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Jessica Weinkle, Ryan Maue, and Roger Pielke Jr


In recent decades, economic damage from tropical cyclones (TCs) around the world has increased dramatically. Scientific literature published to date finds that the increase in losses can be explained entirely by societal changes (such as increasing wealth, structures, population, etc.) in locations prone to tropical cyclone landfalls, rather than by changes in annual storm frequency or intensity. However, no homogenized dataset of global tropical cyclone landfalls has been created that might serve as a consistency check for such economic normalization studies. Using currently available historical TC best-track records, a global database focused on hurricane-force strength landfalls was constructed. The analysis does not indicate significant long-period global or individual basin trends in the frequency or intensity of landfalling TCs of minor or major hurricane strength. The evidence in this study provides strong support for the conclusion that increasing damage around the world during the past several decades can be explained entirely by increasing wealth in locations prone to TC landfalls, which adds confidence to the fidelity of economic normalization analyses.

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Kenneth Broad, Anthony Leiserowitz, Jessica Weinkle, and Marissa Steketee

This article reviews the evolution, communication, and differing interpretations of the National Hurricane Center's “cone of uncertainty” hurricane forecast graphic. It concludes with a discussion of this graphic from the perspective of risk communication theory. The 2004 hurricane season, in which five named storms struck Florida, demonstrated that hurricane forecast graphics, despite admirable attempts by the forecast community to make user-friendly products, are still subject to misinterpretation by many members of the public. This exploratory analysis draws upon interviews with key government officials and media figures, archival research of Florida newspapers, analysis of 962 public comments on the National Hurricane Center's cone of uncertainty graphic, a separate multiagency study of2004 hurricane behavior, and relevant risk communication literature, to identify several characteristics of this graphic that likely contribute to public misinterpretation. Forecast providers should consider more formal, rigorous pretesting of forecast graphics, using standard social science techniques, in order to minimize the probability of misinterpretation.

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