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1. 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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2. Historically unprecedented Northern Gulf of Mexico hurricane activity from 650 to 1250 CE

   https://doi.org/https://doi.org/10.1038/s41598-020-75874-0  

   Rodysill, J.; Donnelly, J.; Sullivan, R; Lane, P.; Toomey, M.; Woodruff, J.; Hawkes, A.; MacDonald, D.; D'Entremont, N.; McKeon, K.; et al (November 2020, Scientific reports)

   null (Ed.)

   Hurricane Michael (2018) was the first Category 5 storm on record to make landfall on the Florida panhandle since at least 1851 CE (Common Era), and it resulted in the loss of 59 lives and $25 billion in damages across the southeastern U.S. This event placed a spotlight on recent intense (exceeding Category 4 or 5 on the Saffir-Simpson Hurricane Wind Scale) hurricane landfalls, prompting questions about the natural range in variability of hurricane activity that the instrumental record is too short to address. Of particular interest is determining whether the frequency of recent intense hurricane landfalls in the northern Gulf of Mexico (GOM) is within or outside the natural range of intense hurricane activity prior to 1851 CE. In this study, we identify intense hurricane landfalls in northwest Florida during the past 2000 years based on coarse anomaly event detection from two coastal lacustrine sediment archives. We identified a historically unprecedented period of heightened storm activity common to four Florida panhandle localities from 650 to 1250 CE and a shift to a relatively quiescent storm climate in the GOM spanning the past six centuries. Our study provides long-term context for events like Hurricane Michael and suggests that the observational period 1851 CE to present may underrepresent the natural range in landfalling hurricane activity. 

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3. Rapid Intensification of Hurricane Ian (2022) in High Shear

   https://doi.org/10.1029/2024JD042024  

   Nickerson, Alexander K; Zhang, Jun A; Weisberg, Robert H; Liu, Yonggang (July 2025, Journal of Geophysical Research: Atmospheres)

   Abstract Initially a Category 3 storm, Hurricane Ian (2022) rapidly intensified on the West Florida Shelf reaching Category 5 over the course of about 12 hr. Intensification occurred despite inhibiting factors such as high axial tilt, high vertical wind shear, low atmospheric moisture, and transit over a relatively shallow continental shelf. Using a high‐resolution simulation of Hurricane Ian from the Hurricane Weather Research Forecasting (HWRF) model, we examine the factors that both hindered and supported rapid intensification (RI) by blending various methods. We show that an increase in diabatic heating in the eyewall led to an inward radial advection of momentum, seen in both the absolute angular momentum budget and in the azimuthal wind budget. Analysis of the moist static energy budget indicates that the substantial latent heat flux from the surface was enough to balance heat losses through storm outflow. For instance, surface latent heat fluxes exceeded 1,500 W m⁻²on the West Florida Continental Shelf. As suggested by actual ocean temperature observations that substantially exceeded those in the HWRF simulation, the latent heating may have even been larger. Physical explanations for discrepancies between the simulated Hurricane Ian and observations are provided, particularly those pertaining to the coastal ocean at the time of Ian's passage. This research provides a comprehensive explanation of the RI of a hurricane using momentum budget analyses as part of a coupled air‐sea analysis. Our findings demonstrate the importance of in situ oceanic air‐sea measurements in evaluating the performance of coupled models, especially for hurricanes. 

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4. Acute Impacts of Hurricane Ian on Benthic Habitats, Water Quality, and Microbial Community Composition on the Southwest Florida Shelf

   https://doi.org/10.3390/coasts5020016  

   Tillman, Matthew Cole; Smith, Robert Marlin; Tubbs, Trevor R; Catasus, Adam B; Urakawa, Hidetoshi; Adhikari, Puspa L; Douglass, James G (June 2025, Coasts)

   Tropical cyclones can severely disturb shallow, continental shelf ecosystems, affecting habitat structure, diversity, and ecosystem services. This study examines the impacts of Hurricane Ian on the Southwest Florida Shelf by assessing water quality, substrate type, and epibenthic and microbial community characteristics at eight sites (3 to 20 m in depth) before and after Ian’s passage in 2022. Hurricane Ian drastically changed substrate type and biotic cover, scouring away epibenthos and/or burying hard substrates in mud and sand, especially at mid depth (10 m) sites (92–98% loss). Following Hurricane Ian, the greatest losses were observed in fleshy macroalgae (58%), calcareous green algae (100%), seagrass (100%), sessile invertebrates (77%), and stony coral communities (71%), while soft coral (17%) and sponge communities (45%) were more resistant. After Ian, turbidity, chromophoric dissolved organic matter, and dissolved inorganic nitrogen and phosphorus increased at most sites, while total nitrogen, total phosphorus, and silica decreased. Microbial communities changed significantly post Ian, with estuary-associated taxa expanding further offshore. The results show that the shelf ecosystem is highly susceptible to disturbances from waves, deposition and erosion, and water quality changes caused by mixing and coastal discharge. More routine monitoring of this environment is necessary to understand the long-term patterns of these disturbances, their interactions, and how they influence the resilience and recovery processes of shelf ecosystems. 

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5. Space-Based Mapping of Pre- and Post-Hurricane Mangrove Canopy Heights Using Machine Learning with Multi-Sensor Observations

   https://doi.org/10.3390/rs16213992  

   Zhang, Boya; Gann, Daniel; Wdowinski, Shimon; Lin, Chaohao; Hestir, Erin; Lamb-Wotton, Lukas; Ishtiaq, Khandker S; Smith, Kaleb; Li, Yuepeng (November 2024, Remote Sensing)

   Coastal mangrove forests provide numerous ecosystem services, which can be disrupted by natural disturbances, mainly hurricanes. Canopy height (CH) is a key parameter for estimating carbon storage. Airborne Light Detection and Ranging (LiDAR) is widely viewed as the most accurate method for estimating CH but data are often limited in spatial coverage and are not readily available for rapid impact assessment after hurricane events. Hence, we evaluated the use of systematically acquired space-based Synthetic Aperture Radar (SAR) and optical observations with airborne LiDAR to predict CH across expansive mangrove areas in South Florida that were severely impacted by Category 3 Hurricane Irma in 2017. We used pre- and post-Irma LiDAR-derived canopy height models (CHMs) to train Random Forest regression models that used features of Sentinel-1 SAR time series, Landsat-8 optical, and classified mangrove maps. We evaluated (1) spatial transfer learning to predict regional CH for both time periods and (2) temporal transfer learning coupled with species-specific error correction models to predict post-Irma CH using models trained by pre-Irma data. Model performance of SAR and optical data differed with time period and across height classes. For spatial transfer, SAR data models achieved higher accuracy than optical models for post-Irma, while the opposite was the case for the pre-Irma period. For temporal transfer, SAR models were more accurate for tall trees (>10 m) but optical models were more accurate for short trees. By fusing data of both sensors, spatial and temporal transfer learning achieved the root mean square errors (RMSEs) of 1.9 m and 1.7 m, respectively, for absolute CH. Predicted CH losses were comparable with LiDAR-derived reference values across height and species classes. Spatial and temporal transfer learning techniques applied to readily available spaceborne satellite data can enable conservation managers to assess the impacts of disturbances on regional coastal ecosystems efficiently and within a practical timeframe after a disturbance event. 

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