Tropical Storm Research Articles

Hydroacoustic Observations Reveal Drivers of Mixing and Salinization of a Karst Subterranean Estuary During Intense Precipitation

AbstractKarst subterranean estuaries within globally ubiquitous carbonate aquifers are coastal groundwater ecosystems that provide an essential water resource for human populations. To understand the drivers of salinization within a coastal aquifer in the Yucatan Peninsula (Mexico), we employed hydroacoustics in flooded caves to observe how oceanic and atmospheric events facilitate mixing between the meteoric lens (fresh‐brackish groundwater) and the saline groundwater on tidal and episodic timescales. Precipitation during Tropical Storm Carlotta increased the flow and salinity of the meteoric lens without evidence for vertical mixing across the halocline. We postulate that vertical migration of haloclines in the conduit relative to those within the rock matrix during precipitation creates lateral density gradients that drive mixing, and ultimately creates a brackish layer within the meteoric lens. These results provide a mechanistic explanation for vertical and lateral exchange in a coastal carbonate aquifer, which has implications for groundwater response to future climatic change.

Prepare for the worst: Make evacuation plans accessible

The 2024 hurricane season had more than its fair share of hurricanes, tornadoes, and tropical storms. Hurricanes Beryl, Debby, Ernesto, Helene, and Milton caused tens of billions of dollars in property damage, including damage to college and university campuses, plus hundreds of deaths. These hurricanes, as well as other natural disasters, serve as a reminder for postsecondary institutions to engage in emergency planning.

Seasonality and Predictability of Hydrometeorological and Water Chemistry Indicators in Three Coastal Forested Watersheds

Forests are recognized for sustaining good water chemistry within landscapes. This study focuses on the water chemistry parameters and their hydrological predictability and seasonality (as a component of predictability) in watersheds of varying scales, with and without human (forest management) activities on them, using Colwell indicators for data collected during 2011–2019. The research was conducted in three forested watersheds located at the US Forest Service Santee Experimental Forest in South Carolina USA. The analysis revealed statistically significant (α = 0.05) differences between seasons for stream flow, water table elevation (WTE), and all water chemistry indicators in the examined watersheds for the post-Hurricane Joaquin period (2015–2019), compared to the 2011–2014 period. WTE and flow were identified as having the greatest influence on nitrogen concentrations. During extreme precipitations events, such as hurricanes or tropical storms, increases in WTE and flow led to a decrease in the concentrations of total dissolved nitrogen (TDN), NH4-N, and NO3-N+NO2-N, likely due to dilution. Colwell indicators demonstrated higher predictability (P) for most hydrologic and water chemistry indicators in the 2011–2014 period compared to 2015–2019, indicating an increase in the seasonality component compared to constancy (C), with a larger decrease in C/P for 2015–2019 compared to 2011–2014. The analysis further highlighted the influence of extreme hydrometeorological events on the changing predictability of hydrology and water chemistry indicators in forested streams. The results demonstrate the influence of hurricanes on hydrological behavior in forested watersheds and, thus, the seasonality and predictability of water chemistry variables within and emanating out of the watershed, potentially influencing the downstream ecosystem. The findings of this study can inform forest watershed management in response to natural or anthropogenic disturbances.

Topographic–Vegetation Interactions on an Incipient Foredune Field Post-Tropical Storm

Sand dunes protect the most important economic and ecologically critical landscapes from coastal hazards (storms and high-tide flooding). The characteristics of the dune affect their protective ability. This paper qualitatively and quantitatively assesses the relationships between pre- and post-storm conditions for vegetation and the morphology of an incipient dune system along the South Carolina coast. Field-based dune vegetation and morphology measurements were obtained before and after tropical storm Dorian (2019). Vegetation is assessed with respect to distribution and functional type, and subgroups are introduced to categorize land cover transitions. At the quadrat scale (0.2 m2) following the storm, there was a shift from stabilizer to builder, a decrease of sand (2%), and the vegetation remained consistent at around 61% of the land cover. Transect-level analysis (0.2 m × 1.0 m) revealed distinct variability concerning post-storm morphology change in the extreme study site extents. Dorian resulted in approximately 10% volumetric loss over the entire study site (101 m2). This study demonstrated changes to a dune system following a tropical storm with wind as the dominant forcing factor. This study revealed that vegetation presence is not broadly correlated with reduced levels of post-storm erosion.

Florida mangrove dieback on a decadal and centennial timescales

Hurricanes are considered some of the most devastating weather phenomena, causing deaths and destruction along the coast. Mangroves are perceived as natural defenses against coastal hazards. However, mangrove gaps, known as mangrove dieback, have occurred in southwestern Florida. This study implemented a spatial-temporal analysis based on satellite, lidar and unmanned aerial vehicle (UAV) images collected along the southwestern Florida coast between Tampa and Naples from 1994 to 2020 CE, and multi-proxy analyses on sediment cores sampled from two mangrove dieback sites to determine the cause(s) of mangrove death and the implications for the sustainability of these forests. The data indicated that out of the 86 identified dieback, 78 % arose between 2004 and 2017 CE, when one tropical storm and three hurricanes made landfall on the studied coast, suggesting hurricanes as the main driver for this mangrove degradation. Multi-proxy analysis indicated mangrove expansion since ~600 cal yr BP due to relative sea-level (RSL) rise. However, hurricanes caused losses in the mangrove area between 1930 and 1950 CE, and during the last two decades in the studied sites. Ground topographic data and aerophotogrammetry revealed circular dieback with permanent ponds (~30 cm depth) inhibiting mangrove recovery. The mangrove death occurred in <3 years, with a gradual dieback expansion due to positive feedback involving physicochemical processes in the sediments. In addition, recent hurricanes increased pre-existing dieback areas. Therefore, dieback sites are vulnerability hotspots for mangroves in the face of projected RSL rise and higher frequency of intense hurricane strikes. Mangrove dieback should be monitored on a temporal (seasonal - annual) and spatial (cm-m) resolution only possible through the combination of satellite and UAV data. Integrating remote sensing and stratigraphic analysis enabled us to identify mangrove diebacks on a decadal to centennial timescale, improving our comprehension of how catastrophic weather events affect these forests.

Performance Assessment of Three Living Shorelines in Cedar Key, Florida, USA

A community-driven effort in Cedar Key, Florida, USA, resulted in the construction of three living shoreline retrofits intended to bolster failing coastal infrastructure and restore habitat functions in Daughtry Bayou. A multi-year monitoring program tracked changes in elevation and vegetation communities across the entire shoreline profile from lower-intertidal to upland/transitional zones and measured wave attenuation during typical and extreme (hurricane) conditions. Overall, these living shoreline retrofits served to soften more than 30% of the bayou’s shoreline, dramatically reducing the extent of armored shoreline in direct contact with tidal influence. The extent of vegetated habitat area has increased at all three sites, despite sediment export from higher elevation zones driven largely by repeated impacts from hurricanes and tropical storms. These living shorelines reduced wave energy by 33 to 79% in typical conditions and by up to 28% in hurricane conditions, consistently outperforming armored shorelines, even during an extreme event (Hurricane Idalia). Our monitoring efforts were sufficient to capture project trajectories and assess performance relative to project goals, but our program had limitations that could have been overcome with additional resources and increased focus on capturing spillover effects. The living shoreline retrofit projects assessed here have persisted through and shown signs of recovery after multiple tropical storms and hurricanes, while providing important energy reduction services. Thus, living shoreline retrofits continue to be a cost-effective shoreline management strategy in the short term for this area. However, our analyses suggest that persistence of these shorelines could be threatened by the combination of sea-level rise (by 2040), upland armoring, and an increasing risk of more intense tropical systems. Therefore, future interventions should more carefully consider these threats in conjunction with habitat enhancement goals.

A Rare Tropical Cyclone Associated With Southwest Monsoon Over the Northern Part of the South China Sea—Tropical Storm Maliksi

AbstractThis study examines the characteristics and development of Tropical Storm Maliksi, which is a special case of tropical cyclone developed in the northwestern part of the South China Sea during a southwest monsoon outbreak. Detailed analyses were conducted using observational data and forecast products. Surface observations, radar wind profilers, aircraft data, and satellite products were used to evaluate Maliksi's wind structure, revealing multiple circulation centers and gale force winds. Vertical wind profiles, warm core structure, wind waves, and the influence of sea temperatures and salinity on Maliksi's intensification were investigated. Regarding forecasting, AI‐based models outperformed conventional numerical weather prediction (NWP) models in predicting Maliksi's initial development, though both struggled to capture the persistence of strong winds as the system moved inland. High‐resolution NWP simulations were employed to examine terrain‐induced wind variability around Hong Kong International Airport, revealing the mountain wake effect and uneven wind and turbulence distribution. These findings provide insights into the challenges of forecasting and monitoring such tropical cyclones, and highlight the need for enhanced observational platforms and forecasting tools along coastlines vulnerable to these systems.

Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam.

Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstanding threat to the nation's population and infrastructure. Changes in hydroclimatic conditions, especially the growing intensity and frequency of storms, have elevated landslide susceptibility in many parts of the country. This research examines the spatio-temporal variations in landslide susceptibility across central Vietnam over several years, using multi-temporal landslide inventories from Typhoon Ketsana (2009), Tropical Storm Podul (2013), and Typhoon Molave (2020). Additionally, the research explores the impact of individual landslide causative factors on the probabilistic occurrences of landslides. The post-event landslide susceptibility models of these three climate extreme events were developed using nine causative factors and a Random Forest machine learning algorithm. The results indicate a notable areal expansion of high to very high landslide susceptibility in the northern and eastern regions and a moderate reduction in the central and southern areas during the post-Molave period compared to the post-Ketsana period. These changes may be early indicators of increasing landslide susceptibility in response to changing hydro-climatic conditions. The research found that annual average rainfall and topographic elevation are the two most important variables influencing landslide prediction, showing a nonlinear relationship with landslide probability. The landslide susceptibility models achieved high Area Under the Receiver Operating Characteristic Curve (AUC) (>95%), accuracy (>89%), and sensitivity (>90%) scores, signifying the robustness of the models. Additionally, the uncertainty of the models was quantified and spatially mapped. This multi-temporal analysis of landslide susceptibility is crucial for understanding the regional susceptibility trends and identifying areas with increasing, decreasing, and consistently high susceptibility to landslides. These insights are invaluable for prioritizing mitigation and risk reduction strategies in landslide-prone regions and guiding appropriate land use planning.

Influence of CyGNSS L2 wind data on tropical cyclone analysis and forecasts in the coupled HAFS/HYCOM system

This study examines the influence of NASA Cyclone Global Navigation Satellite System (CyGNSS) Level 2-derived 10 m (near-surface) wind speed over the ocean on analyses and forecasts within the NOAA operational Hurricane Analysis and Forecast System (HAFS). HAFS is coupled with a regional configuration of the HYCOM ocean model. The primary advantages of data from the CyGNSS constellation of satellites include higher revisit frequency compared to polar-orbiting satellites, and the availability of reliable wind observations over the ocean surface during convective precipitation. CyGNSS data are available early in the life cycle of tropical cyclones (TCs) when aerial reconnaissance observations are not available. We focus on TCs whose forecasts were initialized when the TC was a depression or tropical storm. In the present study, we find first, that assimilation of CyGNSS near-surface winds improves storm track, intensity, and structure statistics in the analysis and early in the forecast, for many cases. Second, we find that assimilation of CyGNSS observations provides additional insights into the evolution of air-sea interaction in intensifying TCs: In effect, the ocean responds in the coupled model to modifications in the initial 10 m wind field, thereby impacting forecasts of intensity, storm structure, and sea surface height, as demonstrated by two case studies. We also discuss some forecasts where assimilating CYGNSS appears to degrade performance for either intensity or structure.

Spatial Variability of Dropsonde‐Derived Moist Static Energy in North Atlantic Tropical Cyclones

AbstractThe spatial variability of moist static energy (MSE) and its column‐integral (CMSE) around tropical cyclones (TCs) are known to help prognose TC development. Though limited in number and spatial coverage per TC, modeling work suggests that dropsondes, when strategically deployed, can reliably capture radial MSE and CMSE variability. This study uses North Atlantic upper‐level reconnaissance dropsondes from 1996 to 2021 to produce the most extensive observational analysis of MSE structure in TCs to date. MSE and CMSE decrease with distance from the TC center. MSE spatial variability is larger in Category 1 and 2 hurricanes compared to tropical storms, and generally largest after a TC's lifetime maximum intensity. Moisture dominates the MSE spatial variability but temperature contributes in the upper levels near the TC center. While differences in MSE spatial variability between weakening and intensifying TCs are less clear, raw MSE tends to be greater in intensifying TCs at most radii and vertical levels.

Storm frequency, magnitude, and cumulative storm beach impact along the US east coast

Abstract. This study extracted historical water level data from 12 National Oceanographic and Atmospheric Administration tide gauge stations, spanning the period from the early 20th century to 2022 from central Maine to southern Florida, in order to determine if temporal and spatial trends existed in the frequency and magnitude of storms along the US Atlantic Ocean coast. We used the Storm Erosion Potential Index (SEPI) to identify and quantify storms. We then use the timing and magnitude of those storms to determine the cumulative effect of storm clustering and large-magnitude storms on sandy beaches using the cumulative storm impact index (CSII) empirical model. The results from this study showed (1) no appreciable increase in storm frequency at any of the stations (except for sheltered stations susceptible to storm tide augmentation), (2) statistically significant but modest increases in storm magnitudes over time for 8 of the 12 tidal stations, (3) regional differences in storm magnitudes (SEPI) and cumulative storm impacts (CSII) characteristic of more frequent extratropical storms (temporal clustering) in the north and less frequent tropical storms in the south, and (4) a 4- to 10-year recovery period for regional beach recovery.

Mortality caused by tropical cyclones in the United States

Natural disasters trigger complex chains of events within human societies1. Immediate deaths and damage are directly observed after a disaster and are widely studied, but delayed downstream outcomes, indirectly caused by the disaster, are difficult to trace back to the initial event1,2. Tropical cyclones (TCs)—that is, hurricanes and tropical storms—are widespread globally and have lasting economic impacts3–5, but their full health impact remains unknown. Here we conduct a large-scale evaluation of long-term effects of TCs on human mortality in the contiguous United States (CONUS) for all TCs between 1930 and 2015. We observe a robust increase in excess mortality that persists for 15 years after each geophysical event. We estimate that the average TC generates 7,000–11,000 excess deaths, exceeding the average of 24 immediate deaths reported in government statistics6,7. Tracking the effects of 501 historical storms, we compute that the TC climate of CONUS imposes an undocumented mortality burden that explains a substantial fraction of the higher mortality rates along the Atlantic coast and is equal to roughly 3.2–5.1% of all deaths. These findings suggest that the TC climate, previously thought to be unimportant for broader public health outcomes, is a meaningful underlying driver for the distribution of mortality risk in CONUS, especially among infants (less than 1 year of age), people 1–44 years of age, and the Black population. Understanding why TCs induce this excess mortality is likely to yield substantial health benefits.

Capturing Urban Heterogeneity Enhances Tropical Cyclones Simulation in Houston

AbstractUrbanization in the coastal region has increased socioeconomic losses from landfalling tropical cyclones (TCs). Although previous studies have explored the broad impacts of urbanization on TCs, the effect of heterogeneity caused by local intra‐urban variability has not been examined. To address this gap, this study utilized the urban Local Climate Zone (LCZ) to capture the urban landscape heterogeneity and the impacts of this representation on the simulation of the post‐landfall TCs characteristics in Houston. Taking the case of two recent TCs: Hurricane Harvey (occurred in 2017) and Tropical Storm Imelda (occurred in 2019), the study evaluated the impact of urban heterogeneity on 10‐m winds, 2‐m temperature, land surface temperature, and precipitation across Houston. The consideration of intra‐urban heterogeneity using LCZ can improve the 10‐m winds, 2‐m temperature, and spatial pattern of land surface temperature. Although the cumulative rainfall remained largely similar within the experiments (with and without LCZ), incorporating intra‐urban heterogeneity notably modified the spatial structure of urban rainfall, particularly in simulating heavy rainfall hot spots. These findings are consistent for both TCs and demonstrate the positive impact of incorporating intra‐urban heterogeneity on the landfalling TC simulations over the Houston area.

Effects of nourished beach morphology on storm response

AbstractField observations on storm induced beach changes are important to improve our effort on beach management. This study compared storm induced beach changes caused by hurricane Hermine in 2016 (4 years after a beach nourishment) and Tropical Storm Eta in 2020 (2 years after a beach renourishment) along the barrier-island coast of west-central Florida. Pre-Eta beach were 1 to 2 times wider than that of pre-Hermine. Since Hurricane Hermine and TS Eta generated a similar hydrodynamic condition for the study site, comparing beach changes induced by these two storms provides a unique opportunity to investigate the response of different antecedent beach conditions to energetic events. The shore protection effect of beach nourishment is apparently evidenced by the fact that post-Eta shoreline was located seaward of those post-Hermine at half of the beach-profile locations in the study area. The shore protection effect in the subaerial portion of the beach, however, is not obvious for the other half of beach profiles where shoreline positions were retreated to similar locations after these two storms. Instead, their shore protection effect occurred in the sub-aqueous portion of the beach and was indicated by higher sandbar crests located closer to the shoreline, which can dissipate and reduce incoming wave energy. The shoreline elevation needs to be properly defined (Mean High Water vs Mean Low Water line) as it is used as a proxy to represent beach volume loss. For Hermine induced beach change, no significant correlation exists between MHW line change and beach volume loss. While a significant correlation exists between MHW line change and beach volume loss induced by TS Eta. This correlation pattern switched if the shoreline here is defined as mean low water line. For efficient beach/shoreline management, multiple proxies (e.g., sandbar height and location of its crest and trough) in addition to shoreline change should be used to assess the performance of beach nourishment project.

Detailed analysis of local climate at the CTAO-North site on La Palma from 20 yr of MAGIC weather station data

ABSTRACT The Observatorio del Roque de los Muchachos will host the northern site of the Cherenkov Telescope Array Observatory (CTAO), in an area about 200 m below the mountain rim, where the optical telescopes are located. The site currently hosts the MAGIC (Major Atmospheric Gamma-ray Imaging Cherenkov) telescopes, which have gathered a unique series of 20 yr of weather data. We use advanced profile-likelihood methods to determine seasonal cycles, the occurrence of weather extremes, weather downtime, and long-term trends correctly taking into account data gaps. The fractality of the weather data is investigated by means of multifractal detrended fluctuation analysis. The data are published according to the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. We find that the behaviour of wind and relative humidity show significant differences compared to the mountain rim. We observe an increase in temperature of $0.55\pm 0.07\mathrm{(stat.)}\pm 0.07\mathrm{(syst.)}$$^{\circ }$C decade−1, the diurnal temperature range of $0.13\pm 0.04\mathrm{(stat.)}\pm 0.02\mathrm{(syst.)}$$^{\circ }$C decade−1 (accompanied by an increase of seasonal oscillation amplitude of $\Delta C_m=0.29\pm 0.10\mathrm{(stat.)}\pm 0.04\mathrm{(syst.)}$$^{\circ }$C decade−1), and relative humidity of $4.0\pm 0.4\mathrm{(stat.)}\pm 1.1\mathrm{(syst.)}$ per cent decade−1, and a decrease in trade wind speeds of $0.85\pm 0.12\mathrm{(stat.)}\pm 0.07\mathrm{(syst.)}$ (km h−1) decade−1. The occurrence of extreme weather, such as tropical storms and long rains, remains constant over time. We find a significant correlation of temperature with the North Atlantic Oscillation Index and multifractal behaviour of the data. The site shows a weather-related downtime of 18.5 per cent–20.5 per cent, depending on the wind gust limits employed. No hints are found of a degradation of weather downtime under the assumption of a linear evolution of environmental parameters over time.

Spatiotemporal Climatology of Georgia Tropical Cyclones and Associated Rainfall

Tropical cyclones (TCs), often characterized by high wind speeds and heavy rainfall, cause widespread devastation, affecting millions of people and leading to economic losses worldwide. TC-specific research in Georgia is scarce, likely due to the minimal geographical extent of its coast and the infrequency of direct landfalls. Research on Georgia TCs does not account for storms that make landfall in other southeastern states (e.g., Florida) and continue north, northeast, or northwest into Georgia. This study used the North Atlantic Basin hurricane database (HURDAT2) to quantify the spatiotemporal patterns of direct and indirect landfalling of Georgia tropical cyclones (&gt;16 ms−1) from 1851 to 2021. TC-induced rainfall was also quantified using rainfall data (nClimGrid-Daily and nClimGrid) from 1951 to 2021 to estimate the proportion of Georgia’s total annual and monthly rainfall attributed to TCs. A multi-methodological approach, incorporating statistics and mapping, is employed to assess the trends of Georgia’s tropical cyclones and the associated rainfall. The study analyzed 113 TCs and found that, on average, less than one TC annually (x¯ = 0.66) traverses the state. September averaged the highest percentage (25%) of TC-induced rainfall, followed by October (14%), and August (13%). This pattern aligns with the TC season, with the highest frequency of TCs occurring in September (n = 35), followed by August (n = 25), and October (n = 18). We found that 10% of tropical storms make landfall on the coastline, while the remaining 91% enter Georgia by making landfall in Florida (92%), Louisiana (7%), or South Carolina (1%) first. A threat of TCs during the peak of the season emphasizes the importance of heightened awareness, increased planning practices, and resource allocation during these periods to protect Georgia’s history and natural beauty, and its residents.

On the Spirality of the Asymmetric Rain Field of Tropical Cyclones Under Vertical Wind Shear

AbstractThe downshear‐left enhancement of tropical cyclone rainfall has been demonstrated previously, but the radial dependence of this effect was not analyzed in detail. This study quantifies the progressive upwind shift of the wavenumber‐1 maximum rain position with radius relative to the vertical wind shear direction. This shift is visualized as a distinctive upwind spiral of the maximum. It is shown that this spiral pattern is generally observed across various storm intensities, shear strength, and ocean basins. Detailed examination revealed that the maximum downwind deflection angle of the wavenumber‐1 rain maximum relative to the shear direction is smaller for tropical storms than hurricanes, but insensitive to hurricane intensity. It is proposed that the spirality is produced by a continuous decline in angular advection of air parcels with radius. The stability of the deflection angle in hurricanes may be accounted for by a corresponding increase in vertical ascent under strengthening angular flow.

Assessing South Indian Ocean tropical cyclone characteristics in HighResMIP simulations

AbstractSeveral damaging tropical cyclones (TCs) have occurred recently over the South Indian Ocean (SIO) region, causing enormous social and economic losses. Yet, while many studies have examined SIO TC characteristics using observations and reanalysis, only a few have assessed these characteristics specifically for this region in climate models, and fewer have investigated their projections under climate change. Here we do this for a historical (1980–2010) and future (2020–2050) period, using multimodel simulations from the High Resolution Model Intercomparison Project, as well as examine biases in the historical period relative to a reanalysis (ERA5). The models have horizontal resolutions of 25–50 km, which has enabled an improved ability to represent tropical cyclones globally in previous studies. TempestExtremes software is employed to detect tropical storm and cyclone tracks. In cases where TempestExtremes cannot be applied due to a lack of requisite variables in a dataset, we instead examine extreme wind speeds in that dataset. For the historical period, we find considerable variation in model biases compared to ERA5, which itself exhibits realistic spatial patterns of tracks and their monthly distribution. Models do at least agree on positive biases in track frequency east of Madagascar and somewhat in the Mozambique Channel. However, the models and ERA5 only produce Category 3 tropical cyclones at best. Wind speeds for 25 km resolution models have much larger positive biases than for 50 km ones, suggesting the former can simulate even higher‐category tropical cyclones. Considerable intermodel variation is also found in track changes between the future and historical periods. No systematic intercategory pattern of change exists, and low signal‐to‐noise may obscure any such patterns in the limited timespan of available data. Thus, no meaningful conclusions can be drawn regarding changes in track intensity. Nevertheless, track frequency broadly decreases across models for the region, as does accumulated cyclone energy. An east‐to‐west shift in track location from east of Madagascar toward the Mozambique Channel is also implied by track frequency and wind speed changes. Our findings provide information to potentially improve storm resiliency in this vulnerable region.

Using Satellite Observations of Lightning and Precipitation to Diagnose the Behavior of Deep Convection in Tropical Cyclones Traversing the Midlatitudes

AbstractThis study uses a unique combination of geostationary and low‐Earth orbiting satellite‐based lightning and precipitation observations, respectively, to examine the evolution of deep convection during the tropical cyclone (TC) lifecycle. The study spans the 2018–2021 Atlantic Basin hurricane seasons and is unique as it provides the first known analysis of total lightning (intra‐cloud and cloud‐to‐ground) observed in TCs through their extratropical transition and post‐tropical cyclone (PTC) phases. We consider the TC lifecycle stage, geographic location (e.g., land, coast, and ocean), shear strength, and quadrant relative to the storm motion and environmental shear vectors. Total lightning maxima are found in the forward right quadrant relative to storm motion and downshear of the TC center, consistent with previous studies using mainly cloud‐to‐ground lightning. Increasing environmental shear focuses the lightning maxima to the downshear right quadrant with respect to the shear vector in tropical storm phases. Vertical profiles of radar reflectivity from the Global Precipitation Measurement mission show that super‐electrically active convective precipitation features (&gt;75 flashes) within the PTC phase of TCs have deeper mixed phase depths and higher reflectivity at −10°C than other phases, indicating the presence of more intense convection. Differences in the net convective behavior observed throughout TC evolution manifest in both the TC‐scale frequency of lightning‐producing cells and the intensity variations amongst individual convective cells. The combination of continuous lightning observations and precipitation snapshots improves our understanding of convective‐scale processes in TCs, especially in PTC phases, as they traverse the tropics and mid‐latitudes.

Buffalo Bayou Watershed Near Katy Flood Analysis

Buffalo Bayou, originating near Katy, Texas, is a vital watercourse within the Houston metropolitan area, traversing diverse urban, suburban, and rural landscapes. This paper investigates the flood mechanisms impacting the Buffalo Bayou watershed, focusing on significant flood events and various flood mitigation methods. Key historical floods, such as those caused by Tropical Storm Allison (2001), the Memorial Day Flood (2015), the Tax Day Flood (2016), and Hurricane Harvey (2017), underscore the region’s vulnerability to intense rainfall and storm systems. By examining a 20-year period of daily streamflow and climate data, this study employs the bucket model to simulate long-term discharge and predict flood occurrences. The results highlight the critical need for effective flood mitigation strategies, including the use of reservoirs, green infrastructure, and infrastructure improvements. The study aims to enhance flood management practices and community resilience within the Buffalo Bayou watershed, offering insights into the dynamic interplay between natural hydrological processes and human interventions.