The growing inadequacy of an open-ended Saffir-Simpson hurricane wind scale in a warming world.

Global warming increases available sensible and latent heat energy, increasing the thermodynamic potential wind intensity of tropical cyclones (TCs). Supported by theory, observations, and modeling, this causes a shift in mean TC intensity, which tends to manifest most clearly at the greatest intensities. The Saffir-Simpson scale for categorizing damage based on the wind intensity of TCs was introduced in the early 1970s and remains the most commonly used metric for public communication of the level of wind hazard that a TC poses. Because the scale is open-ended and does not extend beyond category 5 (70 m/s windspeed or greater), the level of wind hazard conveyed by the scale remains constant regardless of how far the intensity extends beyond 70 m/s. This may be considered a weakness of the scale, particularly considering that the destructive potential of the wind increases exponentially. Here, we consider how this weakness becomes amplified in a warming world by elucidating the past and future increases of peak wind speeds in the most intense TCs. A simple extrapolation of the Saffir-Simpson scale is used to define a hypothetical category 6, and we describe the frequency of TCs, both past and projected under global warming, that would fall under this category. We find that a number of recent storms have already achieved this hypothetical category 6 intensity and based on multiple independent lines of evidence examining the highest simulated and potential peak wind speeds, more such storms are projected as the climate continues to warm.

Elevated atmospheric CO2 drove an increase in tropical cyclone intensity during the early Toarcian hyperthermal.

The occurrence of sedimentary storm deposits around the Tethys Ocean during the early Toarcian hyperthermal (~183 Ma) suggests that intensified tropical cyclone (TC) activity occurred in response to CO2 rise and marked warming. However, this hypothesized linkage between extreme warmth and storm activity remains untested, and the spatial pattern of any changes in TCs is unclear. Here, model results show that there were two potential storm genesis centers over Tethys during the early Toarcian hyperthermal located around the northwestern and southeastern Tethys. The empirically determined doubling of CO2 concentration that accompanied the early Toarcian hyperthermal (~500 to ~1,000 ppmv) leads to increased probability of stronger storms over Tethys, in tandem with more favorable conditions for coastal erosion. These results match well with the geological occurrence of storm deposits during the early Toarcian hyperthermal and confirm that increased TC intensity would have accompanied global warming.

Pelagic seabirds reduce risk by flying into the eye of the storm.

Cyclones can cause mass mortality of seabirds, sometimes wrecking thousands of individuals. The few studies to track pelagic seabirds during cyclones show they tend to circumnavigate the strongest winds. We tracked adult shearwaters in the Sea of Japan over 11 y and found that the response to cyclones varied according to the wind speed and direction. In strong winds, birds that were sandwiched between the storm and mainland Japan flew away from land and toward the eye of the storm, flying within ≤30 km of the eye and tracking it for up to 8 h. This exposed shearwaters to some of the highest wind speeds near the eye wall (≤21 m s-1) but enabled them to avoid strong onshore winds in the storm's wake. Extreme winds may therefore become a threat when an inability to compensate for drift could lead to forced landings and collisions. Birds may need to know where land is in order to avoid it. This provides additional selective pressure for a map sense and could explain why juvenile shearwaters, which lack a map sense, instead navigating using a compass heading, are susceptible to being wrecked. We suggest that the ability to respond to storms is influenced by both flight and navigational capacities. This may become increasingly pertinent due to changes in extreme weather patterns.

Long-term climate and hydrologic regimes shape stream invertebrate community responses to a hurricane disturbance.

Disturbances can produce a spectrum of short- and long-term ecological consequences that depend on complex interactions of the characteristics of the event, antecedent environmental conditions, and the intrinsic properties of resistance and resilience of the affected biological system. We used Hurricane Harvey's impact on coastal rivers of Texas to examine the roles of storm-related changes in hydrology and long-term precipitation regime on the response of stream invertebrate communities to hurricane disturbance. We detected declines in richness, diversity and total abundance following the storm, but responses were strongly tied to direct and indirect effects of long-term aridity and short-term changes in stream hydrology. The amount of rainfall a site received drove both flood duration and flood magnitude across sites, but lower annual rainfall amounts (i.e. aridity) increased flood magnitude and decreased flood duration. Across all sites, flood duration was positively related to the time it took for invertebrate communities to return to a long-term baseline and flood magnitude drove larger invertebrate community responses (i.e. changes in diversity and total abundance). However, invertebrate response per unit flood magnitude was lower in sub-humid sites, potentially because of differences in refuge availability or ecological-evolutionary interactions. Interestingly, sub-humid streams had temporary large peaks in invertebrate total abundance and diversity following recovery period that may be indicative of the larger organic matter pulses expected in these systems because of their comparatively well-developed riparian vegetation. Our findings show that hydrology and long-term precipitation regime predictably affected invertebrate community responses and, thus, our work underscores the important influence of local climate to ecosystem sensitivity to disturbances.

Climate Justice Implications of Natech Disasters: Excess Contaminant Releases during Hurricanes on the Texas Gulf Coast.

Extreme weather events are becoming more severe due to climate change, increasing the risk of contaminant releases from hazardous sites disproportionately located in low-income communities of color. We evaluated contaminant releases during Hurricanes Rita, Ike, and Harvey in Texas and used regression models to estimate associations between neighborhood racial/ethnic composition and residential proximity to hurricane-related contaminant releases. Two-to-three times as many excess releases were reported during hurricanes compared to business-as-usual periods. Petrochemical manufacturing and refineries were responsible for most air emissions events. Multivariable models revealed sociodemographic disparities in likelihood of releases; compared to neighborhoods near regulated facilities without a release, a one-percent increase in Hispanic residents was associated with a 5 and 10% increase in the likelihood of an air emissions event downwind and within 2 km during Hurricanes Rita and Ike (odds ratio and 95% credible interval= 1.05 [1.00, 1.13], combined model) and Harvey (1.10 [1.00, 1.23]), respectively. Higher percentages of renters (1.07 [1.03, 1.11], combined Rita and Ike model) and rates of poverty (1.06 [1.01, 1.12], Harvey model) were associated with a higher likelihood of a release to land or water, while the percentage of Black residents (0.94 [0.89, 1.00], Harvey model) was associated with a slightly lower likelihood. Population density was consistently associated with a decreased likelihood of a contaminant release to air, land, or water. Our findings highlight social inequalities in the risks posed by natural-technological disasters that disproportionately impact Hispanic, renter, low-income, and rural populations.

Assessment of cyclone risk and case study of Gaja cyclone using GIS techniques and machine learning algorithms in coastal zone of Tamil Nadu, India.

Cyclones can cause devastating impacts, including strong winds, heavy rainfall, storm surges, and flooding. The aftermath includes infrastructure damage, loss of life, displacement of communities, and ecological disruptions. Timely response and recovery efforts are crucial to minimize the socio-economic and environmental consequences of cyclones. To accelerate the time-consuming risk assessment process, particularly in geographically diverse regions, a blend of multi-criteria decision-making and machine learning models was utilized. This novel approach swiftly assessed cyclone risk and the impact of the Gaja cyclone in Nagapattinam, India. The method involved assigning weights to distinct criteria, unveiling notable vulnerability aspects like elevation, slope, proximity to the coast, distance from cyclone tracts, Lu/Lc, population density, proximity to cyclone shelters, household density, accessibility to healthcare facilities, NDVI, and levels of awareness. Daddavari, Ettugudi, Kodikarai, Vedharanyam, Velankanni, and Thirupoondi face high/extreme cyclone risk. Nagore, Nagapattinam, Pillai, Enangudi, and Sannanllur have low/no threat. To further enhance the precision of the study, machine learning algorithms like SVM, SAM, and MLC were deployed. These models were instrumental in generating pre- and post-cyclone land use maps. The influence of Gaja cyclones effects shows decreasing of agriculture land from 34% to 30%, aquaculture increase 1%, barren land decrease from 8% to 6%, Built-up land decrease from 15% to 13%, land with scrub and salt pan also decrease from 21% to 17% and 10%-8%. Mostly effect of Gaja cyclone is dramatic increase of water body from 8% to 21%. Conducting cyclone risk zone analysis and pre/post-cyclone Land Use Land Cover (LULC) detection in Nagapattinam offers valuable insights for disaster preparedness, infrastructure planning, and climate resilience. This study can enhance understanding of vulnerability and aid in formulating strategies to mitigate cyclone impacts, ensuring sustainable development in the region.

Hurricane annual cycle controlled by both seeds and genesis probability.

Understanding tropical cyclone (TC) climatology is a problem of profound societal significance and deep scientific interest. The annual cycle is the biggest radiatively forced signal in TC variability, presenting a key test of our understanding and modeling of TC activity. TCs over the North Atlantic (NA) basin, which are usually called hurricanes, have a sharp peak in the annual cycle, with more than half concentrated in only 3 mo (August to October), yet existing theories of TC genesis often predict a much smoother cycle. Here we apply a framework originally developed to study TC response to climate change in which TC genesis is determined by both the number of pre-TC synoptic disturbances (TC "seeds") and the probability of TC genesis from the seeds. The combination of seeds and probability predicts a more consistent hurricane annual cycle, reproducing the compact season, as well as the abrupt increase from July to August in the NA across observations and climate models. The seeds-probability TC genesis framework also successfully captures TC annual cycles in different basins. The concise representation of the climate sensitivity of TCs from the annual cycle to climate change indicates that the framework captures the essential elements of the TC climate connection.

Change in cyclone disaster vulnerability and response in coastal Bangladesh.

The number of deaths owing to tropical cyclones in Bangladesh has significantly reduced. Category 4 Cyclone Gorky in 1991 and Sidr in 2007 caused 147,000 and 4,500 deaths respectively, whereas Category 1 Cyclone Mora in 2017 resulted in six. Face-to-face interviews with 362 residents, participant observation, and focus-group discussions answer a research question about how change in coastal areas has contributed to this outcome. The study considered institutional approaches of disaster risk management through legal frameworks, administrative arrangements, cyclone preparedness activities, cyclone detection and early warning dissemination, construction of shelter centres, strengthening of various types of coastal embankments, paved roads, and pre-cyclone evacuation. The findings indicate significant improvement in house structures and design, income levels and diversification, education, awareness, individual capacity, poverty reduction, and lowering dependency on agriculture-based earning. Furthermore, the availability of mobile telephones, radio, television, and social media platforms enhanced social connectivity and greater gender equality and empowerment helped to facilitate disaster preparedness, evacuation, and response.

A Portable Infrared System for Identification of Particulate Matter.

Occupational exposure to airborne dust is responsible for numerous respiratory and cardiovascular diseases. Because of these hazards, air samples are regularly collected on filters and sent for laboratory analysis to ensure compliance with regulations. Unfortunately, this approach often takes weeks to provide a result, which makes it impossible to identify dust sources or protect workers in real time. To address these challenges, we developed a system that characterizes airborne dust by its spectro-chemical profile. In this device, a micro-cyclone concentrates particles from the air and introduces them into a hollow waveguide where an infrared signature is obtained. An algorithm is then used to quantitate the composition of respirable particles by incorporating the infrared features of the most relevant chemical groups and compensating for Mie scattering. With this approach, the system can successfully differentiate mixtures of inorganic materials associated with construction sites in near-real time. The use of a free-space optic assembly improves the light throughput significantly, which enables detection limits of approximately 10 µg/m3 with a 10 minute sampling time. While respirable crystalline silica was the focus of this work, it is hoped that the flexibility of the platform will enable different aerosols to be detected in other occupational settings.

Satellite imagery-based tropical cyclone impact assessment on LULC and vegetation: a case study of cyclone Biparjoy.

Cyclones pose significant threats to coastal regions, triggering widespread ecological and hydrological changes. This study presents an impact assessment of cyclone Biparjoy, which originated in the Arabian Sea and made landfall on the Gujarat coast of India on June 16, 2023. The research encompasses flood delineation and vegetation impact assessment in the Kachchh and Devbhoomi Dwarka districts of Gujarat, India. Sentinel-1A (VV polarized) imagery is used to precisely map the extent of inundation caused by cyclone Biparjoy. The total flooded area for Kachchh and Devbhoomi Dwarka was calculated to be 6556.73 km2 and 104.49 km2, respectively. The most affected LULC class in Kachchh is found to be bare ground (38.95%) and rangeland (38.94%) which is the major part of the Northeastern Rann region. In Dwarka, most waterlogging has been seen in the cropland (33.04%). The classification of the water and non-water pixels for the pre- and post-images is validated using the ROC curve. The accuracy was 93.2% and 89.5% for pre- and post-images classifications, respectively. Furthermore, vegetation impact was investigated to estimate the cyclone's ecological consequences. Alterations in vegetation density and overall health were estimated by calculating Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from both pre- and post-cyclone Landsat-8 OLI images. The cyclone-induced damage is further assessed for the mangrove trees in Kori Creek. This work contributes to understanding the ecological repercussions of such extreme weather events.

Legacy effects of anthropogenic disturbances modulate dynamics in the world's coral reefs.

Rapidly changing conditions alter disturbance patterns, highlighting the need to better understand how the transition from pulse disturbances to more persistent stress will impact ecosystem dynamics. We conducted a global analysis of the impacts of 11 types of disturbances on reef integrity using the rate of change of coral cover as a measure of damage. Then, we evaluated how the magnitude of the damage due to thermal stress, cyclones, and diseases varied among tropical Atlantic and Indo-Pacific reefs and whether the cumulative impact of thermal stress and cyclones was able to modulate the responses of reefs to future events. We found that reef damage largely depends on the condition of a reef before a disturbance, disturbance intensity, and biogeographic region, regardless of the type of disturbance. Changes in coral cover after thermal stress events were largely influenced by the cumulative stress of past disturbances and did not depend on disturbance intensity or initial coral cover, which suggests that an ecological memory is present within coral communities. In contrast, the effect of cyclones (and likely other physical impacts) was primarily modulated by the initial reef condition and did not appear to be influenced by previous impacts. Our findings also underscore that coral reefs can recover if stressful conditions decrease, yet the lack of action to reduce anthropogenic impacts and greenhouse gas emissions continues to trigger reef degradation. We uphold that evidence-based strategies can guide managers to make better decisions to prepare for future disturbances.

Autonomous Large-Scale Radon Mapping and Buoyant Plume Modeling Quantify Deep Submarine Groundwater Discharge: A Novel Approach Based on a Self-Sufficient Open Ocean Vehicle.

Groundwater discharge into the sea occurs along many coastlines around the world in different geological settings and constitutes an important component of global water and matter budget. Estimates of how much water flows into the sea worldwide vary widely and are largely based on onshore studies and hydrological or hydrogeological modeling. In this study, we propose an approach to quantify a deep submarine groundwater outflow from the seafloor by using autonomously measured ocean surface data, i.e., 222Rn as groundwater tracer, in combination with numerical modeling of plume transport. The model and field data suggest that groundwater outflows from a water depth of ∼100 m can reach the sea surface implying that several cubic meters per second of freshwater are discharged into the sea. We postulate an extreme rainfall event 6 months earlier as the likely trigger for the groundwater discharge. This study shows that measurements at the sea surface, which are much easier to conduct than discharge measurements at the seafloor, can be used not only to localize submarine groundwater discharges but, in combination with plume modeling, also to estimate the magnitude of the release flow rate.

The critical role of cloud-infrared radiation feedback in tropical cyclone development.

The tall clouds that comprise tropical storms, hurricanes, and typhoons-or more generally, tropical cyclones (TCs)-are highly effective at trapping the infrared radiation welling up from the surface. This cloud-infrared radiation feedback, referred to as the "cloud greenhouse effect," locally warms the lower-middle troposphere relative to a TC's surroundings through all stages of its life cycle. Here, we show that this effect is essential to promoting and accelerating TC development in the context of two archetypal storms-Super Typhoon Haiyan (2013) and Hurricane Maria (2017). Namely, this feedback strengthens the thermally direct transverse circulation of the developing storm, in turn both promoting saturation within its core and accelerating the spin-up of its surface tangential circulation through angular momentum convergence. This feedback therefore shortens the storm's gestation period prior to its rapid intensification into a strong hurricane or typhoon. Further research into this subject holds the potential for key progress in TC prediction, which remains a critical societal challenge.

Global increase in major tropical cyclone exceedance probability over the past four decades.

Theoretical understanding of the thermodynamic controls on tropical cyclone (TC) wind intensity, as well as numerical simulations, implies a positive trend in TC intensity in a warming world. The global instrumental record of TC intensity, however, is known to be heterogeneous in both space and time and is generally unsuitable for global trend analysis. To address this, a homogenized data record based on satellite data was previously created for the period 1982-2009. The 28-y homogenized record exhibited increasing global TC intensity trends, but they were not statistically significant at the 95% confidence level. Based on observed trends in the thermodynamic mean state of the tropical environment during this period, however, it was argued that the 28-y period was likely close to, but shorter than, the time required for a statistically significant positive global TC intensity trend to appear. Here the homogenized global TC intensity record is extended to the 39-y period 1979-2017, and statistically significant (at the 95% confidence level) increases are identified. Increases and trends are found in the exceedance probability and proportion of major (Saffir-Simpson categories 3 to 5) TC intensities, which is consistent with expectations based on theoretical understanding and trends identified in numerical simulations in warming scenarios. Major TCs pose, by far, the greatest threat to lives and property. Between the early and latter halves of the time period, the major TC exceedance probability increases by about 8% per decade, with a 95% CI of 2 to 15% per decade.

The typhoon-induced drying of the Maritime Continent.

The Maritime Continent plays a role in the global circulation pattern, due to the energy released by convective condensation over the region which influences the global atmospheric circulation. We demonstrate that tropical cyclones contribute to drying the Maritime Continent atmosphere, influencing the definition of the onset of the dry season. The process was investigated using observational data and reanalysis. Our findings were confirmed by numerical experiments using low- and high-resolution versions of the CMCC-CM2 General Circulation Model contributing to the HighResMIP CMIP6 effort.

Summertime stationary waves integrate tropical and extratropical impacts on tropical cyclone activity.

Tropical cyclones (TC) are one of the most severe storm systems on Earth and cause significant loss of life and property upon landfall in coastal areas. A better understanding of their variability mechanisms will help improve the TC seasonal prediction skill and mitigate the destructive impacts of the storms. Early studies focused primarily on tropical processes in regulating the variability of TC activity, while recent studies suggest also some long-range impacts of extratropical processes, such as lateral transport of dry air and potential vorticity by large-scale waves. Here we show that stationary waves in the Northern Hemisphere integrate tropical and extratropical impacts on TC activity in July through October. In particular, tropical upper-tropospheric troughs (TUTTs), as part of the summertime stationary waves, are associated with the variability of large-scale environmental conditions in the tropical North Atlantic and North Pacific and significantly correlated to the variability of TC activity in these basins. TUTTs are subject to the modulation of diabatic heating in various regions and are the preferred locations for extratropical Rossby wave breaking (RWB). A strong TUTT in a basin is associated with enhanced RWB and tropical-extratropical stirring in that basin, and the resultant changes in the tropical atmospheric conditions modulate TC activity. In addition, the anticorrelation of TUTTs between the North Atlantic and North Pacific makes the TC activity indices over the two basins compensate each other, rendering the global TC activity less variable than otherwise would be the case if TUTTs were independent.

Humanitarian aid and local responses: the aftermath of the rebuilding effort on Tongoa island, Vanuatu.

Cyclone Pam swept through the archipelago of Vanuatu on 13-14 March 2015, with wind speeds exceeding those recorded anywhere in the South Pacific since the 1980s. Southern and central parts of the country were particularly affected. Material damage on Tongoa, one of the most afflicted islands, was extensive, but no deaths were reported. During the storm, villagers found shelter in their kitchen, in what is considered locally as a 'lifeboat'. The aftermath was managed and mitigated by international aid organisations. On Tongoa, this included a 'Shelter Cluster' programme, under which villagers were given house rebuilding kits. Elaborating upon extensive ethnographic investigations on site between 2011 and 2018, this paper explores and reveals the ways in which this aid generated confusion among the local population. In a larger context of regular disasters triggered by natural hazards, locals have found endogenous ways of dealing with such extreme climatic events, for the most part without any external assistance.

Particulate PCDD/F size distribution and potential deposition in respiratory system from a hazardous waste thermal treatment process.

The particulate polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) of various sizes produced from the waste incinerators might have different toxicities, deposition characteristics, and potential health effects in the respiratory system, and their total toxicity equivalent (TEQ) concentration has been strictly regulated in recent years. There is a knowledge gap on the effects of air pollution control devices on particle size distributions (PSDs) of PCDD/Fs and their TEQ deposition. A hazardous waste thermal treatment plant equipped with an advanced scrubber, a cyclone demister, and activated carbon adsorption coupled with a baghouse filtration was investigated in this study. An 8-stage impactor was used to collect the particle distribution of PM10 and bounded PCDD/Fs from the gas stream at four sampling points located before and after each control unit. A "TEQDE" index is defined for the toxicity deposition of PM10-PCDD/F in the respiratory system. The advanced scrubbers significantly reduced the PM10-PCDD/F levels, especially for those with sizes ≥0.6 and ≤ 0.4 µm. Additionally, the cyclone also showed a better performance than the general dry gas treatment but had an efficiency drop with 1.5-4 µm particles. The PM10-PCDD/F loads in the final adsorption-filtration unit were eased and effectively removed the PM10-PCDD/Fs to sizes ≤0.5 or≥1.5 µm. The total TEQDE was 0.00052 ng WHO-TEQ Nm-3 and had a peak level of 0.000157 ng WHO-TEQ Nm-3 at 1.2 µm. PSDs were more sensitive to the PSDs of PM mass at high PM levels but strongly correlated with the PSDs of "PM10-PCDD/Fs/PM10" at low PM10 loads. Consequently, the advanced control system could effectively remove the PM10-PCDD/Fs and might extend the adsorption-filtration lifetime. However, the PM10-PCDD/Fs ≤ 0.4 µm had a higher TEQ deposition rate and should be further considered in emissions and ambient air quality evaluations.

Ensemble forecast experiments of summertime sea ice in the Arctic Ocean using the TOPAZ4 ice-ocean data assimilation system.

Precise information on sea ice thickness (SIT) and its prediction at medium-range (2-week) timescale is crucial for the safe maritime navigation in the Arctic Ocean. In this study, we investigate the sensitivity of medium-range prediction skill of summertime SIT distribution in the Arctic marginal seas to atmospheric forecast data, using the 51-member ECMWF operational ensemble prediction system (EPS). For a synoptic-scale cyclone event occurred in July 5-6, 2015, two-week probabilistic forecast experiments were conducted with the TOPAZ4 ice-ocean forecast system, starting on 1st July. The ensemble correlation analysis between the forecast SIT and the meteorological parameters shows that the forecast error of SIT distribution is sensitive to the sea ice drift speed until 1-week, indicating that realistic sea ice drift improves the sea ice thickness prediction. On the other hand, beyond 1 week lead, the forecast error of SIT distribution is more sensitive to surface heat flux rather than sea ice drift. The surface heat flux signal is confined to the sea ice edge region, where the shortwave radiation flux is related to the SIT change through the sea ice melting process. The shortwave radiation flux in the sea ice edge is mostly determined by the sea ice distribution, suggesting that the skillful prediction of sea ice distribution, which is largely affected by synoptic-scale disturbance, at shorter lead times indirectly affects the medium-range forecast skill. A comparison of different ensemble perturbation techniques shows that the prediction skill is better at shorter lead times (up to 1 week), when using an atmospheric EPS rather than the random perturbations used in the operational forecast system, but the random perturbations are advantageous beyond 1 week. Thus, the application of the EPS to an ice-ocean coupled forecast system leads to a more precise sea ice prediction on medium-range timescale, which we expect to become of practical use for the optimum shipping route in the Arctic Ocean.

Experiences of pregnant women exposed to Hurricanes Irma and Maria in the US Virgin Islands: a qualitative study.

INTRODUCTION: Hurricanes Irma and Maria made landfall in the US Virgin Islands (USVI) in 2017. To date, there is no published literature available on the experiences of pregnant women in the USVI exposed to these hurricanes. Understanding how hurricanes affect pregnant women is key to developing and executing targeted hurricane preparedness and response policies. The purpose of this study was to explore the experiences of pregnancy and birth among women in the USVI exposed to Hurricanes Irma and Maria. METHODS: We employed a qualitative descriptive methodology to guide sampling, data collection, and analysis. Semi-structured interviews of 30-60 min in length were conducted with a purposive sample of women (N = 18) in the USVI who were pregnant during or became pregnant within two months after the hurricanes. Interviews were transcribed verbatim and data managed in MAXQDA. Team members developed a codebook, applied codes for content, and reconciled discrepancies. We thematically categorized text according to a socioecological conceptual framework of risk and resilience for maternal-neonatal health following hurricane exposure. RESULTS: Women's experiences were organized into two main categories (risk and resilience). We identified the following themes related to risk at 3 socioecological levels including: (1) individual: changes in food access (We had to go without) and stress (I was supposed to be relaxing); (2) household/community: diminished psychosocial support (Everyone was dealing with their own things) and the presence of physical/environmental hazards (I was really scared); and (3) maternity system: compromised care capacity (The hospital was condemned). The themes related to resilience included: (1) individual: personal coping strategies (Being calm); (2) household/community: mutual psychosocial and tangible support (We shared our resources); and (3) the maternity system: continuity of high-quality care (On top of their game). CONCLUSIONS: A socioecological approach provides a useful framework to understand how risk and resilience influence the experience of maternal hurricane exposure. As the frequency of the most intense hurricanes is expected to increase, clinicians, governments, and health systems should work collaboratively to implement hurricane preparedness and response plans that address pregnant women's unique needs and promote optimal maternal-infant health.