Hurricane Laura began as a disorganized tropical depression in August 2020. Early forecast guidance showed that the tropical cyclone could either completely dissipate or strengthen to a major hurricane as it approached the United States Gulf Coast. While this uncertainty was known by meteorologists, it was not necessarily communicated to the public in a direct manner. As it turned out, the worst-case scenario was the correct one. The tropical depression rapidly intensified and made landfall near Cameron, Louisiana, with sustained winds of 150 mph, making Laura a Category 4 hurricane on the Saffir-Simpson scale. Laura's rapid intensification caught some people off guard. Ideally, weather forecasts would have begun warning Louisiana residents to prepare for the possibility of a devastating hurricane in the early stages of tropical cyclone development. No one is suggesting that meteorologists did anything wrong. However, with the benefit of hindsight and decades of scholarly research in risk communication, we can speculate how an ideal forecast would have been written. This paper demonstrates that there are some simple considerations that could be made that might better alert the public to future hurricane worst-case scenarios, even in uncertain situations.
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http://dx.doi.org/10.5055/jem.0817 | DOI Listing |
Nat Commun
January 2025
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, USA.
The upper ocean provides thermal energy to tropical cyclones. However, the impacts of the subsurface ocean on tropical cyclogenesis have been largely overlooked. Here, we show that the subsurface variabilities associated with the variation in the 26 °C isothermal depth have pronounced impacts on tropical cyclogenesis over global oceans.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Key Laboratory of Ocean Observation and Forecasting, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266000, China.
Tropical cyclones (TCs), particularly those that rapidly intensify (RI), pose a significant threat due to the uncertainty in forecasting them. RI TC periods, which intensify by at least 13 m/s within 24 h, remain challenging to forecast accurately. Existing models achieve a probability of detection (POD) of 82.
View Article and Find Full Text PDFPLoS Negl Trop Dis
January 2025
Institute of Exact and Applied Sciences, University of New Caledonia, Nouméa, Province Sud, New Caledonia.
Background: Leptospirosis is a neglected zoonotic disease prevalent worldwide, particularly in tropical regions experiencing frequent rainfall and severe cyclones, which are further aggravated by climate change. This bacterial zoonosis, caused by the Leptospira genus, can be transmitted through contaminated water and soil. The Pacific islands bear a high burden of leptospirosis, making it crucial to identify key factors influencing its distribution.
View Article and Find Full Text PDFEnviron Epidemiol
February 2025
Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Background: Tropical cyclones pose significant health risks and can trigger outbreaks of diarrheal diseases in affected populations. Although the effects of individual hazards, such as rainfall and flooding, on diarrheal diseases are well-documented, the complex multihazard nature of tropical cyclones is less thoroughly explored. To date, no dedicated review comprehensively examines the current evidence and research on the association between tropical cyclones and diarrheal diseases.
View Article and Find Full Text PDFSci Rep
January 2025
College of Ocean and Meteorology & South China Sea Institute of Marine Meteorology, Guangdong Ocean University, 524088, Zhanjiang, Guangdong, China.
Accurate classification of tropical cyclone (TC) tracks is essential for evaluating and mitigating the potential disaster risks associated with TCs. In this study, three commonly used methods (K-means, Fuzzy C-Means, and Self-Organizing Maps) are assessed for clustering historical TC tracks that originated in the South China Sea from 1949 to 2023. The results show that the K-means method performs the best, while the Fuzzy C-Means and Self-Organizing Maps methods are also viable alternatives.
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