Tropical Cyclone Intensity Research Articles

A theoretical method to characterize the resistance effects of nonflat terrain on wind fields in a parametric wind field model for tropical cyclones

Traditionally, an empirical speed-up factor was introduced to reflect the effects of nonflat terrain on near-surface wind speeds. In this paper, the resistance effects of nonflat terrain are considered by introducing the terrain drag coefficient in the parametric wind field model for tropical cyclones (TCs) with a theoretical method. Terrain effects on wind fields are investigated in complex areas along the coastal zone in China under TC conditions. The results show that the terrain drag coefficient is the function of the slope angle and is sensitive to the spatial resolution. After including the resistance effect of nonflat terrain, the TC intensities weaken overall during landfall, with a slight enhancement near the coastal zone. The wind speeds outside the radius of the maximum wind speed decrease, while the wind speeds within the radius of the maximum wind speed increase. Both the TC eye and the radius of maximum wind speed shrink, which is more obvious when the TC center is entirely over land. As a result, the location and magnitude of the maximum wind speed are affected by the nonflat terrain. The changed structure of the wind fields demonstrates the necessity of considering the effects of nonflat terrain in simulating the wind fields under TC conditions.

Environments conductive to tropical transitions in the North Atlantic: Anthropogenic climate change influence study

Tropical cyclones can have different precursors, but most of them affecting Europe have a tropical transition origin and develop in autumn. This research focuses on analyzing changes on favorable environments for tropical transition development in the North Atlantic (NATL) basin for this season under the Anthropogenic Climate Change (ACC) effect. Comparisons between the climatology of some relevant variables related to tropical cyclogenesis have been computed for different periods, considering the ACC effect. For this purpose, the SSP5–8.5 scenario from an adapted version of the EC-Earth3 climatic model has been used. The combination of the obtained results is indicative of a NATL environment tropicalization in response to ACC, weightier for the end of the XXI century. Therefore, the NATL environment will be more prone to tropical transition development in the future, which is of particular concern since tropical cyclones are notorious for their lethality and economic impact worldwide. Key points1.To enhance the knowledge of how the ACC could influence the NATL environment behavior to favor tropical transition development.2.To deepen on the understanding of how the ACC could have impacts on the NATL environment to promote tropical cyclones intensification.

Increased threat of strong typhoons along the Pacific coast of Japan: Combined effect of track change and seasonal advance

AbstractThis study analyses the landfall intensity of tropical cyclones (TCs) affecting the Pacific coast of Japan and found that the proportion of strong typhoons increased significantly in the second 22 years from 1977 to 2020. With an objective cluster analysis of TC tracks, one could isolate a cluster of TCs originating from the southeastern part of the western North Pacific (WNP), which plays a dominant role in increasing landfalls of strong typhoons. These TCs are characterized by a long‐recurving track and could achieve significantly higher intensity and larger size. Further analysis of TC trajectories and the environmental steering flow show a greater tendency for TCs originating from the southeastern WNP to approach the Pacific coast of Japan, even though there was a dramatic decrease in TC genesis number during autumn. Meanwhile, a notable earlier onset of strong typhoons occurred within this cluster of TCs due to more favorable atmospheric and oceanic conditions in summer. The results of this study emphasize the impacts of TC track change and seasonal advance of strong typhoons on the variation of intensity and potential destructiveness of landfalling TCs.

Modelación de mapa de inundaciones durante el Huracán Alex: simulación usando precipitación multisensorial en la ciudad de Monterrey, México

Alex Hurricane was one of the most intense tropical cyclones in the North Atlantic, that caused fatalities and loses in the Northeast of Mexico due to the flash floods. Flood hazard mapping is a vital tool to assess inundation areas, which can be simulated using hydraulic and hydrologic models. This study describes the modelling of a flood event during Alex Hurricane in the Santa Catarina River Watershed, Northeast of Mexico, applying HEC-HMS and two dimensional (2D) HEC-RAS models forced with Multi Radar Multi Sensor - Quantitative Precipitation Estimation (MRMS-QPE). A HEC-HMS model was developed forced by (MRMS-QPE) as input to simulate discharges along the Santa Catarina River. The simulated discharges were introduced as border conditions along the mainstream of the Santa Catarina River inside a HEC-RAS 2D model to simulate a flood map along the mainstream of the Santa Catrina River. The observed against the simulated peak discharges achieved a R-squared of 0.97 and a Nash - Sutcliffe coefficient of 0.97. The observed against the simulated accumulated discharges achieved a R-squared of 0.99 and a Nash - Sutcliffe coefficient of 1.0. The observed against the simulated stages achieved a R-squared of 0.74 and, a Nash - Sutcliffe coefficient of 0.68. The use of HEC-HMS and HEC-RAS 2D models coupled with MRMS-QPE. shows that these models are user friendly to setup, the model has stability and the capacity to simulate flood maps along the whole mainstream of the Santa Catarina River with good results.

Spatiotemporal methods for estimating subsurface ocean thermal response to tropical cyclones

Abstract. Tropical cyclones (TCs), driven by heat exchange between the air and sea, pose a substantial risk to many communities around the world. Accurate characterization of the subsurface ocean thermal response to TC passage is crucial for accurate TC intensity forecasts and an understanding of the role that TCs play in the global climate system. However, that characterization is complicated by the high-noise ocean environment, correlations inherent in spatiotemporal data, relative scarcity of in situ observations, and the entanglement of the TC-induced signal with seasonal signals. We present a general methodological framework that addresses these difficulties, integrating existing techniques in seasonal mean field estimation, Gaussian process modeling, and nonparametric regression into an ANOVA decomposition model. Importantly, we improve upon past work by properly handling seasonality, providing rigorous uncertainty quantification, and treating time as a continuous variable, rather than producing estimates that are binned in time. This ANOVA model is estimated using in situ subsurface temperature profiles from the Argo fleet of autonomous floats through a multistep procedure, which (1) characterizes the upper-ocean seasonal shift during the TC season, (2) models the variability in the temperature observations, and (3) fits a thin-plate spline using the variability estimates to account for heteroskedasticity and correlation between the observations. This spline fit reveals the ocean thermal response to the TC passage. Through this framework, we obtain new scientific insights into the interaction between TCs and the ocean on a global scale, including a three-dimensional characterization of the near-surface and subsurface cooling along the TC storm track and the mixing-induced subsurface warming on the track's right side.

Characteristics of rainfall distribution induced by tropical cyclones using GSMaP data over the Vietnam region

ABSTRACT Tropical cyclones (TCs) contribute significantly to rainfall along Vietnam's coast, yet their complex precipitation structures remain poorly resolved, hindering forecast skill. This study analyzes TC rainfall distributions over the Vietnam East Sea from 2000 to 2020. The Global Satellite Mapping of Precipitation (GSMaP) product provides precipitation estimates with 0.1° resolution at hourly intervals, enabling detailed structural characterization. Rainfall features are analyzed across TC intensities, motion vectors, landfall locations, and interactions with cold surge (CS) air masses. Results show that total coverage differences are less significant than the intensity variations in narrow inner core rainbands. Asymmetric rainfall distributions concentrate in the front-right quadrant but shift after landfall. Northern Vietnam observes higher TC frequencies, but southern regions experience heavier extreme rains. Additionally, CS intrusions substantially intensify eyewall convection and redirect TC precipitation. These structural sensitivities visible in GSMaP observations elucidate the dynamics modulating TC rainfall. Characterizing multi-scale interactions and precipitation processes aids in forecasting and impact assessment for these high-risk storms with complex regional behavior.

A Hybrid Machine Learning/Physics‐Based Modeling Framework for 2‐Week Extended Prediction of Tropical Cyclones

AbstractPrediction of tropical cyclones (TCs) beyond a week is challenging but of great importance for disaster prevention and mitigation. We propose a hybrid machine learning (ML)/physics‐based modeling framework to extend TC forecasts to 2 weeks. This framework integrates a recently launched ML‐based global weather prediction model (Pangu) and the high‐resolution physics‐based regional weather research and forecasting (WRF) model. The Pangu model shows promise in enhancing the accuracy of predictions for large‐scale circulation and TC tracks, while the high‐resolution WRF model is capable of capturing the core processes underlying TC evolution. To capitalize on the complementary strengths of both the Pangu and WRF models in predicting TCs, the framework comprises three key components: downscaling the Pangu model using the WRF model, adjusting large‐scale circulation through spectral nudging driven by the Pangu model forecasts, and updating sea surface temperature using an ocean mixed‐layer model. These components also ensure the framework's feasibility for real‐time TC forecasting. The prediction skill of the framework has been demonstrated for five long‐lived TCs across various basins from 2018 to 2023. Results indicate that the hybrid ML/physics‐based modeling framework decreased the 2‐week mean TC track and intensity errors by 59% and 32% compared to the global numerical weather prediction models, by 2% and 59% compared to the ERA5‐driven Pangu model, and by 32% and 23% compared to the ERA5‐driven WRF model, respectively. This implies that the framework has great potential to be used for 2‐week extended prediction of TCs.

Asymmetric and Irreversible Response of Tropical Cyclone Potential Intensity to CO2 Removal

AbstractUnderstanding the behaviors of tropical cyclone (TC) intensity under the CO2 removal scenario is important for future climate adaptation and policy making. Based on the idealized CO2 ramp‐up (from 284.7 to 1,138.8 ppm) and symmetric ramp‐down experiments, our results suggest an asymmetric and irreversible response of TC potential intensity to CO2 reduction. Potential intensity shows an additional enhancement at the same CO2 level during the CO2 ramp‐down relative to the ramp‐up periods (though with regional differences), and does not completely return to the initial value even when CO2 recovers on multi‐decadal to centennial timescale. The enhanced potential intensity is dominated by the increased thermodynamic disequilibrium, which is mainly attributed to the weakened surface winds arising from the El Niño‐like warming pattern and inter‐hemispheric ocean temperature contrast. Our results highlight the potential risks of stronger storms on the socioeconomic development under the negative carbon emissions pathways.

Interannual Fluctuations and Their Low-Frequency Modulation of Summertime Heavy Daily Rainfall Potential in Western Japan

Heavy rainfall under the conditions of the changing climate has recently garnered considerable attention. The statistics on heavy daily rainfall offer vital information for assessing present and future extreme events and for clarifying the impacts of global climate variability and change, working to form a favorable background. By analyzing a set of large-ensemble simulations using a global atmospheric model, this study demonstrated that two different physical processes in global climate variability control the interannual fluctuations in the 99th- and 90th-percentile values of summertime daily rainfall (i.e., the potential amounts) on Kyushu Island in western Japan. The 90th-percentile values were closely related to large-scale horizontal moisture transport anomalies due to changes in the subtropical high in the northwestern Pacific, which was usually accompanied by basin-scale warming in the Indian Ocean subsequent to the wintertime El Niño events. The contributions of the sea surface temperatures over the northern Indian Ocean and the eastern tropical Pacific Ocean showed low-frequency modulations, mainly due to the influences of the global warming tendency and the interdecadal variability in the climate system, respectively. In contrast, tropical cyclone activity played a major role in changing the 99th-percentile value. The potentials of both the tropical cyclone intensity and the existence density fluctuated, largely owing to the summertime sea surface temperature over the tropical Pacific, which can be modulated by the El Niño diversity on interdecadal timescales.

Factors Driving Intensification of Pre-Monsoon Tropical Cyclones Over the Bay of Bengal: A Comparative Study of Cyclones Fani and Yaas

Factors Driving Intensification of Pre-Monsoon Tropical Cyclones Over the Bay of Bengal: A Comparative Study of Cyclones Fani and Yaas

Quantitative assessment of population risk to tropical cyclones using hybrid modeling combining GAM and XGBoost: A case study of Hainan Province

Global climate change is expected to increase the proportion of intense tropical cyclones (TCs) in the Northwest Pacific. This study focused on how factors, especially extreme events, may affect disaster losses. To address this issue, an event-based multivariate TC risk assessment model, which employs copulas, a generalized additive model, and undersampling extreme gradient boosting decision tree techniques, is developed to enhance the accuracy of disaster loss prediction. The results suggest that on Hainan Island, the rate of the affected population is positively correlated with the maximum wind speed and maximum daily rainfall while negatively correlated with the gross domestic product and elevation. The study also shows that the TC risk in the cities of Hainan Island increases as the return period expands, and each return period scenario shows a unique geospatial distribution of TC risk on Hainan Island, with higher risks in the coastal and eastern regions. These results highlight the importance of implementing effective disaster management strategies to mitigate the impact of severe TCs in the region.

Changes to tropical cyclone trajectories in Southeast Asia under a warming climate

The impacts of tropical cyclones (TCs) on Southeast Asia’s coastlines are acute due to high population densities in low-lying coastal environments. However, the trajectories of TCs are uncertain in a warming climate. Here, we assess >64,000 simulated TCs from the nineteenth century to the end of the twenty-first century for both moderate- and high-emissions scenarios. Results suggest changes to TC trajectories in Southeast Asia, including: (1) poleward shifts in both genesis and peak intensification rates; (2) TC formation and fastest intensification closer to many coastlines; (3) increased likelihoods of TCs moving most slowly over mainland Southeast Asia; and (4) TC tracks persisting longer over land. In the cities of Hai Phong (Vietnam), Yangon (Myanmar), and Bangkok (Thailand), these variations result in future increases in both peak TC intensity and TC duration compared to historical TCs.

Multi-class AUC maximization for imbalanced ordinal multi-stage tropical cyclone intensity change forecast

Intense tropical cyclones (TCs) cause significant damage to human societies. Forecasting the multiple stages of TC intensity changes is considerably crucial yet challenging. This difficulty arises due to imbalanced data distribution and the need for ordinal multi-class classification. While existing classification methods, such as linear discriminant analysis, have been utilized to predict rare rapidly intensifying (RI) stages based on features related TC intensity changes, they are limited to binary classification distinguishing between RI and non-RI stages. In this paper, we introduce a novel methodology to tackle the challenges of imbalanced ordinal multi-class classification. We extend the Area Under the Curve maximization technique with inter-instance/class cross-hinge losses and inter-class distance-based slack variables. The proposed loss function, implemented within a deep learning framework, demonstrates its effectiveness using real sequence data of multi-stage TC intensity changes, including satellite infrared images and environmental variables observed in the western North Pacific.

Fewer tropical cyclones yield more near-inertial wind work to the global ocean over the past four decades

In general, tropical cyclones (TCs) will inject energy into oceanic inertial motion‒a prevalent phenomenon in the ocean. Under global warming, the intensity of TCs is on the rise, while their frequency has exhibited a decline since 2000. However, the long-term trend of this energy infusion is an underexplored problem in this context. Using a damped-slab model, we computed the wind work exerted by TCs on the ocean’s mixed-layer inertial motions. Our results show that the global wind work has increased by approximately 50% from 1979 to 2023. The wind work increase of strong TCs (Saffir–Simpson levels 4–5) is the major contributor to the increasing trend of global wind work, primarily due to their increasing frequency and substantial wind stress. At basin scale, the wind work input of the North Atlantic TCs has increased by 2 times, owing to an increase in both their intensity and frequency. Specifically, in the South Indian and the eastern North Pacific basins, the rise in wind work is primarily attributed to the enhanced wind energy of TCs within the inertial bands.

Remote effect of tropical south Atlantic sea surface temperature anomalies on April–June accumulated cyclone energy over the western North Pacific

Global processes and their teleconnections, such as the El Niño-Southern Oscillation (ENSO), have been shown to be a large driver of interannual changes in accumulated cyclone energy (ACE) of western North Pacific (WNP) tropical cyclones (TCs), with higher ACE during El Niño and lower ACE during La Niña. However, it remains uncertain whether interannual changes in WNP TC ACE are modulated by sea surface temperature anomalies (SSTAs) in other oceans. This study finds a significant negative correlation between WNP TC ACE during the early season (April–June) and simultaneous SSTAs over the tropical south Atlantic (TSA) in 1970–2021. On average, in warm TSA years, basinwide April–June ACE is significantly lower, with significant ACE decreases mainly occurring over the region spanning 5°–30°N, 115°–150°E. This is a result of reduced TC frequency, intensity and duration, due to a remote modulation of WNP environmental conditions by TSA SSTAs. In warm TSA years, there are significant decreases in 700–500-hPa relative humidity, 850-hPa relative vorticity and 200-hPa divergence and significant increases in 850–200-hPa vertical wind shear over the portion of the WNP with significant ACE reductions. These environmental changes can be linked to an anomalous Walker circulation induced by TSA SSTAs.

WMO Typhoon Landfall Forecast Demonstration Project (2010–22): A Decade of Transition from Track Forecasts to Impact Forecasts

Abstract The Typhoon Landfall Forecast Demonstration Project (TLFDP) (2010–22) was an international cooperative scientific project conducted under the framework of the WMO. The primary objectives of the TLFDP were to enhance the capability of tropical cyclone (TC) forecasters and support related decision-makers in effective utilization of the most advanced forecasting techniques for the ultimate purpose of reducing and preventing disasters associated with TC landfall. Forty agencies/organizations/projects globally participated in the activities of the TLFDP following its inception in 2010, although the primary focus was on landfalling TCs in the western North Pacific. The TLFDP facilitated collaborations and workshops that realized notable achievements in four key areas: 1) the collection, production, and sharing of TC data; 2) the development and application of TC forecast verification metrics; 3) research on TC forecast skill; and 4) development of new techniques for TC forecasting. An obvious outcome was the shift from prediction of TC features, including track and intensity, toward prediction of TC impacts with more probabilistic conception. The final years of the project also promoted increasing application of artificial intelligence and machine learning techniques in various techniques for analysis and forecasting of TCs. Although the TLFDP ended in 2022, its core activities have continued to be extended through new WMO projects and regional cooperative initiatives.

Oceanic seabirds chase tropical cyclones

In late summer and autumn, the passage of intense tropical cyclones can profoundly perturb oceanic and coastal ecosystems. Direct negative effects on individuals and marine communities can be dramatic, especially in the coastal zone,1,2,3,4 but cyclones can also enhance pelagic primary and secondary production.5,6,7,8,9 However, cyclone impacts on open ocean marine life remain poorly understood. Here, we investigate their effects on the foraging movements of a wide-ranging higher predator, the Desertas petrel (Pterodroma deserta), in the mid-latitude North Atlantic during hurricane season. Contrary to previously studied pelagic seabirds in tropical and mid-latitude regions,10,11 Desertas petrels did not avoid cyclones by altering course, nor did they seek calmer conditions within the cyclone eye. Approximately one-third of petrels tracked from their breeding colony interacted with approaching cyclones. Upon encountering strong winds, the birds reduced ground speed, likely by spending less time in flight. A quarter of birds followed cyclone wakes for days and over thousands of kilometers, a behavior documented here for the first time. Within these wakes, tailwind support was higher than along alternative routes. Furthermore, at the mesoscale (hours-weeks and hundreds of kilometers), sea surface temperature dropped and surface chlorophyll sharply increased, suggesting direct effects on ocean stratification, primary production, and therefore presumably prey abundance and accessibility for surface-feeding petrels. We therefore hypothesize that cyclone wakes provide both predictably favorable wind conditions and foraging opportunities. As such, cyclones may have positive net effects on the demography of many mid-latitude pelagic seabirds and, likely, other marine top-predators.

Variations in air-sea heat fluxes during lifetime of intense tropical cyclones over the Bay of Bengal

Variations in air-sea heat fluxes during lifetime of intense tropical cyclones over the Bay of Bengal

Diversity of Tropical Cyclones Rapid Intensification

AbstractThe study investigates the rapid intensification (RI) of tropical cyclones (TCs) in the Northwestern Pacific. We found that rapid changes in the maximum wind speed (Vmax) and the minimum central pressure (Pmin) are not always concurrent. RI cases can be categorized into three types: (a) RIv, only Vmax strengthens rapidly; (b) RIp, only Pmin decreases rapidly; (c) RIpv, rapid changes in Vmax and Pmin occur concurrently. At the onset of RI, RIv‐type TCs exhibit the weakest intensity and the smallest size, with deep convection concentrated in the inner‐core region; RIp‐type TCs are characterized by the strongest cyclone intensity and the largest outer‐core size, with strong convection covering the inner‐ and outer‐core regions; RIpv‐type TCs show moderate intensity, size, and convection distribution. For RIpv, significant strengthening of wind profile is concentrated in the inner‐core region, while for RIp it is more prominent in the outer‐core.

Response of Sediment Dynamics to Tropical Cyclones under Various Scenarios in the Jiangsu Coast

The Jiangsu Coast (JC), China, is an area susceptible to the impact of tropical cyclones (TCs). However, due to the lack of available on-site observation data, nearshore sedimentary dynamic processes under the impact of TCs have not been fully explored. This study developed a 3D wave–current–sediment numerical model for the JC based on the Finite Volume Community Ocean Model (FVCOM) to investigate sediment dynamic responses to TCs under various scenarios, including different tracks, intensities of TCs and tidal conditions. The validation results demonstrated the model’s satisfactory performance. According to the simulation results, typhoons can significantly impact the hydrodynamics and sediment dynamics. During Typhoon Lekima in 2019, strong southeasterly winds substantially increased the current velocity, bottom stress, wave height, and suspended sediment concentration (SSC). Three typical landfall-type typhoons, with prevailing southeasterly winds, brought significant sediment flux from southeast to northwest along the coast, while the typhoon that moved northward in the Yellow Sea induced a relatively small sediment flux from north to south. Typhoons could also induce stripe-like erosion and deposition, which is closely related to seafloor topography, resulting in seabed thickness variations of up to ±0.3 m. Additionally, strengthening typhoon wind fields can lead to increased sediment flux and seabed morphological changes. Typhoon Winnie, particularly at spring tide, had a greater impact on sediment dynamics compared to other landfall typhoons. Numerical simulations showed that the typhoon-induced net sediment flux within the spring tidal cycle could increase by 80% to 100% compared to the neap tidal cycle, indicating the significant influence of tidal conditions on sediment transport during TC events.