Hurricane Events Research Articles

Reliability-based retrofit assessment of coastal bridges subjected to wave forces using 3D CFD simulation and metamodeling

ABSTRACT This paper proposes a comprehensive analysis framework, combining three-dimensional (3D) numerical modelling and metamodeling, to investigate the probabilistic performance of retrofit actions on coastal bridges subjected to extreme wave forces. Specifically, a 3D Computational Fluid Dynamics (CFD) model is developed to calculate extreme wave load on the bridge superstructure. The established 3D model is validated by laboratory experiments. The characteristics of wave forces are parametrically investigated, and an Artificial Neural Network (ANN) metamodel is utilised to quantify the loading effects with multiple surge and wave parameters. Such a numerical-based ANN metamodel could predict wave forces under variable scenarios accurately, and significantly reduce the high computational cost of the 3D numerical model. Based on the numerical and metamodeling results, the bridge fragility curve is derived by considering uncertainties associated with structural demand, capacity, and hurricane hazard. Long-term failure risk is assessed under different climate change scenarios. Furthermore, different retrofit methods to improve structural performance and reduce failure risk are examined according to the proposed framework, including inserting air venting holes, enhancing connection strengths, and elevating bridge structures. The proposed framework could facilitate the optimal and robust design and maintenance of coastal infrastructures under hurricane effects in a long-term time interval.

Port resiliency and the effects of hurricanes on port operations

This paper studies the negative effects of hurricanes on port operations. Hurricanes push a large amount of sediment into the port and connecting channels, thus decreasing the water depth. As a result, larger vessels need extra time to de-ballast the water from the ballast tanks in order to reduce their draft and enter the port. Arena software is used to simulate port operations before and after a hurricane. The simulation study addresses how de-ballasting can affect the port key performance indicators. The model before a hurricane allows ships to enter the port, unload and load containers, and leave the port, while the after-hurricane model forces the large vessels to first empty their ballast tanks before entering the port. The simulation models are used to study the case of hurricane Harvey at the Port Houston. The results show that hurricanes have detrimental impacts on the port.

Port resiliency and the effects of hurricanes on port operations

This paper studies the negative effects of hurricanes on port operations. Hurricanes push a large amount of sediment into the port and connecting channels, thus decreasing the water depth. As a result, larger vessels need extra time to de-ballast the water from the ballast tanks in order to reduce their draft and enter the port. Arena software is used to simulate port operations before and after a hurricane. The simulation study addresses how de-ballasting can affect the port key performance indicators. The model before a hurricane allows ships to enter the port, unload and load containers, and leave the port, while the after-hurricane model forces the large vessels to first empty their ballast tanks before entering the port. The simulation models are used to study the case of hurricane Harvey at the Port Houston. The results show that hurricanes have detrimental impacts on the port.

Identifying State Dependence in Brand Choice: Evidence from Hurricanes

We analyze structural state dependence in brand choice using variation from brand switching during stock-outs caused by hurricanes. We derive a simple test for structural state dependence based on the time-series of choice persistence for households affected by the stock-outs that requires fewer assumptions than most previous work. Using data from the bottled water category, we show that demand increases substantially around hurricane events and causes households to purchase different brands. We find that purchase behavior reverts back to its pre-hurricane trajectory immediately after the hurricane and we are not able to reject the null hypothesis of no structural state dependence. We show that our results are not driven by unusual purchases during the hurricane or context-specific purchase behavior.

Simple method for identification of forest windthrows from Sentinel-1 SAR data incorporating PCA

Abstract We present outcomes from our experimental work towards identification of forest segments in Czech Jeseniky mountains damaged by a hurricane event on March 17, 2018. We have specifically processed Sentinel-1 satellite radar data and identified a functional methodology of extracting extents of the affected segments. The backscatter intensity of the damaged forest segments in Sentinel-1 images does not change significantly, subject to the sensitivity of the instrument. We have identified that a careful preprocessing of the data can lead to a state of possibility to identify edges of the affected areas in one of Principal Components (PC) generated from a set of dual-polarisation images before and after the event. In our case, these features were clearly visible in PC3 that was used in post-processing chain incorporating strong spatial filtering and edge detection routines. The identified damaged forest segments were validated by mapping during visiting one of the areas and by a comparison with multispectral satellite imagery, from data taken following year (as the damaged forest areas were already cleared and not regenerated). The approach can bring advantage in possibility of early preliminary mapping of the forest damages.

Computational fluid dynamic analysis of wind flow around Mangrove roots to reduce the damage due to heavy wind

• The wind flow around Pneumatophores Mangrove Roots of Avicennia Marina mangrove species. • CFD simulation and analysis of Incompressible and Compressible flow of air around the roots. • The wind flow around the Mangrove roots using numerical method. • The CFD analysis by the Finite volume method. • The wind speed reduces to more than 70% after the air flows through the mangrove roots. This research work aims at analyzing the wind flow around Pneumatophores Mangrove Roots of Avicennia Marina mangrove species to understand and visualize how the mangrove roots can reduce the speed of heavy wind and thereby play a prominent role in protecting the coast from the effects of cyclone, typhoons or hurricanes, mudslides and storm surges. Simulation and Analysis are performed with ANSYS Fluent software which employs Computational Fluid Dynamic (CFD) techniques. Wind speed during Extratropical storms and tropical cyclones is simulated using the flow of air with inlet velocities 75 km/hr., 250 km/hr. and 450 km/hr. Velocity, density and pressure at various locations are obtained to analyze the flow patterns. Results reveal that the presence of Mangrove roots reduces the wind speed by 70% of the initial speed of the wind. This data can be used in designing breakwater models as well as to improve the effectiveness of the existing ones.

Changes in coastal Gopher Tortoise (Gopherus polyphemus) burrow characteristics and density following hurricane events in Northeast Florida, USA: Implications for conservation planning

The Gopher Tortoise, Gopherus polyphemus is iconic, yet threatened throughout its range in the southeastern United States. It is a burrowing, herbivorous tortoise whose upland habitats have been greatly reduced by habitat destruction, fragmentation and/or reduction in quality due to anthropogenic changes in the disturbance regimes, such as fire, that are necessary to maintain quality habitat. Importantly, Gopher Tortoises are well documented keystone species supporting numerous conspecifics that are dependent upon or regularly use their burrows.While this species has been much studied in its inland habitats, it also thrives in coastal sand dune environments where little is known about its behavior, ecosystem role or conservation status. Coastal natural areas in the state of Florida, USA have been significantly reduced by human activity, and are now additionally threatened with accelerated sea level rise and more frequent and intense storms.We collected Gopher Tortoise burrow location, abundance, width and activity data in 2016 for a coastal population within northeast Florida, protected within the northern component of the Guana Tolomato Matanzas National Estuarine Research Reserve. Soon after our burrow survey was completed in 2016, Hurricane Matthew heavily impacted our study area that fall. In order to determine the degree to which this Gopher Tortoise population might have been impacted by the hurricane, we began re-surveying burrows in 2017 but were interrupted by another Hurricane, Irma, in 2017. We completed the post-hurricanes burrow surveys in 2018.When comparing pre-and post-hurricanes surveys, we found that habitat was lost and burrow density increased. The relative proportion of burrows categorized as “active” increased, while “inactive” and “abandoned” burrows decreased. Furthermore, burrow abundance decreased by 10% following these back-to-back hurricane events.We infer that individual Gopher Tortoises mostly abandoned low elevation burrows at risk of hurricane-related storm surge and relocated to higher elevation, unused (or “inactive” and “abandoned”) burrows. Such relocation, combined with significant loss of previously inhabited lower elevation habitat could explain the post-storm increase in burrow density and the proportional changes in burrow activity classification.However, as resilient as this population may be, it is running out of room due to sea level rise and habitat loss and fragmentation. Such implications for this and other species should be considered in conservation planning for coastal species of concern.

A PERFORMANCE-BASED COASTAL ENGINEERING FRAMEWORK

Coastal regions are exposed to both chronic and punctuated hazards, such as sea level rise and hurricane events, that can jeopardize entire coastal communities. Therefore, to effectively assess the risk and resilience of coastal communities subjected to multi-hazard environments, evaluation of the capacity of individual structures and infrastructure systems to withstand the different time-varying demands imposed in coastal settings is of paramount importance. This study proposes a comprehensive probabilistic framework for the design, risk and resilience assessment of coastal structures. The methodology also provides useful tools to inform decision-making, facilitate recovery efforts and improve resource allocation.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/8SI3Dw30yes

Hurricane effects on climate-adaptive silviculture treatments to longleaf pine woodland in southwestern Georgia, USA

Abstract The Adaptive Silviculture for Climate Change (ASCC) network tests silvicultural treatments to promote ‘resistance’ or ‘resilience’ to climate change or speed ‘transition’ to new forest types. Based on projected increases in air temperatures and within-season dry periods in southeastern USA, we installed resistance, resilience and transition treatments involving species selection and varied intensities of density reduction, plus an untreated control, in mixed longleaf pine-hardwood woodland in southwest Georgia USA. Within a year of treatment a tropical cyclone, Hurricane Michael, exposed the site to the unforeseen climatic stress of >44-m s−1 winds. We measured inventory plots post-cyclone and compared the data to pre-storm and pre-treatment values. We analysed stand density index (metric SDI, species maximum value = 1000), stand complexity index (SCI), composition and individual tree characteristics. The ASCC treatments decreased both SDI (from 220 to 124 in the transition treatment) and SCI. The cyclone did not greatly decrease SDI (mean decrease 4.5 per cent) and decreased SCI only in the Controls. Xeric hardwoods were more prone to damage than other functional groups, and ordination showed that the cyclone shifted species composition to greater longleaf pine dominance. Taller trees were more likely to be damaged, except in the resilience treatment, which had a relatively large representation of shorter, more easily damaged xeric hardwoods. The open canopy of the longleaf-hardwood woodland, only 22 per cent of maximum SDI before treatment, evidently fostered wind-firmness, thereby limiting the destructive effect of the cyclone. The sensitivity of xeric hardwoods to hurricane damage suggests that there may be a trade-off between wind tolerance and drought tolerance among functional groups. Maintaining a mixture of drought and wind-resistant species, as in the resilience treatments, may provide broader insurance against multiple climate change impacts in longleaf pine and other forested systems dominated by a single foundation species.

Role of Uncertainty and Social Networks on Shadow Evacuation and Non-Compliance Behavior in Hurricanes

Shadow evacuation and non-compliance are among undesirable behaviors during hurricane events. Based on a post-Hurricane Matthew household survey, this study aims to understand the combined effects of information source and uncertainty on individual-level evacuate–stay decisions from the Jacksonville, Florida metropolitan area. A random parameter logit model is developed to capture the heterogeneous effects among individuals. The combined effects are substantial and distinct in the two cases and the study reveals several significant findings. First, consistent and sufficient warning information leads to better alignment with recommended actions. Second, larger social networks encourage compliance and induce shadow evacuation. Third, a highly diverse network induces compliance with the recommended actions, and isolated individuals should be provided with more information. Fourth, risk information from traditional media should be clearly delineated between the high-risk and low-risk areas for effective compliance. However, information from social media has a nonsignificant effect.

Scrambling For Safety In The Eye Of Dorian: Mental Health Consequences Of Exposure To A Climate-Driven Hurricane.

As climate change alters the behavior of Atlantic hurricanes, these storms are trending stronger, wetter, and slower moving over coastal and island populations. Hurricane Dorian exemplified all three attributes. Dorian's destructive passage over the Abaco Islands, Bahamas, on September 1, 2019, exposed residents of its capital, Marsh Harbour, to a prolonged encounter with the storm's core. After Dorian's fierce front eyewall and towering storm surge tore apart shanty town habitats and eviscerated concrete homesites, residents desperately sought refuge during the brief respite when Dorian's eye passed directly overhead. The category 5 winds then resumed abruptly and Dorian continued its relentless destruction. This article focuses on the storm's mental health consequences, drawing on observations of on-site clinicians as well as findings from previous research on the mental health effects of Atlantic hurricanes and the transformation of hurricane hazards resulting from climate change. To protect island and coastal populations against climate-driven storms, disaster planning policy should emphasize resilience-focused prevention and mitigation strategies. In the aftermath of these events, health system response should include community outreach, case finding, and evidence-based interventions that optimize the use of mental health professionals.

Long-term healthcare provider availability following large-scale hurricanes: A difference-in-differences study.

Hurricanes Katrina and Sandy were two of the most significant disasters of the 21st century that critically impacted communities and the health of their residents. Despite the assumption that disasters affect access to healthcare, to our knowledge prior studies have not rigorously examined availability of healthcare providers following disasters. The objective of this study was to examine availability of healthcare providers following large-scale hurricanes. Using historical data on healthcare providers from the National Plan and Provider Enumeration System and county-level population characteristics, we conducted a quasi-experimental study to examine the effect of large-scale hurricanes on healthcare provider availability in the short-term and long-term. We separately examined availability of primary care physicians, medical specialists, surgeons, and nurse practitioners. A difference-in-differences analysis was used to control for time variant factors comparing county-level health care provider availability in affected and unaffected counties the year before Hurricanes Katrina and Sandy, to five years after each storm. Counties affected by Hurricane Katrina compared to unaffected locales experienced a decrease of 3.59 primary care physicians per 10,000 population (95% CI: -6.5, -0.7), medical specialists (decrease of 5.9 providers per 10,000 (95% CI: -11.3, -0.5)), and surgeons (decrease of 2.1 (95% CI: -3.8, -0.37)). However, availability of nurse practitioners did not change appreciably. Counties affected by Hurricane Sandy exhibited less pronounced changes. Changes in availability of primary care physicians, nurse practitioners, medical specialists, and surgeons were not statistically significant. Large-scale hurricanes appear to affect availability of healthcare providers for up to several years following impact of the storm. Effects vary depending on the characteristics of the community. Primary care physicians and medical specialists availability was the most impacted, potentially having long-term implications for population health in the context of disaster recovery.

Uncertainty Reduction Through Data Management in the Development, Validation, Calibration, and Operation of a Hurricane Vulnerability Model

Catastrophe models estimate risk at the intersection of hazard, exposure, and vulnerability. Each of these areas requires diverse sources of data, which are very often incomplete, inconsistent, or missing altogether. The poor quality of the data is a source of epistemic uncertainty, which affects the vulnerability models as well as the output of the catastrophe models. This article identifies the different sources of epistemic uncertainty in the data, and elaborates on strategies to reduce this uncertainty, in particular through identification, augmentation, and integration of the different types of data. The challenges are illustrated through the Florida Public Hurricane Loss Model (FPHLM), which estimates insured losses on residential buildings caused by hurricane events in Florida. To define the input exposure, and for model development, calibration, and validation purposes, the FPHLM teams accessed three main sources of data: county tax appraiser databases, National Flood Insurance Protection (NFIP) portfolios, and wind insurance portfolios. The data from these different sources were reformatted and processed, and the insurance databases were separately cross-referenced at the county level with tax appraiser databases. The FPHLM hazard teams assigned estimates of natural hazard intensity measure to each insurance claim. These efforts produced an integrated and more complete set of building descriptors for each policy in the NFIP and wind portfolios. The article describes the impact of these uncertainty reductions on the development and validation of the vulnerability models, and suggests avenues for data improvement. Lessons learned should be of interest to professionals involved in disaster risk assessment and management.

Regulation in the COVID-19 pandemic and post-pandemic times: day-watchman tackling the novel coronavirus

Purpose While fighting with the novel coronavirus will not be the main goal of sectoral regulators, different regulatory authorities join the struggle by providing a regulatory response. The purpose of this paper is to address this regulatory response in pandemic gathered around eight thematic areas. Design/methodology/approach This paper discusses the regulatory response in pandemic gathered around eight thematic areas, namely, the objectives, rules and standards, authorization and permits, procedure, monitoring and surveillance, enforcement, accountability and an institution presenting regulatory actions to tackle coronavirus (COVID-19) in reference to day-watchman type regulation. Findings Tackling the COVID-19 pandemic should be a knowledge-based approach (taking as much as possible from best available practices with respect to the novel coronavirus) with a framework of rules, standards, authorization, permits and guidance, monitored and enforced in a way adjusted to conditions of the pandemic, being as safe (as non-physical, as online) as possible, with suspended or extended deadlines, free of unnecessary administrative burdens. In this way, regulation should be pragmatic and flexible, as under the day-watchman model. Research limitations/implications In a post-pandemic regime, in the short run, the regulators should try to minimize the social and economic challenges faced by consumers and entrepreneurs. Among them, one may find scaling back, at least temporarily, the rules developed in non-disaster contexts. However, in the end, the post-disaster reforms tended to strengthen regulators’ hands, also under the deregulated government. The day-watchman type regulation balances both, as a middle ground approach, being a bridge between “a total subordination” and “a complete release.” Practical implications The disaster management (including public law regulation) provided by public authorities when tackling the effects of hurricanes, earthquakes or tsunamis can be a benchmark for regulatory responses to the COVID-19 pandemic. This concerns the support offered to entities and individuals affected by the negative consequences of reducing or stopping their businesses and staying in isolation. Social implications The day-watchman approach, visible in certain examples of public response to COVID-19 may serve as a framework for establishing a regulatory regime that would automatically take effect in case of another pandemic, limiting delays in regulatory actions, reducing non-compliance and accelerating recovery. Originality/value This study provides an analysis of different theories on public regulation addressing the notion of regulation using the day-watchman theory, which could be applied in regulatory actions during a pandemic. The paper discusses concrete steps taken by regulatory authorities worldwide, bringing examples from the USA, Canada, the UK, France, China, Japan, Australia and New Zealand. It juxtaposes the regulatory experiences derived from different catastrophes such as hurricanes, earthquakes or tsunamis with the regulatory response in a pandemic.

Projecting the effects of a warming climate on the hurricane hazard and insured losses: Methodology and case study

This paper summarizes research (conducted previously by the author) to incorporate (1) sea-surface temperature projections, (2) event-based hurricane simulation models, and (3) loss models to assess the impacts of the changing climate on the hurricane hazard and estimated insured losses. The focus of the work is on the US east coast and hence the formation and movement of hurricanes over the Atlantic Basin. As an illustrative case, the area around Charleston, South Carolina is considered. Specifically, this paper presents a methodology to probabilistically estimate regional hurricane loss considering both hurricane intensity and size as well as projected sea surface temperature change as a function of climate change.It is most common to characterize the hurricane wind hazard using a measure of intensity only. Recent studies have demonstrated the importance of accounting for storm size when characterizing the hurricane hazard in order to properly estimate/predict the spatial extent of damage. For purposes of regional loss estimation, therefore, considering maximum wind speed only may not be adequate. A storm with larger size but lower intensity might result in more damage and hence greater total loss than a smaller, more intense storm. Here, the maximum wind speed (intensity) and the radius of maximum winds (spatial extent) are selected as the two dominant indicators (parameters) characterizing the hurricane (event) hazard. The resulting bivariate hazard model is then used as input to a regional loss estimation model to illustrate its potential application. Only hurricane wind damage (and associated losses from both wind damage and water intrusion) is considered in this study. Collateral damage due to flood or storm surge is not addressed here.Simulated events impacting this region are extracted from a synthetic hurricane database (developed by the author and his colleagues) and the joint distribution of intensity and size is established to characterize the hurricane hazard. Regional loss for each simulated hurricane event is then estimated using the loss estimation module in HAZUS_MH. Finally, distributions of regional loss at different (event) hazard levels are generated.A future climate scenario (increasing sea surface temperature) is next considered and the joint distribution of hurricane intensity and size and the resulting loss distribution curve is recomputed. The results are then able to be compared to those under the current climate scenario. Such comparisons can help to inform codes and standards committees, for example, as they consider whether and how to take potential climate change impacts (in the design lifetime) into account. They also can inform ongoing public discourse around mitigation and adaptation, whether hardening of buildings and other infrastructure systems, community resilience planning, construction practices, or related policies.

Hurricanes and Gasoline Price Gouging

Conventional wisdom suggests that gasoline price gouging before and after natural disasters is widespread. To explore this conjecture, we compile data on more than 4.7 million daily station-level retail gasoline prices. We combine these data with information on wholesale rack prices, spot prices, hurricane threats and landfalls, weather, traffic, and power outages. We investigate the effect of hurricanes on retail prices, wholesale prices, retailer margins, fuel price pass-through, and share of stations reporting transactions. We exploit the fact that the exact timing and location of hurricane landfalls is conditionally exogenous for identification. We find no evidence for widespread price gouging. Instead, we document evidence consistent with shortages predicted by theory in the presence of restrictions on price movements.

Hurricane Hazard Assessment Along the United States Northeastern Coast: Surface Wind and Rain Fields Under Changing Climate

Surface wind and rain fields are two significant elements of hurricane-induced hazards in coastal areas. Mitigation of losses due to hurricane wind and rain hazards has become an increasing urgent and challenging issue in light of changing climate and continued escalation of coastal population density, prompting the need for a more advanced risk analysis methodology to take global warming effects into consideration. In this study, the assessment of hurricane surface wind and rain hazards under changing climate is achieved by performing three simulation components, namely an enhanced hurricane track model to generate the synthesized storms (including a physics-based intensity model integrating sea surface temperature (SST), wind shear, and convective instability contributions), a newly developed thermal wind balance-based model to simulate the gradient wind profiles (explicitly considering environmental conditions of SST, temperature at the top of atmospheric boundary layer, and outflow temperature), and a height-resolving boundary-layer model to obtain the surface wind and rain fields (reducing inherent uncertainties associated with conventionally used gradient-to-surface wind speed conversion factors). A total of 10,000 years of hurricane events are generated for both observed (historical) and projected climate conditions, and a systematical comparison between these two scenarios is investigated. The simulation and comparison results highlight the important effects of a global warming scenario on hurricane surface wind and rain fields, and hence on critical civil infrastructure in hurricane-prone areas.

Hurricane-related health impacts and modification by community resilience

Background: The public health impacts of hurricanes and floods are significant. While the death toll from hurricanes and floods has climbed in recent years, mortality, alone, is a poor indicator of human impacts. Official death counts are known to be an underestimate, and mortality from direct exposure to a hurricane event is just the tip of the iceberg for public health impacts. Few studies have quantified excess morbidity across a range of outcomes from hurricane events. Further, little is known about community factors that may mitigate the health impacts of hurricanes.Methods: Emergency department (ED) visit data for New Jersey communities impacted by Hurricane Sandy was obtained from the Healthcare Cost and Utilization Project. A two-stage Bayesian hierarchical model was used to estimate the increase in risk for respiratory, cardiovascular, and renal cause visits due to Hurricane Sandy. We examined how community-level resilience characteristic modified this association, after adjusting for storm severity.Results: In the months following the storm, there was an increase in ED visits for all causes we examined, ranging from 5.6% (95% PI: 3.0, 8.4) for chronic renal disease to 18.9% (95% PI: 15.9, 22.0) for chronic obstructive pulmonary disease (COPD). The effect of the storm on ED visits decreased by 3.1% (95% PI: 1.1, 5.0) for COPD and by 3.0% (95% PI: 0.6, 5.3) for chronic renal disease for a standard deviation increase in community resilience. Social and environmental domains of resilience drove this association.Conclusions: Severe hurricane events are associated with excess morbidity risk across a wide range of causes. Community-level resilience measures explain some spatial variation in health impacts due to extreme weather events. Increasing community resilience has the potential to mitigate health impacts from hurricanes, reduce healthcare utilization, and result in healthcare cost reductions.

Semi-analytical solution for gable roofs under uplift wind loads

A common type of failure observed during hurricane events is the detachment of the roofs of light-frame wood houses because of the inability of the roof-to-wall connection (RTWC) to transfer uplift wind loads acting on the roofs. This paper introduces a computationally efficient procedure for conducting nonlinear analysis of the roofs to determine the connections forces using a semi-analytical solution. The new procedure simulates an entire roof as a continuous beam resting on elastic supports through the use of statically indeterminate slope deflection equations that include shear deformations. It accounts for the two-dimensional spatial variation of the uplift wind pressure. The new model was validated against a three-dimensional finite element model and also through a comparison with the results of experimental testing of a gable roof house previously conducted at the University of Western Ontario, Canada. The model was used to determine the load sharing among the trusses under a realistic load. It was also used to assess the adequacy of using the tributary area method under a code load. Based on the validation results, the semi-analytical solution model demonstrated an ability to predict the response of a roof under uplift wind loads that vary both in time and space. The main advantage of the new model is the efficient computational time compared to three-dimensional finite element modeling. As such this model can be used in the future for conducting probabilistic analysis of the roof taking into account the variation of the connection properties.

Wind-waves in the coast of mainland Portugal induced by post-tropical storms

In this short communication paper, we investigate the characteristics of wind-waves in Portugal mainland coast induced by post-tropical storms. Six major Atlantic hurricane events that occurred between 2012 and 2019 are studied: Rafael (2012), Joaquin (2015), Ophelia (2017), Leslie and Michael (2018), and Lorenzo (2019). None of these events has made landfall as a hurricane or tropical storm in mainland Portugal. However, Leslie and Ophelia have undergone extratropical transition close to mainland Portugal. We use wave buoy data at three different locations offshore mainland Portugal to characterize wind-waves during the events. The wind-waves here studied reached the coast in October. When compared with the dominant Northern Hemisphere winter wind-wave storms (December to March), the wind-waves here studied presented relatively mild wave conditions (maximum significant wave heights up to 5 m) that barely exceed wind-wave storm thresholds. Nevertheless, these wind-waves presented high mean direction variability, and induced high peak wave periods (up to 18 s).