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1. A Multivariate Frequency Analysis Framework to Estimate the Return Period of Hurricane Events Using Event‐Based Copula

   https://doi.org/10.1029/2023WR034786  

   Cho, Eunsaem; Ahmadisharaf, Ebrahim; Done, James; Yoo, Chulsang (December 2023, Water Resources Research)

   Abstract This study proposed a framework to evaluate multivariate return periods of hurricanes using event‐based frequency analysis techniques. The applicability of the proposed framework was demonstrated using point‐based and spatial analyses on a recent catastrophic event, Hurricane Ian. Univariate, bivariate, and trivariate frequency analyses were performed by applying generalized extreme value distribution and copula on annual maximum series of flood volume, peak discharge, total rainfall depth, maximum wind speed, wave height and storm surge. As a result of point‐based analyses, return periods of Hurricane Ian was investigated by using our framework; univariate return periods were estimated from 39.2 to 60.2 years, bivariate from 824.1 to 1,592.6 years, and trivariate from 332.1 to 1,722.9 years for the Daytona‐St. Augustine Basin. In the Florida Bay‐Florida Keys Basin, univariate return periods were calculated from 7.5 to 32.9 years, bivariate from 36.5 to 114.9 years, and trivariate from 25.0 to 214.8 years. Using the spatial analyses, we were able to generate the return period map of Hurricane Ian across Florida. Based on bivariate frequency analyses, 18% of hydrologic unit code 8 (HUC8) basins had an average return period of more than 30 years. Sources of uncertainty, due to the scarcity of analysis data, stationarity assumption and impact of other weather systems such as strong frontal passages, were also discussed. Despite these limitations, our framework and results will be valuable in disaster response and recovery. 

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2. Storm surge and ponding explain mangrove dieback in southwest Florida following Hurricane Irma

   https://doi.org/10.1038/s41467-021-24253-y  

   Lagomasino, David; Fatoyinbo, Temilola; Castañeda-Moya, Edward; Cook, Bruce D.; Montesano, Paul M.; Neigh, Christopher S. R.; Corp, Lawrence A.; Ott, Lesley E.; Chavez, Selena; Morton, Douglas C. (June 2021, Nature Communications)

   Abstract Mangroves buffer inland ecosystems from hurricane winds and storm surge. However, their ability to withstand harsh cyclone conditions depends on plant resilience traits and geomorphology. Using airborne lidar and satellite imagery collected before and after Hurricane Irma, we estimated that 62% of mangroves in southwest Florida suffered canopy damage, with largest impacts in tall forests (>10 m). Mangroves on well-drained sites (83%) resprouted new leaves within one year after the storm. By contrast, in poorly-drained inland sites, we detected one of the largest mangrove diebacks on record (10,760 ha), triggered by Irma. We found evidence that the combination of low elevation (median = 9.4 cm asl), storm surge water levels (>1.4 m above the ground surface), and hydrologic isolation drove coastal forest vulnerability and were independent of tree height or wind exposure. Our results indicated that storm surge and ponding caused dieback, not wind. Tidal restoration and hydrologic management in these vulnerable, low-lying coastal areas can reduce mangrove mortality and improve resilience to future cyclones. 

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3. High Resolution 3D Mapping of Hurricane Flooding from Moderate-Resolution Operational Satellites

   https://doi.org/10.3390/rs14215445  

   Li, Sanmei; Goldberg, Mitchell; Kalluri, Satya; Lindsey, Daniel T.; Sjoberg, Bill; Zhou, Lihang; Helfrich, Sean; Green, David; Borges, David; Yang, Tianshu; et al (November 2022, Remote Sensing)

   Floods are often associated with hurricanes making landfall. When tropical cyclones/hurricanes make landfall, they are usually accompanied by heavy rainfall and storm surges that inundate coastal areas. The worst natural disaster in the United States, in terms of loss of life and property damage, was caused by hurricane storm surges and their associated coastal flooding. To monitor coastal flooding in the areas affected by hurricanes, we used data from sensors aboard the operational Polar-orbiting and Geostationary Operational Environmental Satellites. This study aims to apply a downscaling model to recent severe coastal flooding events caused by hurricanes. To demonstrate how high-resolution 3D flood mapping can be made from moderate-resolution operational satellite observations, the downscaling model was applied to the catastrophic coastal flooding in Florida due to Hurricane Ian and in New Orleans due to Hurricanes Ida and Laura. The floodwater fraction data derived from the SNPP/NOAA-20 VIIRS (Visible Infrared Imaging Radiometer Suite) observations at the original 375 m resolution were input into the downscaling model to obtain 3D flooding information at 30 m resolution, including flooding extent, water surface level and water depth. Compared to a 2D flood extent map at the VIIRS’ original 375 m resolution, the downscaled 30 m floodwater depth maps, even when shown as 2D images, can provide more details about floodwater distribution, while 3D visualizations can demonstrate floodwater depth more clearly in relative to the terrain and provide a more direct perception of the inundation situations caused by hurricanes. The use of 3D visualization can help users clearly see floodwaters occurring over various types of terrain conditions, thus identifying a hazardous flood from non-hazardous flood types. Furthermore, 3D maps displaying floodwater depth may provide additional information for rescue efforts and damage assessments. The downscaling model can help enhance the capabilities of moderate-to-coarse resolution sensors, such as those used in operational weather satellites, flood detection and monitoring. 

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4. Multi‐hazard probabilistic risk assessment and equitable multi‐objective optimization of building retrofit strategies in hurricane‐vulnerable communities

   https://doi.org/10.1111/mice.13445  

   Braik, Abdullah M; Gupta, Himadri Sen; Koliou, Maria; González, Andrés D (June 2025, Computer-Aided Civil and Infrastructure Engineering)

   Abstract Coastal communities are increasingly vulnerable to hurricanes, which cause billions of dollars in damage annually through wind, storm surge, and flooding. Mitigation efforts are essential to reduce these impacts but face significant challenges, including uncertainties in hazard prediction, damage estimation, and recovery costs. Resource constraints and the disproportionate burden borne by socioeconomically vulnerable groups further complicate retrofitting strategies. This study presents a probabilistic methodology to assess and mitigate hurricane risks by integrating hazard analysis, building fragility, and economic loss assessment. The methodology prioritizes retrofitting strategies using a risk‐informed, equity‐focused approach. Multi‐objective optimization balances cost‐effectiveness and risk reduction while promoting fair resource allocation among socioeconomic groups. The novelty of this study lies in its direct integration of equity as an objective in resource allocation through multi‐objective optimization, its comprehensive consideration of multi‐hazard risks, its inclusion of both direct and indirect losses in cost assessments, and its use of probabilistic hazard analysis to incorporate varying time horizons. A case study of the Galveston testbed demonstrates the methodology's potential to minimize damage and foster equitable resilience. Analysis of budget scenarios and trade‐offs between cost and equity underscores the importance of comprehensive loss assessments and equity considerations in mitigation and resilience planning. Key findings highlight the varied effectiveness of retrofitting strategies across different budgets and time horizons, the necessity of addressing both direct and indirect losses, and the importance of multi‐hazard considerations for accurate risk assessments. Multi‐objective optimization underscores that equitable solutions are achievable even under constrained budgets. Beyond a certain point, achieving equity does not necessarily increase expected losses, demonstrating that more equitable solutions can be implemented without compromising overall cost‐effectiveness. 

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5. StEER: Field Assessment Structural Team (FAST) Dataset: Hurricane Ian

   https://doi.org/10.17603/ds2-f1p1-ev62  

   Ceferino, Luis; Faraone, Dylan; Gurley, Kurtis; Lynett, Patrick; Pinelli, Jean-Paul; Zdebski, Jaqueline; Roueche, David; Kijewski-Correa, Tracy; Cinar, Ezgi; Civello, Joey; et al (January 2025, Designsafe-CI)

   Eighteen years after Hurricane Charley made landfall in 2004, Hurricane Ian made landfall in nearly the same location, also as a Category 4 hurricane. Unlike Hurricane Charley (2004), water more so than wind was the impetus behind the disaster that unfolded. Despite being a below-design-level wind event, the large windfield drove a powerful storm surge as much as 13 ft high (relative to the NAVD8 vertical datum) in the barrier islands of Sanibel, Ft. Myers Beach, and Bonita Beach. Flooding was extensive along not only the Florida coast, but also well inland into low-lying areas as far north as Duval County and the storm’s second landfall site in South Carolina. As such, Hurricane Ian will likely be one of the costliest landfalling hurricanes of all time in the US, claiming over 100 lives. The impacts from Hurricane Ian were most severe in the barrier islands from the combination of storm surge and high winds, with many buildings completely washed away, and others left to deal with significant scour and eroded foundations. Several mobile/manufactured home parks on the barrier islands fared particularly poorly, offering little to no protection to anyone unfortunate enough to shelter in them. The damage was not restricted to buildings, as the causeways out to the barrier islands were washed away in multiple locations. In contrast, wind damage from Hurricane Ian appears less severe overall relative to other Category 4 storms, perhaps due to a combination of actual wind intensity being less than Category 4 at the surface at landfall, and the improvements in building construction that have occurred since Hurricane Charley struck 18 years earlier. It is notable that extensive losses were in part driven by decades-long construction boom of residential structures in Ft. Myers and Cape Coral since the 1950s and 1960s, expanding communities and neighborhoods encroaching upon vulnerable coastlines. Beyond serving as an important event to validate current and evolving standards for coastal construction, Hurricane Ian provides a clarion call to reconsider the ramifications of Florida's coastal development under changing climate. This project encompasses the products of StEER's response to this event: Preliminary Virtual Reconnaissance Report (PVRR), Early Access Reconnaissance Report (EARR) and Curated Dataset. 

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