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Hurricane Michael made landfall as a Category 5 Hurricane on 10 October 2018 between Mexico Beach, Florida and Tyndall Air Force Base in Panama City Beach, Florida causing damages totaling $25 billion (Beven et al. 2019). While damages were caused by both wind and surge, this paper is solely concerned with the surge induced damages which were observed predominantly within 50 km (27 nmi) of the hurricane’s path. Generally, regions to the east of Hurricane Michael’s landfall sustained the most severe damages and appear consistent with the spatial gradient in peak water levels. This gradient was marked; with surge induced damage concentrated in the immediate vicinity of Mexico Beach and attenuating significantly over distances as little as 37 km (20 nmi) to the west in Panama City Beach and east in Port Saint Joe (Kennedy, in review). The gradient in erosion was also pronounced, with Panama City Beach experiencing an average erosion rate of 0.4 m3/m (3.9 cy/ft) while Mexico Beach and Cape San Blas experienced rates approximately three (1.1 m3/m or 11.5 cy/ft) and five (1.7 m3/m or 18.5 cy/ft) times that. For inherent reasons, the pronounced gradient in surge damages and erosion values are of primary interest to coastal researchers and managers. Storm Erosion Index (SEI), developed by Miller and Livermont (2008) combines the three primary drivers of coastal erosion (wave height, total water level, and storm duration) into a physically meaningful form to evaluate storms based on their erosion potential. Here, SEI is applied to explore these spatial variations at seven distinct regions within the Florida Panhandle and are compared to the observed impacts for both erosion and structural damages. These regions include: (west to east) Panama City Beach, Tyndall Air Force Base (AFB), Mexico Beach, Cape San Blas, Port St. Joe, St. Vincent Island, and St. George Island. Empirically, the cumulative SEI relates well with the observed beach erosion; while the Peak Erosion Intensity (PEI) was found to better capture the trends in structural damages. By capturing the spatial variation of the storm intensity, SEI and PEI are therefore proposed as a viable engineering demand parameter with potential applications in community scale fragility curves.

The paper is focused on the formulation of an adequate criterion for associating wave storm events to the generating wind storm ones, and on the study of correlation between their characteristic parameters. In this context, the sea storm definition commonly used for storm identification from significant wave height data is adapted for wind storm, by processing wind speed data. A sensitivity analysis is proposed as function of the storm thresholds aiming at identifying optimal combination of wind speed and significant wave height thresholds allowing the association of relatively large number of events ensuring high correlation between wind and wave storm parameters. The analysis is carried out using as input data wind speeds and significant wave heights from four meteorological (buoys and anemometers) stations of the National Data Buoy Center moored off the East Coast of the United States. Results reveal that an optimal threshold combination is achieved assuming both wind speed and significant wave height threshold as 1.5 time their respective averages.

We present the first quantitative calculations of thermospheric heating and cooling times for geomagnetic storms of different intensity, including extreme events. We utilize the neutral mass density database of the CHAllenging Mini‐satellite Payload and Gravity Recovery And Climate Experiment missions to produce thermospheric global system response to geomagnetic storms caused by coronal mass ejections via superposed epoch analysis during May 2001 to December 2015. Storm events are grouped in five different categories based on the minimum value of the SYM‐H index. We calculate the time from storm onset for the thermosphere to reach maximum intensification (heating time) and the time from onset for the thermosphere to recover (cooling time). We find that heating and cooling times decrease as storm intensity increases and the effect is more pronounced for the cooling times. For extreme storms, the thermospheric heating time is 9.5 hr, while the cooling time is 22 hr.

A global COVID-19 pandemic, rising asthma and allergies - along with climate change impacting storm intensity and frequency - point to an urgent need to unify U.S. atmospheric biology research. To this end, we briefly define atmospheric biology, summarize its fragmented history and then outline how to unify the field to provide benefits for the U.S. science community and its citizens. Atmospheric biology refers to the study of concentrations, sources, sinks, transformation and impacts of airborne microorganisms inclusive of pollen, fungal spores, algae, lichens, bacteria, viruses, cellulose fibers, and other biomolecules or fragments of cells. Here our focus is biological particles, both respirable (PM10 ) and systemic (PM2.5 ). Due to its interdisciplinary dependencies and broadness of scales from nanometers to kilometers, atmospheric biology research is highly fragmented in the U.S. science community. It lacks shared paradigms and common vocabulary. This deficit calls for recognizing atmospheric biology as a research community in its own right, thereby linking human health to climate change. We need to recognize atmospheric biology's importance to national security and science diplomacy. Advanced atmospheric biology research is being conducted in Europe, Russia and China, not in the United States.

There is an increasing risk of dike failures along the coasts worldwide due to increase in relative MSL (Mean Sea Level) rise and increase in storm intensity. Wave run-up plays a key role in planning and design of coastal structures. Numerous research works were carried out on wave run-up and wave overtopping in the last few decades. However, limited information is available on the effect of the curvature in coastal dikes on wave run-up and overtopping. This research focuses on influence of curved dikes on wave run-up using numerical models. The numerical models used for this research are DualSPHysics and OpenFOAM. Analysis covers both wave run-up estimation and the underlying wave transformation processes at the curvature. The numerical analysis results show a complex behavior in wave transformation processes for curved dikes. Hence, this research aims to contribute a more precise analysis and understanding the influence of the curvature in the dike line and thus ensuring a higher level of protection in the future development of coastal structures.

Storm-event analysis (SEA) is a method of extracting information from rainfall data by defining rainfall events as storm events. A profile-based model in SEA defines storm events using the ...

We present a parametric study of surface wave effects on storm surge and coastal inundation. Hurricane wind forcing terms, atmosphere pressure gradient terms, and radiation open boundary conditions are implemented into an existing quasi-3D nearshore model, NearCoM-TVD, which uses a shock-capturing TVD scheme and can better simulate the wetting-drying process during inundation than a conventional finite difference model. Systematic numerical experiments are carried out in an idealized continental shelf-beach-land system to identify the role of waves in modeling storm surge and inundation under different storm characteristics. Four storm parameters, including storm intensity, storm size, translation speed and incident angle are investigated. Modeling results reveal that the presence of waves can increase the maximum storm surge heights significantly through wave setup, and the contribution of waves varies considerably depending on the storm characteristics. In addition to direct wave forcing, the wave-enhanced bottom stress in the surfzone also promotes higher wave setup and hence higher surge heights. Waves also have a major influence on the maximum inland inundation distance, however, we find that waves do not always favor more inundation as expected. For storms traveling at very slow translation speeds or nearly parallel to the coast, waves surprisingly exert a negative effect on the maximum inundation distance. We argue that wave-enhanced bottom stress combined with longer forcing duration in such storms counteract the positive effect of wave setup, and thus less inundation is predicted in wave-current coupled simulations. Our results highlight the necessity of fully-incorporating wave effects in storm surge and inundation modeling.

The Emergency Events Database (EM-DAT) indicates that the economic damage associated with storms has been rapidly growing in Vietnam. By contrast, the fatality rate due to storm-relevant disasters has been declining in recent decades. This study investigates whether typhoon trends have affected these outcomes. Best track data from the Japan Meteorological Agency (JMA) were examined to estimate central pressure and wind speed when typhoons made landfall. From 1977 to 2017, typhoons with wind speeds above 20 knots struck the country 105 times. A statistical analysis, which defined a storm's intensity using principal component analysis (PCA), revealed that Typhoon Doksuri in 2017 was the strongest among the collection, followed by Cecil in 1985, Xangsane in 2006, and Damrey in 2017. The worst storm in history, Typhoon Linda in 1997, claimed over 3500 lives in southern Vietnam, but was only ranked 37th, demonstrating that typhoon intensity is not always the determining factor of fatalities. Moreover, the analysis of variance (ANOVA) illustrates that none of the meteorological trends such as frequency, central pressure, wind speed, or storm intensity show any significant increase or decrease over the last four decades. However, landfall frequency has risen significantly, particularly in the northernmost part of the country where two large cities, Hanoi and Hai Phong, are located. A strong correlation was found between intensity and recent economic damage (r = 0.80) based on the proposed index of positive annual landfall storm intensity (PALSI). Given all of these factors, it is reasonable to attribute the expansion of disaster-related economic damage to economic development and the fundamental volatility of typhoons.

This study extends the statistical analysis on the dependence of tropical cyclone (TC) intensification rate (IR) on sea surface temperature (SST), storm initial intensity (maximum sustained surface wind speed Vmax), and storm size, in terms of the radius of maximum wind (RMW), the radius of 34-kt (AR34; 1 kt = 0.51 m s−1) wind, and the outer-core wind skirt parameter DR34 (= AR34 − RMW), for North Atlantic TCs to western North Pacific (WNP) TCs during 1982–2015. Results show that the relationship between the TC maximum potential intensification rate (MPIR) and SST also exists in the WNP. TC IR depends strongly on TC intensity and structure, consistent with the findings for North Atlantic TCs. TC IR is positively (negatively) correlated with storm intensity when Vmax is below (above) 70 kt and negatively correlated with the RMW. Rapid intensification (RI) occurs only in a relatively narrow range of parameter space in storm intensity and both inner- and outer-core sizes, with the highest IR appearing for Vmax = 70 kt, RMW ≦ 40 km, AR34 = 150 km, and DR34 = 100 km. The highest frequency of occurrence of intensifying TCs occurs for Vmax ~ 40–60 kt, RMW ~ 20–60 km, AR34 = 200 km, and DR34 = 120 km. Overall, these values are very similar to those for TCs in the North Atlantic. These results suggest the need for the realistic initialization of TC structure in numerical models and the inclusion of size parameters in statistical TC intensity prediction schemes.

The ocean waves in the North Atlantic Ocean are internationally recognized to represent a wave climate suitable for the design of merchant ships. However, the accumulated knowledge from the past indicates that the encountered sea states are less severe than the Standard Wave Data recommended by the International Association of Classification Society. In this study, we propose a statistical model representing storm avoidance by ships and apply it to a newly computed 25-year wave hindcast (TodaiWW3-NK) in the North Atlantic Ocean. We derive the 25-year statistics of waves encountered by merchant ships. The statistical model relates the storm intensity and the distance of the ship from the storm center and derives from the 2 years and 11 months of ship position records based on Automatic Identification System (AIS) and the hindcast wave data. The estimated 25-year exceedance probability of significant wave height in the North Atlantic Ocean agrees well with that of the waves encountered along the shipping route, thereby demonstrating the validity of the suggested storm avoidance model. The most significant uncertainty of the estimate originates from the choice of a wave model, as shown by comparison with the estimation based on other hindcast products (ERA5 and IOWAGA).

This paper empirically examines the economic impacts of Hurricanes Harvey and Irma in 2017 and the role of federal aid in the recovery process. Data from 90 disaster counties in Texas and Florida reveal a strong relationship between direct economic damages and localized measures of storm intensity. The impact of the storms on local unemployment and employment dissipated within one year. Along with individual communities’ inherent resilience capacity, federal policy responses to economic losses played a role in supporting local recovery across the two disaster regions. Regressions with spatial effects show that following a hurricane strike, employment and wages moved in the opposite directions between a disaster county and its neighboring counties.

Rainfall erosivity is the capability of rainfall to cause soil loss from hillslopes by water. Modern definitions of rainfall erosivity began with the development of the Universal Soil Loss Equation (USLE), where rainfall characteristics were statistically related to soil loss from thousands of plot-years of natural rainfall and runoff data. USLE erosivity combines the energy of the rainfall and the maximum continuous 30-min intensity in the event. Energy of rainfall is estimated as a function of the storm intensity through the rainfall event. The USLE erosivity has been used effectively for conservation planning purposes for more than 5 decades. When the USLE was replaced by the Revised Universal Soil Loss Equation (RUSLE), a new energy-intensity equation was adopted. The new equation was not extensively tested prior to adoption, leads to significant under-predictions of erosivity, and was later replaced in RUSLE2. The RUSLE energy-intensity equation is no longer recommended by the RUSLE and RUSLE2 development teams. RUSLE2 also introduced the concept of erosivity density, which resulted in significant improvements in the calculations and mapping of rainfall erosivity. Calculations of erosivity as a whole are entirely based on rainfall intensities, and erosivity is an empirically-based index. The science indicates that the direct role of kinetic energy of rainfall as the driver of hillslope erosion in all cases is not warranted by the overall evidence, because many times the kinetic energy of raindrops is not the driving force behind rill erosion. The USLE erosivity empirically explains much of the variance in the soil loss from natural rainfall erosion plots.

The results of studying the intensity of fluxes of 30–80 keV ions from the data of measurements of the NOAA (POES) sun-synchronous satellites during geomagnetic storms of different intensity are presented. For 15 geomagnetic storms with |Dst|max from ~37 to ~422 nT, the storm-time maximum ion fluxes in the near-equatorial region (trapped particles) and at high latitudes (precipitating particles) have been considered. It is shown that the maximum fluxes of trapped particles, which are considered a ring-current proxy, increase with the storm power. In this case, if a smooth growth of fluxes is recorded for storms with |Dst|max 250 nT. This may be evidence of both an increasing of the contribution of the ring current relative to magnetotail currents to the development of high-intensity storms and to a nonlinear link between the ring current and ion fluxes at low altitudes in the near-equatorial region. Despite large variations in fluxes of precipitating particles in the polar region above the boundary of isotropization, a decreasing tendency, as a whole, in fluxes of these particles is observed with increasing the storm intensity. This is the evidence of the effect of saturation of magnetotail currents and of an increase in the relative role of the ring current during strong magnetic storms.

Due to the impacts of globe climate change and human activities, dramatic variations in runoff and sediment load were observed for the Yellow River. Analyses of nearly 65 years’ data measured at main hydrologic-stations on the Yellow River from 1950 to 2014 indicated that, except for the Tangnaihai station in the head region, sharp downward trends existed in both the annual runoff and annual sediment load according to the Mann–Kendal trend test; and their abrupt changes occurred in 1986 and in 1980, respectively, according to the rank sum test. Factors affecting the changes in the runoff and sediment load were very complicated. Results indicated that the reducing precipitation and the increasing water consumption were the main causes for the runoff decline, while the impoundment of the Longyangxia Reservoir and its combined operation with the Liujiaxia Reservoir exerted a direct bearing on the abrupt change in the annual runoff. In addition to the sediment load decrease associated with the runoff reduction, the reduced storm intensity, the conducted soil erosion control, and the constructed dam buildings all played an important role in the trends and abrupt changes of sediment load decline.

Intensity and size are two crucial factors in determining the destructiveness of a tropical cyclone (TC), but little is known about the relationship between them because of a lack of observations. TC fullness, a new concept, is proposed to quantitatively measure the storm wind structure, which is defined as the ratio of the extent of the outer-core wind skirt to the outer-core size of the TC. TC intensity is more strongly correlated with fullness than with other measures comprising just a single size parameter. A scale is introduced to classify TCs into four categories based on TC fullness (FS1 to FS4). Regardless of the specific inner-core and outer-core size, the FS4 fullness structure is necessary for an intense TC's development, while category FS1 and FS2 TCs are generally weak. Most major TCs achieve FS4 fullness structure earlier and more frequently than nonmajor TCs. Rapidly increasing fullness favors the intensification of TC.

One major threat to cities at present is the increased inundation hazards owing to changes in climate and accelerated human activity. Future evolution of urban inundation is still an unsolved issue, given large uncertainties in future environmental conditions within urbanized areas. Developing model techniques and urban inundation projections are essential for inundation management. In this paper, we proposed a 2D hydrodynamic inundation model by coupling SWMM and LISFLOOD-FP models, and revealed how future urban inundation would evolve for different storms, sea level rise and subsidence scenarios based on the developed model. The Shiqiao Creek District (SCD) in Dongguan City was used as the case study. The model ability was validated against the June 13th, 2008 inundation event, which occurred in SCD, and proved capable of simulating dynamic urban inundation. Scenario analyses revealed a high degree of consistency in the inundation patterns among different storms, with larger magnitudes corresponding to greater return periods. Inundations across SCD generally vary as a function of storm intensity, but for lowlands or regions without drainage facilities inundations tend to aggravate over time. In riverfronts, inundations would exacerbate with sea level rise or subsidence; however, the inland inundations are seemingly insensitive to both factors. For the combined scenario of 100-yr storm, 0.5 m subsidence and 0.7 m sea level rise, the riverside inundations would occur much in advance, whilst catastrophic inundations sweep across SCD. Furthermore, the optimal low-impact development found for this case study includes 0.2 km2 of permeable pavements, 0.1 km2 of rain barrels and 0.7 km2 of green roofs.

This paper statistically examines the hypothesis that the level of storm surge, not storm intensity, is primarily responsible for the large number of tropical cyclone fatalities in South Asia. Because the potential causal link between intensity and surge can confound statistical inference, the authors develop two fatality models using different assumptions on the relationship between storm surge and intensity. The authors find evidence that storm surge is a primary killer of people in South Asia relative to storm intensity. In a surge–pressure independence model, it is found that a 10-cm increase in storm surge results in a 14% increase in the number of fatalities. In a surge–pressure dependence model, a 10-cm increase in the level of surge not driven by minimum central pressure (MCP) leads to 9.9% increase in the number of fatalities. By contrast, a one-millibar (1 hPa) decrease in MCP leads to a 7.3% increase in the number of fatalities, some of which is also attributable to storm surge. In South Asia, adaptation strategies should target a higher level of storm surge instead of higher-intensity storms. Policies to combat surge include permanent relocation, temporary evacuation, changes in building structures, and coastal fortification.

Historical reanalyses that span more than a century are needed for a wide range of studies, from understanding large‐scale climate trends to diagnosing the impacts of individual historical extreme weather events. The Twentieth Century Reanalysis (20CR) Project is an effort to fill this need. It is supported by the National Oceanic and Atmospheric Administration (NOAA), the Cooperative Institute for Research in Environmental Sciences (CIRES), and the U.S. Department of Energy (DOE), and is facilitated by collaboration with the international Atmospheric Circulation Reconstructions over the Earth initiative. 20CR is the first ensemble of sub‐daily global atmospheric conditions spanning over 100 years. This provides a best estimate of the weather at any given place and time as well as an estimate of its confidence and uncertainty. While extremely useful, version 2c of this dataset (20CRv2c) has several significant issues, including inaccurate estimates of confidence and a global sea level pressure bias in the mid‐19th century. These and other issues can reduce its effectiveness for studies at many spatial and temporal scales. Therefore, the 20CR system underwent a series of developments to generate a significant new version of the reanalysis. The version 3 system (NOAA‐CIRES‐DOE 20CRv3) uses upgraded data assimilation methods including an adaptive inflation algorithm; has a newer, higher‐resolution forecast model that specifies dry air mass; and assimilates a larger set of pressure observations. These changes have improved the ensemble‐based estimates of confidence, removed spin‐up effects in the precipitation fields, and diminished the sea‐level pressure bias. Other improvements include more accurate representations of storm intensity, smaller errors, and large‐scale reductions in model bias. The 20CRv3 system is comprehensively reviewed, focusing on the aspects that have ameliorated issues in 20CRv2c. Despite the many improvements, some challenges remain, including a systematic bias in tropical precipitation and time‐varying biases in southern high‐latitude pressure fields.

The secondary eyewall replacement cycle (ERC) is an important aspect for tropical cyclone (TC) intensity and structure forecasts. Both observational studies and idealized simulations are conducted to explore the sensitivity of secondary eyewall formation (SEF) to the initial structure of the tropical cyclone. It is found that a TC with a larger size (i.e. both the radial of maximum wind and outer size) is apt to SEF. Furthermore, a larger TC likely has a potential to form a larger outer eyewall and thus a wider moat region. The different SE structures may lead to different intensity fluctuations. This study motivates further research with respect to how initial structure influences the storm intensity and structure changes.

The skill of tropical cyclone intensity forecasts has improved slowly since such forecasts became routine, even though track forecast skill has increased markedly over the same period. In deciding whether or how best to improve intensity forecasts, it is useful to estimate fundamental predictability limits as well as sources of intensity error. Toward that end, the authors estimate rates of error growth in a “perfect model” framework in which the same model is used to explore the sensitivities of tropical cyclone intensity to perturbations in the initial storm intensity and large-scale environment. These are compared to estimates made in previous studies and to intensity error growth in real-time forecasts made using the same model, in which model error also plays an important role. The authors find that error growth over approximately the first few days in the perfect model framework is dominated by errors in initial intensity, after which errors in forecasting the track and large-scale kinematic environment become more pronounced. Errors owing solely to misgauging initial intensity are particularly large for storms about to undergo rapid intensification and are systematically larger when initial intensity is underestimated compared to overestimating initial intensity by the same amount. There remains an appreciable gap between actual and realistically achievable forecast skill, which this study suggests can best be closed by improved models, better observations, and superior data assimilation techniques.

The role of Universal Time (UT) dependence on storm-time development has remained an unresolved question in geospace research. This study presents new insight into storm progression in terms of the UT of the storm peak. We present a superposed epoch analysis of solar wind drivers and geomagnetic index responses during magnetic storms, categorized as a function of UT of the storm peak, to investigate the dependency of storm intensity on UT. Storms with Dst minimum less than - 100 nT were identified in the 1970 - 2012 era (305 events), covering four solar cycles. The storms were classified into 6 groups based on the UT of the minimum Dst (40 to 61 events per bin), then each grouping was superposed on a timeline that aligns the time of the minimum Dst. Fifteen different quantities were considered, seven solar wind parameters and eight activity indices derived from ground-based magnetometer data. Statistical analyses of the superposed means against each other (between the different UT groupings) were conducted to determine the mathematical significance of similarities and differences in the time series plots. It was found that the solar wind parameters have no significant difference between the UT groupings, as expected. The geomagnetic activity indices, however, all show statistically significant differences with UT during the main phase and/or early recovery phase. Specifically, the 02:00 UT groupings are stronger storms than those in the other UT bins. That is, storms are stronger when the Asian sector is on the nightside (American sector on the dayside) during the main phase.

Jarmalavicius, D.; Smatas, V.; Stankūnavicius, G.; Pupienis, D., and Žilinskas, G., 2016. Factors controlling coastal erosion during storm events. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 1112 - 1116. Coconut Creek (Florida), ISSN 0749-0208. Extreme storms may induce major changes in coastal morphology which are usually short-term in nature. The storm-related effects are controlled by different factors such as storm intensity, sand composition and coastal morphology. The main task of this study is to identify the main factors controlling erosion processes in particular coastal sectors during an extreme event. We analysed three major storms that took place over the last 15 years on the Lithuanian Baltic Sea coast: 4th December, 1999, 9th January, 2005 and 11th January, 2015. The scale of storm impact has been assessed through annual...

To combat erosion, there is need for adequate examination of soils and factors of erosion. The study of Erosivity is vital for effective soil conservational planning and agricultural activities in Enugu State of Nigeria of West Africa, and other parts of the world. In this study, rainfall amount and duration were obtained and used in the determination of rainfall intensities in Enugu regions. These rainfall records were used in calculating the three erosivity indices namely; the maximum 30-minute intensity, kinetic energy greater than 25, and peak storm intensity. With the aid of the above data, erosivity of Enugu was uncovered. This was achieved by taking the average of the calculated years. This Erosivity value can be used in modeling a general soil loss equation for all soil types in Enugu. This general soil loss equation can be used to predict erosion in Enugu region. Also, from the force impact of rain capable of causing erosion, erosive rain were separated from non erosive rain using the method based upon the concept that there is a threshold value of intensity at which rain starts to be erosive. With this insight, one can also predict future erosive rain and non erosive rain using the weather forecast data. With the knowledge of these predictions, erosion prevention technique may be applied in areas of possible future occurrence rather than remediating soil after erosion hazard.

A strong windstorm struck south-central Nepal on March 31, 2019. Southern parts of Bara and Parsa districts were affected by the storm. The storm caused 28 casualties, 1155 injuries, damaged 2637 houses and affected 16 infrastructures. The effect of the storm was observed along a NW-SE stretch for ~25 ​km ​at a width of around 250 ​m. This paper presents an account of the damage observed during the field reconnaissance conducted between April 2–4, 2019. Reinforced concrete (RC), brick masonry, and vernacular wattle and daub construction systems are considered to depict storm vulnerability of residential buildings. As storms are not frequent in Nepal, and Nepal had not witnessed storm of this scale in the past seven decades or more, this paper assesses storm vulnerability of structures and infrastructures combining the field observations and forensic interpretations. A new storm intensity scale is proposed, and the affected areas are mapped based on the assigned intensities. Empirical fragility functions for wattle and daub houses are also derived from the damage statistics. Finally, some lessons regarding storm damage and vulnerability are also outlined in this paper.

This study analyses Global Positioning System dropsondes to document the axisymmetric tropical cyclone (TC) boundary-layer structure, based on storm intensity. A total of 2608 dropsondes from 42 named TCs in the Atlantic basin from 1998 to 2017 are used in the composite analyses. The results show that the axisymmetric inflow layer depth, the height of maximum tangential wind speed, and the thermodynamic mixed layer depth are all shallower in more intense TCs. The results also show that more intense TCs tend to have a deep layer of the near-saturated air inside the radius of maximum wind speed (RMW). The magnitude of the radial gradient of equivalent potential temperature (&theta, e) near the RMW correlates positively with storm intensity. Above the inflow layer, composite structures of TCs with different intensities all possess a ring of anomalously cool temperatures surrounding the warm-core, with the magnitude of the warm-core anomaly proportional to TC intensity. The boundary layer composites presented here provide a climatology of how axisymmetric TC boundary layer structure changes with intensity.