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The design of coastal protection measures and the quantification of coastal risks at locations affected by tropical cyclones (TCs) are often based solely on the analysis of historical cyclone tracks. Due to data scarcity and the random nature of TCs, the assumption that a hypothetical TC could hit a neighboring area with equal likelihood to past events can potentially lead to over- and/or underestimations of extremes and associated risks. The simulation of numerous synthetic TC tracks based on (historical) data can overcome this limitation. In this paper, a new method for the generation of synthetic TC tracks is proposed. The method has been implemented in the highly flexible open-source Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE). TCWiSE uses an empirical track model based on Markov chains and can simulate thousands of synthetic TC tracks and wind fields in any oceanic basin based on any (historical) data source. Moreover, the tool can be used to determine the wind extremes, and the output can be used for the reliable assessment of coastal hazards. Validation results for the Gulf of Mexico show that TC patterns and extreme wind speeds are well reproduced by TCWiSE. [ABSTRACT FROM AUTHOR]

The Hurricane Weather Research and Forecasting Model (HWRF) was the flagship hurricane model at NOAA's National Centers for Environmental Prediction for 16 years and a state-of-the-art tool for tropical cyclone (TC) intensity prediction at the National Weather Service and across the globe. HWRF was a joint development between NOAA research and operations, specifically the Environmental Modeling Center and the Atlantic Oceanographic and Meteorological Laboratory. Significant support also came from the National Hurricane Center, Developmental Testbed Center, University Corporation for Atmospheric Research, universities, cooperative institutes, and the TC community. In the North Atlantic basin, where most improvement efforts focused, HWRF intensity forecast errors decreased by 45%–50% at many lead times between 2007 and 2022. These large improvements resulted from increases in horizontal and vertical resolution, as well as advances in model physics and data assimilation. HWRF intensity forecasts performed particularly well over the Gulf of Mexico in recent years, providing useful guidance for a large number of impactful landfalling hurricanes. Such advances were made possible not only by significant gains in computing but also through substantial investment from the Hurricane Forecast Improvement Program. SIGNIFICANCE STATEMENT: HWRF is considered one of the most important and successful ocean-coupled, regional numerical weather prediction models. This work documents HWRF forecast performance for TCs in the North Atlantic since its operational inception (2007–22). Track, intensity, and storm size (wind radii) forecasts all showed significant error reductions and skill improvements, including 45%–50% lower intensity errors. HWRF intensity forecasts showed marked improvement for rapid intensification events, especially in the Gulf of Mexico, where numerous impactful TCs made landfall throughout HWRF's lifetime. HWRF's impressive performance led to its expanded use as guidance for official TC forecasts and as a research tool across the TC community. These successes paved the way for NOAA's next-generation hurricane model, the Hurricane Analysis and Forecast System. [ABSTRACT FROM AUTHOR]

The impact of surface wave assimilation on hurricane track and intensity forecasts has been investigated using a fully coupled air-ocean-wave tropical cyclone data assimilation and forecast modeling system. A new 3DVAR wave assimilation method in the Navy Coupled Ocean Data Assimilation system (NCODA) maps the 1D wave energy spectra from buoys to 2D directional wave energy spectra using the maximum likelihood method (MLM) and corrects the wave model forecast component directional wave energy spectra. The Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclone Prediction (COAMPS-TC) is used to conduct three Hurricane Harvey (2017) airocean-wave coupled data assimilation and forecasting experiments with and without the wave data assimilation. Hurricane Harvey traversed through the Western Gulf of Mexico from 24 August to 1 September, 2017 and made landfall in the Texas and Louisiana coast. Validation of track, maximum wind speed, significant wave height, and mean absolute wave periods show wave assimilation of the 1D wave energy spectra from 13 National Data Buoy Center (NDBC) buoys reduced the forecast errors of these parameters compared to experiments without the wave assimilation. In spite of this positive outcome, the wave assimilation is unable to reduce Harvey's 0-120 h forecast mean wave direction errors and correlation compared to the NDBC buoy time series. [ABSTRACT FROM AUTHOR]

The design of coastal protection measures and the quantification of coastal risks at locations affected by tropical cyclone (TC) are often based solely on the analysis of historical cyclone tracks. Due to data scarcity and the random nature of TCs, the assumption that future TCs could hit a neighboring area with equal likelihood than past events can potentially lead to over- and/or underestimations of extremes and associated risks. The simulation of numerous synthetic TC tracks based on (historical) data can overcome this limitation. In this paper, a new method for the generation of synthetic TC tracks is proposed. The method has been implemented in the highly flexible open-source Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE). TCWiSE uses an Empirical Track Model based on Markov-chains and can simulate thousands of synthetic TC tracks and wind fields in any oceanic basin based on any (historical) data source. Moreover, the tool can be used to determine the wind extremes and the output can be used for the reliable assessment of coastal hazards. Validation results for the Gulf of Mexico show that TC patterns and extreme wind speeds are well reproduced by TCWiSE. [ABSTRACT FROM AUTHOR]

Intense tropical cyclones (TCs) can cause catastrophic damage to coastal regions after landfall. Recent studies have linked the devastation associated with TCs to climate change, which induces favorable conditions, such as increasing sea-surface temperature, to supercharge storms. Meanwhile, environmental factors, such as atmospheric aerosols, also impact the development and intensity of TCs, but their effects remain poorly understood, particularly coupled with ocean dynamics. Here, we quantitatively assess the aerosol microphysical effects and aerosol-modified ocean feedbacks during Hurricane Katrina using a cloud-resolving atmosphere–ocean coupled model: Weather Research and Forecasting (WRF) in conjunction with the Regional Ocean Model System (ROMS). Our model simulations reveal that an enhanced storm destructive power, as reflected by larger integrated kinetic energy, heavier precipitation, and higher sea-level rise, is linked to the combined effects of aerosols and ocean feedbacks. These effects further result in an expansion of the storm circulation with a reduced intensity because of a decreasing moist static energy supply and enhancing vorticity Rossby wave outward propagation. Both accumulated precipitation and storm surge are enhanced during the mature stage of the TC with elevated aerosol concentrations, implying exacerbated flood damage over the polluted coastal region. The ocean feedback following the aerosol microphysical effects tends to mitigate the vertical mixing cooling in the ocean mixing layer and offsets the aerosol-induced storm weakening by enhancing cloud and precipitation near the eyewall region. Our results highlight the importance of accounting for the effects of aerosol microphysics and ocean-coupling feedbacks to improve the forecast of TC destructiveness, particularly near the heavily polluted coastal regions along the Gulf of Mexico. [ABSTRACT FROM AUTHOR]

Several hypotheses have been put forward for the mechanisms of generation of surface circulation associated with tropical cyclones. This paper examines high-resolution simulations of Tropical Storm Gert (2005), which formed in the Gulf of Mexico during NASA’s Tropical Cloud Systems and Processes Experiment, to investigate the development of low-level circulation and its relationship to the precipitation evolution. Two simulations are examined: one that better matches available observations but underpredicts the storm’s minimum sea level pressure and a second one that somewhat overintensifies the storm but provides a set of simulations that encapsulates the overall genesis and development characteristics of the observed storm. The roles of convective and stratiform precipitation processes within the mesoscale precipitation systems that formed Gert are discussed. During 21–25 July, two episodes of convective system development occurred. In each, precipitation system evolution was characterized by intense and deep convective upward motions followed by increasing stratiform-type vertical motions (upper-level ascent, low-level descent). Potential vorticity (PV) in convective regions was strongest at low levels while stratiform-region PV was strongest at midlevels, suggesting that convective processes acted to spin up lower levels prior to the spinup of middle levels by stratiform processes. Intense vortical hot towers (VHTs) were prominent features of the low-level cyclonic vorticity field. The most prominent PV anomalies persisted more than 6 h and were often associated with localized minima in the sea level pressure field. A gradual aggregation of the cyclonic PV occurred as existing VHTs near the center continually merged with new VHTs, gradually increasing the mean vorticity near the center. Nearly concurrently with this VHT-induced development, stratiform precipitation processes strongly enhanced the mean inflow and convergence at middle levels, rapidly increasing the midlevel vorticity. However, the stratiform vertical motion profile is such that while it increases midlevel vorticity, it decreases vorticity near the surface as a result of low-level divergence. Consequently, the results suggest that while stratiform precipitation regions may significantly increase cyclonic circulation at midlevels, convective vortex enhancement at low to midlevels is likely necessary for genesis. [ABSTRACT FROM AUTHOR]

Using 42 years of reanalysis data, we investigate regional, storm‐relative characteristics of three groups of Atlantic tropical cyclone intensification: slightly, moderately, and rapidly intensifying. Probability density functions are distinct between these groups for vertical wind shear, sea surface temperature (SST), and radius of maximum winds (RMW), but less so for relative humidity (RH). In the Gulf of Mexico and southern North Atlantic, shear and RMW are good predictors. In the open Atlantic, north of 22°N, shear and SST are the best predictors. In the Caribbean, weaker relationships suggest low statistical predictability in a region where RI cases increased between 1980–2000 and 2001–2021. Of our storm‐relative variables tested, increasing SST appears to be most closely connected to the 36% increase in rapidly intensifying events between the two periods, whereas shear and RH are not significantly more favorable. The variability across regions, periods, and variables motivates further investigation. Plain Language Summary: Although many damaging Atlantic tropical cyclones intensify rapidly during their lifetime, forecasting how rapidly they will intensify remains difficult. To address this, we need to better understand whether the conditions in a storm's environment can help identify whether it will intensify rapidly or more slowly, and whether these results change in different regions. Using 42 years of data, we find that wind shear (change in wind speed and direction with height) and ocean temperature are useful to discriminate whether a storm may intensify rapidly versus slowly across the basin, although there is variability in the results. Humidity is less useful. Our results vary by region. The Caribbean shows lower discrimination between intensification rates, highlighting potential difficulties in predicting intensification in this region. This is concerning since the number of rapidly intensifying events has risen sharply in the Caribbean between 1980–2000 and 2001–2021. We also find that the trends in intensifying storms during these 21‐year periods vary by region. The most consistent signal related to the rise in intensifying events is the increasing ocean temperature. Key Points: Atlantic basin rapid intensification trends vary by region, with the greatest increases between 1980–2000 and 2001–2021 south of 22°NWind shear, sea surface temperature, and radius of maximum winds are useful discriminators between intensification ratesStorm‐relative environmental variable trends vary by region, with sea surface temperatures often related to regional intensity change trends [ABSTRACT FROM AUTHOR]

The impact of the high space-temporal variability of the wind field during the moderate and intense storm stages of a tropical cyclone on the wave field as computed by the numerical model WaveWatch III is investigated in this work. The realistic wind fields are generated by a high-resolution implementation of the HWRF model in the Gulf of Mexico and stored over 15 min intervals. The spatial structure of the wind field computed by HWRF is highly variable in space and time, although its mean structure is very similar to that described for parametric hurricanes already specified in the previous studies. The resulting storm-generated wave fields have a persistent structure, with wave maxima present in the forward quadrants of the storm and in the rear quadrant II. This structure is determined by the strong winds and the extended fetch condition in quadrants I and II, as well as by the translation speed of the storm. When a shorter time interval is analyzed (e.g., a 3 h period, when the storm becomes a category 1 hurricane), the structure of the mean wind field may differ greatly from the mean field calculated with a sufficiently longer period; however, the spatial distribution of the wave field around the hurricane tends to maintain its typical spatial structure. The use of wind fields with reduced time variability (e.g., with a 3 h moving average) does not change the structure of the mean wave field, but reduces the mean wave height values by up to 10%. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) can transport birds and insects near their center of circulation. In this study, we examined the maximum altitude, area and density of the radar‐derived bioscatter signature across a set of 42 TC centers of circulation sampled from 2011 to 2020. All TC events contained at least one time when a bioscatter signature was present. More intense hurricanes with closed eyes typically had taller and denser bioscatter signatures, and sometimes larger areas dominated by bioscatter. This indicated a larger number of organisms within the circulation of more intense hurricanes, supporting the speculation that those storms were most likely to trap birds that do not want to risk flying through their eyewall thunderstorms. Larger and denser bioscatter signatures, indicating a larger number of birds, tend to occur when fall migration brings a large bird population to the Gulf and East Coasts where most storms were sampled. TC formation location was not related to bioscatter characteristics, but storms sampled in the Gulf of Mexico and Florida tended to have larger and denser bioscatter signatures. [ABSTRACT FROM AUTHOR]

The active 2020 Atlantic hurricane season produced 30 named storms, 14 hurricanes, and 7 major hurricanes (category 3+ on the Saffir–Simpson hurricane wind scale). Though the season was active overall, the final two months (October–November) raised 2020 into the upper echelon of Atlantic hurricane activity for integrated metrics such as accumulated cyclone energy (ACE). This study focuses on October–November 2020, when 7 named storms, 6 hurricanes, and 5 major hurricanes formed and produced ACE of 74 × 104 kt2 (1 kt ≈ 0.51 m s−1). Since 1950, October–November 2020 ranks tied for third for named storms, first for hurricanes and major hurricanes, and second for ACE. Six named storms also underwent rapid intensification (≥30 kt intensification in ≤24 h) in October–November 2020—the most on record. This manuscript includes a climatological analysis of October–November tropical cyclones (TCs) and their primary formation regions. In 2020, anomalously low wind shear in the western Caribbean and Gulf of Mexico, likely driven by a moderate-intensity La Niña event and anomalously high sea surface temperatures (SSTs) in the Caribbean, provided dynamic and thermodynamic conditions that were much more conducive than normal for late-season TC formation and rapid intensification. This study also highlights October–November 2020 landfalls, including Hurricanes Delta and Zeta in Louisiana and in Mexico and Hurricanes Eta and Iota in Nicaragua. The active late season in the Caribbean would have been anticipated by a statistical model using the July–September-averaged ENSO longitude index and Atlantic warm pool SSTs as predictors. [ABSTRACT FROM AUTHOR]

Paleohurricane reconstructions extend the observational record of tropical cyclones (TCs) back thousands of years. However, these records are subject to biases–capturing only close‐moving intense storms at varying resolutions. We devise two pseudo proxy networks drawing from the full suite of published paleohurricane studies in the North Atlantic. We run synthetic storms forced with two global climate model simulations of the past millennium through each pseudo network to assess the theoretical skill of paleohurricane proxies at capturing low‐frequency variability in North Atlantic basin‐wide and intrabasin TCs. We find that basin‐wide and paleohurricane compiled TC counts are significantly correlated with one another for the past millennium on annual to multi‐decadal timescales, but compilation skill is limited by proxy temporal resolution. Current paleohurricane proxy networks predominantly capture storms moving in the Caribbean/Gulf of Mexico. Increasing the quantity of paleohurricane records from the North American coastline substantially improves reconstruction skill. Plain Language Summary: As our climate warms, we need to understand how the statistics of Atlantic hurricanes will change. Scientists use natural archives, such as sediment and tree cores, to reconstruct Atlantic hurricane frequency over the past couple of thousand years. These natural archives, also known as paleohurricane proxies, are biased; they only record storms that move close to the coring site at a high intensity. Over the past few decades, scientists have amassed large networks of paleohurricane proxies from coastlines in the western North Atlantic. Here, we use two different sets of synthetic hurricanes to test if a compilation of the current network of paleohurricane proxies will smooth out the biases of each individual site and provide an accurate representation of Atlantic basin‐wide hurricane frequency over the past 1,000 years. We find that current network of paleohurricane records can be used to reconstruct past Atlantic hurricanes, but most of the current sites only capture storms that form/move through the Caribbean Sea and the Gulf of Mexico. We can improve our estimates of past hurricanes in future work by adding more sites from the U.S. Southeast and Central America. Key Points: The current network of paleohurricane proxies captures annual to multi‐decadal scale variability in Atlantic tropical cyclone (TC) frequencyPaleohurricane records predominantly capture storms that impact the U.S. Gulf Coast and Caribbean SeaMore paleohurricane records, especially from the U.S. Southeast, are needed to reconstruct recurving TCs [ABSTRACT FROM AUTHOR]

While North Atlantic tropical cyclone (TC) forecasts are numerous, the number of Gulf of Mexico (GOM) storms is normally left ambiguous. Motivated by the 2020 GOM hurricane season, this study introduces two methods of anticipating upcoming GOM TC frequency on June 1 of each year: (a) statistically transforming Climate Forecast System (CFS)‐predicted June–November GOM 500‐hPa temperature (T500); and (b) applying a 0.284 multiplier, the climatological proportion of GOM versus North Atlantic TCs, to a representative, widely circulated North Atlantic‐wide forecast. Both methods perform skillfully, especially given their simplicity. Though warm T500 normally inhibits deep convection and is not generally considered among statistical TC forecasts, it is comparatively well represented by modeling systems. Additionally, T500 is well correlated with traditional, yet less accurately resolved, TC environmental parameters. While unfavorable to individual TCs, T500 generally (though indirectly) indicates several difficult‐to‐model physical aspects of more favorable GOM TC environments. Plain Language Summary: Seasonal forecasts of North Atlantic tropical cyclone (TC) activity have become quite common in recent years. Unfortunately, the number of Gulf of Mexico (GOM) storms is not often stated among North Atlantic‐wide forecasts. Consequently, this study introduces two methods of anticipating upcoming GOM TC frequency at the first day of hurricane season. The first is based solely on June–November midlevel temperatures over the GOM predicted by the Climate Forecast System (CFS), version 2. The second applies a 0.284 multiplier, the climatological proportion of GOM TCs within the North Atlantic, to a widely circulated North Atlantic‐wide forecast. Both methods perform skillfully, especially given their simplicity. Though warm midlevel temperature is not generally considered among statistical TC forecasts, we show that it is comparatively well modeled by the reanalysis/forecast systems, and is correlated to other TC‐related variables that are less accurately resolved. Midlevel temperature provided the greatest gain in performance over the scaling factor for the most active GOM hurricane seasons. Key Points: The Gulf of Mexico (GOM) encounters 28.4% of all North Atlantic tropical cyclonesGOM named storm counts are significantly positively correlated with 500‐hPa temperatureClimate Forecast System (CFS) predictions of GOM 500‐hPa temperature were accurate, skillful indications of subsequent named storm activity [ABSTRACT FROM AUTHOR]

The development of high-resolution, fully coupled, regional Earth system model systems is important for improving our understanding of climate variability, future projections, and extreme events at regional scales. Here we introduce and present an overview of the newly developed Regional Community Earth System Model (R-CESM). Different from other existing regional climate models, R-CESM is based on the Community Earth System Model version 2 (CESM2) framework. We have incorporated the Weather Research and Forecasting (WRF) Model and Regional Ocean Modeling System (ROMS) into CESM2 as additional components. As such, R-CESM can be conveniently used as a regional dynamical downscaling tool for the global CESM solutions or/and as a standalone high-resolution regional coupled model. The user interface of R-CESM follows that of CESM, making it readily accessible to the broader community. Among countless potential applications of R-CESM, we showcase here a few preliminary studies that illustrate its novel aspects and value. These include 1) assessing the skill of R-CESM in a multiyear, high-resolution, regional coupled simulation of the Gulf of Mexico; 2) examining the impact of WRF and CESM ocean–atmosphere coupling physics on tropical cyclone simulations; and 3) a convection-permitting simulation of submesoscale ocean–atmosphere interactions. We also discuss capabilities under development such as (i) regional refinement using a high-resolution ROMS nested within global CESM and (ii) "online" coupled data assimilation. Our open-source framework (publicly available at https://github.com/ihesp/rcesm1) can be easily adapted to a broad range of applications that are of interest to the users of CESM, WRF, and ROMS. [ABSTRACT FROM AUTHOR]

The destructive power of tropical cyclones is driven by latent heat released from water condensation and is inevitably linked to the abundance of aerosols as cloud condensation nuclei. However, the aerosol effects are unaccounted for in most operational hurricane forecast models. We combined multisource measurements and cloud‐resolving model simulations to show fundamentally altered cloud microphysical and thermodynamic processes by anthropogenic aerosols during Hurricane Harvey. Our observational analyses reveal intense lightning and precipitation in the proximity of Houston industrial areas, and these hot spots exhibit a striking geographic similarity to a climatological maximum of lightning flash density in the south‐central United States. Our ensemble cloud‐resolving simulations of Hurricane Harvey indicate that aerosols increase precipitation and lightning by a factor of 2 in the Houston urban area, unraveling the key anthropogenic factor in regulating flooding during this weather extreme. Plain Language Summary: The catastrophic flooding during Hurricane Harvey has received major attention, but the cause remains mysterious. The destructive power of tropical cyclones is produced by the latent heat release from phase change of water, which is linked to airborne particles emitted from vehicles and petrochemical plants. By combining observation and model simulations, our work provides microphysical and thermodynamic insights into the cause of the catastrophic flooding during Hurricane Harvey by the aerosols from industrial sources. Our discovery underscores the importance of representing the effects of anthropogenic aerosols for accurate short‐term forecast and climate projection of tropical cyclones to minimize future catastrophic destruction along the highly industrialized Gulf of Mexico region. Key Points: Aerosol increases accumulative precipitation by a factor of 2T and invigorates lightning activities in Houston during Hurricane HarveyObservations show intense lightning over Houston which exhibits geographic similarity to climatological maximum lightning flash densityTo better forecast extreme weather events, it is essential to account for aerosol effects in operational weather forecast models [ABSTRACT FROM AUTHOR]

The FV3GFS is the current operational Global Forecast System (GFS) at the National Centers for Environmental Prediction (NCEP), which combines a finite-volume cubed sphere dynamical core (FV3) and GFS physics. In this study, FV3GFS is used to gain understanding of rapid intensification (RI) of tropical cyclones (TCs) in shear. The analysis demonstrates the importance of TC structure in a complex system like Hurricane Michael, which intensified to a category 5 hurricane over the Gulf of Mexico despite over 20 kt (10 m s−1) of vertical wind shear. Michael's RI is examined using a global-nest FV3GFS ensemble with the nest at 3-km resolution. The ensemble shows a range of peak intensities from 77 to 159 kt (40–82 m s−1). Precipitation symmetry, vortex tilt, moisture, and other aspects of Michael's evolution are compared through composites of stronger and weaker members. The 850–200-hPa vertical shear is 22 kt (11 m s−1) in the mean of both strong and weak members during the early stage. Tilt and moisture are two distinguishing factors between strong and weak members. The relationship between vortex tilt and humidification is complex, and other studies have shown both are important for sheared intensification. Here, it is shown that tilt reduction leads to upshear humidification and is thus a driving factor for intensification. A stronger initial vortex and early evolution of the vortex also appear to be the key to members that are able to resist the sheared environment. [ABSTRACT FROM AUTHOR]

A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in U.S. landfalling systems. Here, the authors present a tentative study that examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1°-0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and subtropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks' seasonality, intensity, and power dissipation index in each cluster are documented for both configurations. The authors' results show that, except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. The authors also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, the authors examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others. [ABSTRACT FROM AUTHOR]

The authors develop a statistical guidance product, the tropical cyclone tornado parameter (TCTP), for forecasting the probability of one or more tornadoes during a 6-h period that are associated with landfalling tropical cyclones affecting the coastal Gulf of Mexico and the southern Atlantic coast. TCTP is designed to aid forecasters in a time-limited environment. TCTP provides a 'quick look' at regions where forecasters can then conduct detailed analyses. The pool of potential predictors included tornado reports and tropical cyclone data between 2000 and 2008, as well as storm environmental parameters. The original pool of 28 potential predictors is reduced to six using stepwise regression and logistic regression. These six predictors are 0-3-km wind shear, 0-3-km storm relative helicity, azimuth angle of the tornado report from the tropical cyclone, distance from the cyclone's center, time of day, and 950-1000-hPa convective available potential energy. Mean Brier scores and Brier skill scores are computed for the entire TCTP-dependent dataset and for corresponding forecasts produced by the Storm Prediction Center (SPC). TCTP then is applied to four individual cyclone cases to qualitatively and quantitatively assess the parameter and compare its performance with SPC forecasts. Results show that TCTP has skill at identifying regions of tornado potential. However, tornadoes in some tropical systems are overpredicted, but underpredicted in others. TCTP 6-h forecast periods provide slightly poorer statistical performance than the 1-day tornado probability forecasts from SPC, probably because the SPC product includes forecaster guidance and because their forecasts are valid for longer periods (24 h). [ABSTRACT FROM AUTHOR]

The ocean mixed layer response to a tropical cyclone within and immediately adjacent to the Gulf of Mexico Loop Current is examined. In the first of a two-part study, a comprehensive set of temperature, salinity, and current profiles acquired from aircraft-deployed expendable probes is utilized to analyze the three-dimensional oceanic energy evolution in response to Hurricane Lili's (2002) passage. Mixed layer temperature analyses show that the Loop Current cooled <1°C in response to the storm, in contrast to typically observed larger decreases of 3°-5°C. Correspondingly, vertical current shear associated with mixed layer currents, which is responsible for entrainment mixing of cooler water, was found to be up to 50%% weaker, on average, than observed in previous studies within the directly forced region. The Loop Current, which separates the warmer, lighter Caribbean Subtropical Water from the cooler, heavier Gulf Common Water, was found to decrease in intensity by −0.18 ± 0.25 m s−1 over an approximately 10-day period within the mixed layer. Contrary to previous ocean response studies, which have assumed approximately horizontally homogeneous ocean structure prior to storm passage, a kinetic energy loss of 5.8 ± 6.4 kJ m−2, or approximately −1 wind stress-scaled energy unit, was observed. By examining near-surface currents derived from satellite altimetry data, the Loop Current is found to vary similarly in magnitude over such time scales, suggesting storm-generated energy is rapidly removed by the preexisting Loop Current. In a future study, the simulated mixed layer evolution to a Hurricane Lili-like storm within an idealized preexisting baroclinic current is analyzed to help understand the complex air-sea interaction and resulting energetic response. [ABSTRACT FROM AUTHOR]

Sources of dynamical model track error for Hurricane Ike (2008) in the Gulf of Mexico are examined. Deterministic and ensemble model output are compared against National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analyses to identify potential critical features associated with the motion of Ike and its eventual landfall along the upper Texas coast. Several potential critical features were identified, including the subtropical ridge north of Ike and several synoptic-scale short-wave troughs and ridges over central and western North America, and Tropical Storm Lowell in the eastern North Pacific. Using the NCEP Gridpoint Statistical Interpolation (GSI) data assimilation scheme, the operational GSI analysis from the 0000 UTC 9 September 2008 cycle was modified by perturbing each of these features individually, and then integrating the GFS model using the perturbed initial state. The track of Ike from each of the perturbed runs was compared to the operational GFS and it was found that the greatest improvements to the track forecast were associated with weakening the subtropical ridge north of Ike and strengthening a midlevel short-wave trough over California. A GFS run beginning with an analysis where both of these features were perturbed produced a greater track improvement than either did individually. The results suggest that multiple sources of error exist in the initial states of the operational models, and that the correction of these errors in conjunction with reliable ensemble forecasts would lead to improved forecasts of tropical cyclone tracks and their accompanying uncertainty. [ABSTRACT FROM AUTHOR]

The strongest hurricanes over the North Atlantic Ocean are getting stronger, with the increase related to rising ocean temperature. Here, the authors develop a procedure for estimating future wind losses from hurricanes and apply it to Eglin Air Force Base along the northern coast of Florida. The method combines models of the statistical distributions for extreme wind speed and average sea surface temperature over the Gulf of Mexico with dynamical models for tropical cyclone wind fields and damage losses. Results show that the 1-in-100-yr hurricane from the twentieth century picked at random to occur in the year 2100 would result in wind damage that is 36%% [(13%%, 76%%) == 90%% confidence interval] greater solely as a consequence of the projected warmer waters in the Gulf of Mexico. The method can be applied elsewhere along the coast with modeling assumptions modified for regional conditions. [ABSTRACT FROM AUTHOR]

The life cycle of a North Atlantic cyclone in December 2005 that included a rapid propagation phase as a diabatic Rossby wave (DRW) is investigated by means of operational analyses and deterministic forecasts from the ECMWF. A quasigeostrophic omega diagnostic has been applied to assess the impact of upper-level forcing during the genesis, propagation, and intensification phase, respectively. The system was generated in the Gulf of Mexico as a mesoscale convective vortex (MCV) influenced by vertical motion forcing from a nearby upper-level trough. The DRW propagation phase was characterized by a shallow, low-level, diabatically produced potential vorticity (PV) anomaly that rapidly propagated along the southern border of an intense baroclinic zone. No significant upper-level forcing could be identified during this phase of the development. Eventually, explosive intensification occurred as the region of vertical motion forced by an approaching upper-level trough reached the position of the DRW. The rapid intensification of 34 hPa in 24 h led to a mature extratropical cyclone in the central North Atlantic with marked frontal structures associated with a pronounced PV tower. The performance of four operational deterministic ECMWF forecasts has been investigated for the DRW propagation and cyclone intensification. The forecasts showed a highly variable skill. Despite the fact that the DRW was initially well represented in all forecasts, two of them failed to capture the explosive intensification. By applying a DRW tracking tool, the low-level baroclinicity downstream of the DRW and the moisture supply to the south of the DRW could be identified as the key environmental parameters during DRW propagation. The subsequent cyclone intensification went wrong in two of the forecasts because of the missing interaction of the DRW and the upper-level trough. It is shown that this interaction can fail if the intensity of the DRW and/or the approaching upper-level wave are too weak, or in case of an erroneous structure of the upper-level trough leading to a phasing problem of the vertical interaction with the DRW. Therefore, the DRW intensification bears similar characteristics and forecast challenges as the extratropical reintensification of tropical cyclones. [ABSTRACT FROM AUTHOR]

Unprecedented numbers of tropical cyclones occurred in the North Atlantic Ocean and the Gulf of Mexico in 2005. This provides a unique opportunity to evaluate the performance of two operational regional wave forecasting models at the National Centers for Environmental Prediction (NCEP). This study validates model predictions of the tropical cyclone-generated maximum significant wave height, simultaneous spectral peak wave period, and the time of occurrence against available buoy measurements from the National Data Buoy Center (NDBC). The models used are third-generation operational wave models: the Western North Atlantic wave model (WNA) and the North Atlantic Hurricane wave model (NAH). These two models have identical model physics, spatial resolutions, and domains, with the latter model using specialized hurricane wind forcing. Both models provided consistent estimates of the maximum wave height and period, with random errors of typically less than 25%, and timing errors of typically less than 5 h. Compared to these random errors, systematic model biases are negligible, with a typical negative model bias of 5%. It appears that higher wave model resolutions are needed to fully utilize the specialized hurricane wind forcing, and it is shown that present routine wave observations are inadequate to accurately validate hurricane wave models. [ABSTRACT FROM AUTHOR]

Tropical cyclone intensity change remains a forecasting challenge with important implications for such vulnerable areas as the U.S. coast along the Gulf of Mexico. Analysis of 1979-2008 Gulf tropical cyclones during their final two days before U.S. landfall identifies patterns of behavior that are of interest to operational forecasters and researchers. Tropical storms and depressions strengthened on average by about 7 kt for every 12 h over the Gulf, except for little change during their final 12 h before landfall. Hurricanes underwent a different systematic evolution. In the net, category 1-2 hurricanes strengthened, while category 3-5 hurricanes weakened such that tropical cyclones approach the threshold of major hurricane status by U.S. landfall. This behavior can be partially explained by consideration of the maximum potential intensity modified by the environmental vertical wind shear and hurricane-induced sea surface temperature reduction near the storm center associated with relatively low oceanic heat content levels. Linear least squares regression equations based on initial intensity and time to landfall explain at least half the variance of the hurricane intensity change. Applied retrospectively, these simple equations yield relatively small forecast errors and biases for hurricanes. Characteristics of most of the significant outliers are explained and found to be identifiable a priori for hurricanes, suggesting that forecasters can adjust their forecast procedures accordingly. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) Katrina and Rita moved as major hurricanes over energetic geostrophic ocean features in the Gulf of Mexico. Increased and reduced oceanic mixed layer (OML) cooling was measured following the passage of both storms over cyclonic and anticyclonic geostrophic relative vorticity ζg, respectively. This contrasting thermal response is investigated here in terms of the evolution of the storms’ near-inertial wave wake in geostrophic eddies. Observational data and ray-tracing techniques in realistic geostrophic flow indicate that TC-forced OML near-inertial waves are trapped in regions of negative ζg, where they rapidly propagate into the thermocline. These anticyclonic-rotating regimes coincided with the distribution of reduced OML cooling because rapid downward dispersion of near-inertial energy reduced the amount of kinetic energy available to increase vertical shears at the OML base. By contrast, TC-forced OML near-inertial waves were stalled in upper layers of cyclonic circulations, which strengthened vertical shears and entrainment cooling. Upgoing near-inertial energy propagation dominated inside a geostrophic cyclone that interacted with Katrina; the salient characteristics of these upward-propagating waves were the following: (i) they were radiated from the ocean interior because of geostrophic adjustment following upwelling–downwelling processes; (ii) rather than with the buoyancy frequency, they amplified horizontally as they encountered increasing values of f + ζg/2 during upward propagation; and (iii) they produced episodic vertical mixing through shear instability at a critical layer underneath the OML. To improve the prediction of TC-induced OML cooling, models must capture geostrophic features and turbulence closures must represent near-inertial wave processes such as dispersion and breaking between the OML base and the thermocline. [ABSTRACT FROM AUTHOR]

The decay of tropical cyclones after landfall is a key factor in estimating the extent of the hazard overland. Yet our current understanding of this decay is challenged by the low frequency of past events. Consequently, one cannot rely solely upon the historical record when attempting to quantify robustly the inland penetration of tropical cyclones. Thus, a framework designed to complement the historical record of landfalling storms by means of numerical modeling is introduced. Historical meteorological situations that could potentially have led to a landfall on the coast of the Gulf of Mexico are targeted and, using a bogus vortex technique in conjunction with a mesoscale model, a large number of landfalling hurricanes are simulated. The numerical ensemble constitutes a more comprehensive sample of possible landfalling hurricanes: it encompasses the range of events observed in the past but is not constrained to it. This allows us to revisit existing statistical models of the decay of tropical cyclones after landfall. A range of statistical models trained on the numerical ensemble of storms are evaluated on their ability to reproduce the inland decay of historical storms. These models have more skill at predicting tropical cyclone intensity over land than similar models trained exclusively on historical data. [ABSTRACT FROM AUTHOR]

The performance of the wave model WAVEWATCH III under a very strong, category 5, tropical cyclone wind forcing is investigated with different drag coefficient parameterizations and ocean current inputs. The model results are compared with field observations of the surface wave spectra from an airborne scanning radar altimeter, National Data Buoy Center (NDBC) time series, and satellite altimeter measurements in Hurricane Ivan (2004). The results suggest that the model with the original drag coefficient parameterization tends to overestimate the significant wave height and the dominant wavelength and produces a wave spectrum with narrower directional spreading. When an improved drag parameterization is introduced and the wave–current interaction is included, the model yields an improved forecast of significant wave height, but underestimates the dominant wavelength. When the hurricane moves over a preexisting mesoscale ocean feature, such as the Loop Current in the Gulf of Mexico or a warm- and cold-core ring, the current associated with the feature can accelerate or decelerate the wave propagation and significantly modulate the wave spectrum. [ABSTRACT FROM AUTHOR]

Seasonal hurricane forecasts are continuing to develop skill, although they are still subject to large uncertainties. This study uses a new methodology of cross-correlating variables against empirical orthogonal functions (EOFs) of the hurricane track density function (HTDF) to select predictors. These predictors are used in a regression model for forecasting seasonal named storm, hurricane, and major hurricane activity in the entire Atlantic, the Caribbean Sea, and the Gulf of Mexico. In addition, a scheme for predicting landfalling tropical systems along the U.S. Gulf of Mexico, southeastern, and northeastern coastlines is developed, but predicting landfalling storms adds an extra layer of uncertainty to an already complex problem, and on the whole these predictions do not perform as well. The model performs well in the basin-wide predictions over the entire Atlantic and Caribbean, with the predictions showing an improvement over climatology and random chance at a 95% confidence level. Over the Gulf of Mexico, only named storms showed that level of predictability. Predicting landfalls proves more difficult, and only the prediction of named storms along the U.S. southeastern and Gulf coasts shows an improvement over random chance at the 95% confidence level. Tropical cyclone activity along the U.S. northeastern coast is found to be unpredictable in this model; with the rarity of events, the model is unstable. [ABSTRACT FROM AUTHOR]

Using methods unique for tropical cyclone studies in peer-reviewed literature, this study examines the dynamics and predictability of a nondeveloping tropical disturbance in the Gulf of Mexico during the 2004 hurricane season. Short-range ensemble forecasts are performed with a mesoscale model at low resolution with parameterized moist convection and at high resolution with explicit convection. Taking advantage of discrepancies between ensemble members, statistical correlation is used to elucidate why some ensemble members strengthen the disturbance into a tropical cyclone or hurricane and others do not. It is found that the two most important factors in the initial conditions for genesis in this case are the presence of deep moisture and high CAPE. These factors combine to yield more active initial convection and a quick spinup during the first 6–12 h. Because these factors result in quicker genesis in some ensemble members than others, they are also the primary source for spread early in the ensemble. Discrepancies after 12 h are amplified by differences in convection that are related to fluxes of sensible and latent heat. Eventually the wind-induced surface heat exchange mechanism results in even larger ensemble spread. [ABSTRACT FROM AUTHOR]

The role of the Madden–Julian oscillation (MJO) in modulating the frequency and location of tropical cyclogenesis over the eastern Pacific and the Gulf of Mexico during August–September 1998 is examined. During the nonconvective phase of the MJO, convection and low-level cyclonic vorticity occurred primarily in conjunction with the intertropical convergence zone (ITCZ). During the convective phase, convection, low-level cyclonic vorticity, and convergence expanded into the northeastern Pacific and the Gulf of Mexico. This was accompanied by enhanced eddy kinetic energy and barotropic energy conversions as compared to the nonconvective phase, consistent with previous research. During the nonconvective phase of the MJO, vertical shear was relatively weaker but tropical cyclones tended to form mainly within the ITCZ. On the contrary, during the convective phase, vertical wind shear exceeded 10 m s-1 over much of this region and tropical cyclone development occurred north of the ITCZ, near the Mexican Pacific coast and the Gulf of Mexico. Idealized numerical experiments are conducted using a barotropic model with time-invariant basic states representative of the nonconvective and convective phases of the MJO. The simulations indicate that the propagation paths as well as the amplification of the eddies differ substantially between the two phases. During the nonconvective phase, the waves tend to propagate westward into the eastern Pacific. During the convective phase, stronger southerlies steer the waves into the Gulf of Mexico. The MJO-related modulation of tropical cyclogenesis in the eastern Pacific and Gulf of Mexico thus appears to involve anomalous convergence, cyclonic vorticity, vertical wind shear, and differing tracks of easterly waves. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TC) are some of the most intense weather systems on Earth and are responsible for generating hazardous waves on the sea surface that dominate the extreme wave climate in several regions, including the Gulf of Mexico and the U.S. East Coast. Modeling these waves is crucial for engineering applications, yet it is notoriously difficult, due to TC's compact structure and rapid evolution in space and time relative to other weather systems. To better understand the wave structure under TCs, we use satellite altimeter data paired with TC tracks. We parse the data by TC intensity and forward translation velocity, finding evidence of extended fetch. We use the altimeter data to evaluate operational hindcasts, including the US Army Corps of Engineer's Wave Information Study, National Oceanic and Atmospheric Administration's National Centers for Environmental Prediction Production Hindcast, and the Institut français de recherche pour l'exploitation de la mer (Ifremer) hindcast. The Ifremer hindcast (1990–2016) is examined in detail. Near the eye in the TC-centered reference frame, we find a pattern of model underestimation in the right sector and over estimation in the left and back sectors. This pattern holds, albeit modulated, across various intensities, forward translation velocities, and radii of maximum winds; the exceptions being the most intense and smallest storms, where underestimation is more severe and expands to all sectors near the TC eye. [ABSTRACT FROM AUTHOR]

The article cites a research conducted by James Belanger related to the connection between the size and intensity of Gulf hurricanes and the number of tornadoes that arise from these storms. It focuses on the model developed by the scientists for predicting this link. The model was applied to more than 100 Gulf Coast tropical cyclones which showed that as the size of landfalling hurricanes increased the number of tornadoes increased. The study is published in the "Geophysical Research Letters."

In recent decades, the scientific ability to project tropical cyclone (TC) intensities and tracks has improved. Hurricanes undergoing the process of rapid intensification (RI) have created new barriers in formulating predictions of TC paths and peak velocities. Current research suggests the warming climate may produce more intense TCs with a higher probability of undergoing RI during their life cycle. The increased likelihood of rapidly intensifying TCs necessitates the development of an RI climatology spanning the current North Atlantic record. A time series count analysis suggests a significant increasing trend of RI events in the Atlantic basin by 29.1% (17%–45%) from the years 1900 to 2017. For the entire basin, the peak frequency occurs in September, followed by August, then October. Gulf of Mexico events tend to occur more regularly over June, July, August, and September, while Atlantic storms peak in August, September, and October. The onset of RI typically begins in the Western Caribbean and Gulf of Mexico, west of 85° W. The lifetime maximum intensity typically occurs in the Gulf of Mexico basin. Density analysis suggests the locations of lifetime maximum intensities (LMIs) in rapidly intensifying TCs are clustered through space. It should be noted that these results are dependent upon the HURDAT record of events. This research is necessary in order to find substantive trends in RI events that may aid future predictions of tropical cyclones; therefore, potentially decreasing the lives lost and the cost of damage that these storms are known to cause. [ABSTRACT FROM AUTHOR]

Nadal-Caraballo, N.C.; Campbell, M.O.; Gonzalez, V.M.; Torres, M.J.; Melby, J.A., and Taflanidis, A.A., 2020. Coastal Hazards System: A Probabilistic Coastal Hazard Analysis Framework. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1211-1216. Coconut Creek (Florida), ISSN 0749-0208. Coastal hazards such as storm surge, waves, currents, wind, and rainfall associated with extratropical and tropical cyclones (e.g., hurricanes) can have devastating effects and threaten the lives of millions of people living along the world's coastlines. This has led to the development of the Coastal Hazards System (CHS), an ambitious program with the primary goal of quantifying extreme coastal hazards due to both tropical and extratropical cyclones. The CHS currently covers all U.S. hurricane-prone coastlines along the Gulf of Mexico, the Atlantic seaboard, Puerto Rico, and the U.S. Virgin Islands, as well as regions affected only by extratropical storms like the Great Lakes. The Probabilistic Coastal Hazard Analysis (PCHA) is an innovative statistical and probabilistic framework that serves as the foundation of the CHS. This framework includes comprehensive characterization of storm climatology, high-resolution numerical modeling, and advanced joint probability analysis of atmospheric forcing and primary storm responses, including associated aleatory and epistemic uncertainties. New PCHA advancements overcome limitations of previous joint probability methods by integrating meta-Gaussian copula for the computation of storm probabilities, spatially-varying bias and uncertainty quantification, and Gaussian process metamodel (GPM) based on existing CHS synthetic tropical cyclones. GPM emulates the response of computationally-expensive hydrodynamic models and enables the generation of augmented tropical cyclone suites, consisting of up to millions of storms, for optimal coverage of the parameter and probability spaces. The CHS also includes a database and a web-based data mining and visualization system for public distribution of high-fidelity probabilistic, atmospheric and hydrodynamic modeling results. PCHA results are distributed along with the corresponding metadata, in self-describing data formats for easy and efficient use by engineers, planners, economists, emergency managers, and researchers. [ABSTRACT FROM AUTHOR]

Tropical cyclone induced phytoplankton productivity is examined using a tropical cyclone version of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®). A four-component Nutrient–Phytoplankton–Detritus biological model is integrated into COAMPS to create a fully integrated air-ocean-wave-biology model. This study investigates the upper ocean physical and biological states before and after Hurricane Ivan traversed the central Gulf of Mexico, in mid-September 2004. Elevated concentrations of surface chlorophyll-a appear in the simulation two days after the passage of the tropical cyclone, and these results are spatially and temporally coherent with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data for this time period. Model results reveal enhancement of chlorophyll-a in submesoscale filaments on the periphery of a warm-core eddy that are dominated by large values of lateral strain and relative vorticity at the surface. The vertical circulation of the filament, with its associated upward vertical motion, permits surface ventilation of cold, nitrogen-rich water and subsequent stimulation of primary biological production. Here, we show for the first time that coupled biological-physical submesoscale processes may be simulated via a fully integrated air-sea-wave-biology tropical cyclone model that provides a mechanistic explanation of the conspicuous features revealed in satellite ocean color imagery following Ivan. [ABSTRACT FROM AUTHOR]

One of the most destructive natural hazards, tropical cyclone (TC)–induced coastal flooding, will worsen under climate change. Here we conduct climatology–hydrodynamic modeling to quantify the effects of sea level rise (SLR) and TC climatology change (under RCP 8.5) on late 21st century flood hazards at the county level along the US Atlantic and Gulf Coasts. We find that, under the compound effects of SLR and TC climatology change, the historical 100-year flood level would occur annually in New England and mid-Atlantic regions and every 1–30 years in southeast Atlantic and Gulf of Mexico regions in the late 21st century. The relative effect of TC climatology change increases continuously from New England, mid-Atlantic, southeast Atlantic, to the Gulf of Mexico, and the effect of TC climatology change is likely to be larger than the effect of SLR for over 40% of coastal counties in the Gulf of Mexico. Tropical cyclone-induced coastal flooding will increase under climate change. Here the authors estimate the effects of sea level rise and tropical cyclone climatology change on late–21st–century flood hazards along the US Atlantic and Gulf Coasts and find that the effect of tropical cyclone change could surpass the effect of sea level rise at some areas in the Gulf of Mexico. [ABSTRACT FROM AUTHOR]