters and researchers. Tropical storms and depressions strengthened on average by about 7 kt for every 12 h over the Gulf, except for little change during their final 12 h before landfall. Hurricanes underwent a different systematic evolution. In the net, category 1–2 hurricanes strengthened, while category 3–5 hurricanes weakened such that tropical cyclones approach the threshold of major hurricane status by U.S. landfall. This behavior can be partially explained by consideration of the maximum potential intensity modified by the environmental vertical wind shear and hurricane-induced sea surface temperature reduction near the storm center associated with relatively low oceanic heat content levels. Linear least squares regression equations based on initial intensity and time to landfall explain at least half the variance of the hurricane intensity change. Applied retrospectively, these simple equations yield relatively small forecast errors and biases for hurricanes. Characteristics of most of the significant outliers are explained and found to be identifiable a priori for hurricanes, suggesting that forecasters can adjust their forecast procedures accordingly.

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Philip J. Klotzbach, Carl J. Schreck III, Gilbert P. Compo, Steven G. Bowen, Ethan J. Gibney, Eric C. J. Oliver, and Michael M. Bell

Capsule Summary

The 1933 Atlantic hurricane season was extremely active, generating the most Accumulated Cyclone Energy on record. The season would have been well anticipated using current statistical seasonal forecasting models.

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