Impact Of Cyclones Research Articles

Changing Impacts of Tropical Cyclones on East and Southeast Asian Inland Regions in the Past and a Globally Warmed Future Climate

The impacts of the western North Pacific (WNP) tropical cyclone (TC) on East and Southeast Asian inland regions are analyzed. Here, based on a stringent TC selecting criterion, robust increase of TC-related inland impacts between 1979 and 2016 over East and Southeast Asian regions have been detected. The storms sustained for 2–9 h longer and penetrated 30–190 km further inland, as revealed from different best track datasets. The most significant increase of the TC inland impacts occurred over Hanoi and South China. The physical mechanism that affects TC-related inland impacts is shortly discussed. First, the increasing TC inland impacts just occur in the WNP region, but it is not a global effect. Second, besides the significant WNP warming effects on the enhanced TC landfall intensity and TC inland impacts, it is suggested that the weakening of the upper-level Asian Pacific teleconnection pattern since 1970s may also play an important role, which may reduce the climatic 200 hPa anti-cyclonic wind flows over the Asian region, weakening the wind shear near the Philippine Sea, and may eventually intensify the TC intensity when the TCs across the basin. Moreover, the TC inland impacts in the warming future are projected based on a high-resolution (20 km) global model according to the Representative Concentration Pathway 8.5 scenario. By the end of the 21st century, TC mean landfall intensity will increase by 2 m/s (6%). The stronger storms will sustain 4.9 h (56%) longer and penetrate 92.4 km (50%) farther inland, thereby almost doubling the destructive power delivered to Asian inland regions. More inland locations will therefore be exposed to severe storm–related hazards in the future due to warmer climate. Long-term planning to enhance disaster preparedness and resilience in these regions is called for.

Moving Earth (not heaven): A novel approach to tropical cyclone impact modelling, demonstrated for New Zealand

Some of the historically highest-impact weather events to affect New Zealand have been caused by ex-tropical cyclones (ex-TCs) which have had significant direct and indirect adverse effects. The weather theme of a New Zealand government funded research programme known as the Resilience to Nature’s Challenges (RNC2) aims to create physical datasets of high-impact, yet credible, extreme weather events not previously available to researchers and end-users. This paper focusses on the potential scenarios of a major ex-TC impacting Auckland and surrounding areas in the north of New Zealand. Highly-detailed, meteorologically consistent data of such events are produced by relocating the New Zealand land mass into the path of historical ex-TC cases, using convection permitting simulations of the Met Office Unified Model. We illustrate the applicability of this method over simpler (non-consistent) methods, and show for ex-TC Cook (April 2017) what wind strength and precipitation totals would have been for a track just slightly to the west of reality. Finally, we illustrate how sub-kilometre simulations nested within the main simulation can add significant additional detail at the city scale, and show how simple modifications, for example raising the sea-surface temperature, can illustrate how events may change in future. Such scenarios may prove invaluable in designing future infrastructure and planning for such an event.

Impacts of tropical cyclones on the thermodynamic conditions in the tropical tropopause layer observed by A-Train satellites

Abstract. The tropical tropopause layer (TTL) is the transition layer between the troposphere and the stratosphere. Tropical cyclones may impact the TTL by perturbing the vertical distributions of cloud, temperature, and water vapor. This study combines several A-Train instruments, including radar from CloudSat, lidar from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, and the Atmospheric Infrared Sounder (AIRS) on the Aqua satellite, to detect signatures of cyclone impacts on the distribution patterns of cloud, water vapor, temperature, and radiation by compositing these thermodynamic fields relative to the cyclone center location. Based on the CloudSat 2B-CLDCLASS-LIDAR product, this study finds that tropical cyclone events considerably increase the occurrence frequencies of TTL clouds, in the form of cirrus clouds above a clear troposphere. The amount of TTL cloud ice, however, is found to be mostly contributed by overshooting deep convection that penetrates the base of the TTL at 16 km. To overcome the lack of temperature and water vapor products in cloudy conditions, this study implements a synergistic method that retrieves temperature, water vapor, ice water content, and effective radius simultaneously by incorporating observations from AIRS, CloudSat, and CALIPSO. Using the synergistic method, we find a vertically oscillating pattern of temperature anomalies above tropical cyclones, with warming beneath the cloud top (around 16 km) and cooling above. Based on water vapor profiles retrieved by the synergistic method, we find that the layer integrated water vapor (LIWV) above 16 km is higher above tropical cyclones, especially above overshooting deep convective clouds, compared to climatological values. Moreover, we find that the longwave and net radiative cooling effect of clouds prevails within 1000 km of tropical cyclone centers. The radiative heating effects of clouds from the CloudSat 2B-FLXHR-LIDAR product are well differentiated by the collocated brightness temperature of an infrared window channel from the collocated AIRS L1B product. By performing instantaneous radiative heating rate calculations, we further find that TTL hydration is usually associated with radiative cooling of the TTL, which inhibits the diabatic ascent of moist air across isentropic surfaces to the stratosphere. Therefore, the radiative balance of the TTL under the impact of the cyclone does not favor the maintenance of moist anomalies in the TTL or transporting water vertically to the stratosphere.

Corrigendum to “The Impact of Tropical Cyclones in Premonsoonal Season on Local Convection over the Al-Hajar Mountains in Oman during 2007–2018”

Corrigendum to “The Impact of Tropical Cyclones in Premonsoonal Season on Local Convection over the Al-Hajar Mountains in Oman during 2007–2018”

Impact of Tropical Cyclones on Geostrophic Velocity of the Western Boundary Current

AbstractTropical cyclones (TC), which are among the most destructive natural phenomena on Earth, have significant impacts on the western boundary current (WBC). We quantify the direct impact of TCs on the surface geostrophic velocity of the Kuroshio, the WBC in the western North Pacific, by analyzing satellite‐derived geostrophic current data and using results from theoretical and numerical models. The study reveals that TCs decrease the surface geostrophic velocity by 14 cm s−1 which is 16% of the mean velocity of the Kuroshio (85 cm s−1), with the reduced velocity maintained for a month. The decrease in velocity of the Kuroshio is mainly (87%) due to the effect of TC‐driven upwelling (“Cooling effect”), the effect of ocean heat uptake after the TC (“Warming effect”) being minor (13%); these are basically enabled by the strong thermal gradient around the Kuroshio.

The association between tropical cyclones and dengue fever in the Pearl River Delta, China during 2013-2018: A time-stratified case-crossover study.

Studies have shown that tropical cyclones are associated with several infectious diseases, while very few evidence has demonstrated the relationship between tropical cyclones and dengue fever. This study aimed to examine the potential impact of tropical cyclones on dengue fever incidence in the Pearl River Delta, China. Data on daily dengue fever incidence, occurrence of tropical cyclones and meteorological factors were collected between June and October, 2013-2018 from nine cities in the Pearl River Delta. Multicollinearity of meteorological variables was examined via Spearman correlation, variables with strong correlation (r>0.7) were not included in the model simultaneously. A time-stratified case-crossover design combined with conditional Poisson regression model was performed to evaluate the association between tropical cyclones and dengue fever incidence. Stratified analyses were performed by intensity grades of tropical cyclones (tropical storm and typhoon), sex (male and female) and age-groups (<18, 18-59, ≥60 years). During the study period, 20 tropical cyclones occurred and 47,784 dengue fever cases were reported. Tropical cyclones were associated with an increased risk of dengue fever in the Pearl River Delta region, with the largest relative risk of 1.62 with the 95% confidence interval (1.45-1.80) occurring on the lag 5 day. The strength of association was greater and lasted longer for typhoon than for tropical storm. There was no difference in effect estimates between males and females. However, individuals aged over 60 years were more vulnerable than others. Tropical cyclones are associated with increased risk of local dengue fever incidence in south China, with the elderly more vulnerable than other population subgroups. Health protective strategies should be developed to reduce the potential risk of dengue epidemic after tropical cyclones.

Hurricane Matthew in 2100: effects of extreme sea level rise scenarios on a highly valued coastal area (Palm Beach, FL, USA)

Sea-level rise represents a severe hazard for populations living within low-elevation coastal zones and is already largely affecting coastal communities worldwide. As sea level continues to rise following unabated greenhouse gas emissions, the exposure of coastal communities to inundation and erosion will increase exponentially. These impacts will be further magnified under extreme storm conditions. In this paper, we focus on one of the most valuable coastal real estate markets globally (Palm Beach, FL). We use XBeach, an open-source hydro and morphodynamic model, to assess the impact of a major tropical cyclone (Hurricane Matthew, 2016) under three different sea-level scenarios. The first scenario (modern sea level) serves as a baseline against which other model runs are evaluated. The other two runs use different 2100 sea-level projections, localized to the study site: (i) IPCC RCP 8.5 (0.83 m by 2100) and (ii) same as (i), but including enhanced Antarctic ice loss (1.62 m by 2100). Our results show that the effective doubling of future sea level under heightened Antarctic ice loss amplifies flow velocity and wave height, leading to a 46% increase in eroded beach volume and the overtopping of coastal protection structures. This further exacerbates the vulnerability of coastal properties on the island, leading to significant increases in parcel inundation.

Impacts of Tropical Cyclones on the Caribbean Under Future Climate Conditions

AbstractJoint effects of the dynamic sea‐level rise projected changes in the large‐scale atmosphere/ocean circulation, and wave climate on hurricane‐induced extreme water levels in the Caribbean region are assessed. We use the 2D‐depth integrated ADCIRC + SWAN wave‐ocean model, baroclinically coupled to an ocean‐eddying version of the Community Earth System Model, to compare impacts of the September 2017 hurricanes with projected impacts of similar hypothetical tropical storms occurring in the future. The model predicts only minor changes in the hurricane‐induced extreme water levels for those Caribbean islands which were severely devastated by the 2017 tropical storms (Irma and Maria). That is, provided that the hurricane intensity remains at the present‐day level, the global mean sea‐level rise is the main future coastal flood risk factor.

Multi-cyclone analysis and machine learning model implications of cyclone effects on forests

Past studies of cyclones (hurricanes, typhoons, tropical cyclones) disturbance showed that meteorological, topographical, and biological factors affect the patterns of forest disturbance intensity but left open the extent to which these findings were representative across different global cyclone regions. Using remote sensing data and machine learning models, we examined how these factors change over spatial scales and assessed their consistency across four major cyclones: Katrina (August 2005), Rita (September 2005), Yasi (February 2011), and María (September 2017). Our results revealed that the factors which best explained forest disturbance intensity pattern varied across these regions. Wind speed and precipitation were the dominant factors contributing to the variation in impacts of Katrina; terrain features, especially elevation, explained most of the variation in disturbance intensity of Rita; pre-disturbance vegetation condition was significant predictors of effects of Yasi; these factors played equal roles in explaining the disturbance intensity variation of María. A 40 m/s (144 km/h) wind speed threshold was proposed to split low- and high-level forest disturbance intensity. Other than wind speed, few generalizations can be made on features across multiple regions. We built several generalized hurricane impact models, which worked well with the test data from cyclones used for model development (R2 = 0.89). However, these models did not have good predictions on other cyclones, such as Michael (October 2018) and Laura (August 2020). This study showed that each cyclone interacted with the landscape in a unique way and the challenges remained in building a generalized cyclone impact model.

Tropical cyclones shape mangrove productivity gradients in the Indian subcontinent

Recent literature on the impact of cyclones on mangrove forest productivity indicates that nutrient fertilizations aided by tropical cyclones enhance the productivity of mangrove forests. We probe the implications of these predictions in the context of Indian mangroves to propose potential future directions for mangrove research in the subcontinent. First, we look at the time series trend (2000–2020) in satellite-derived gross primary productivity (GPP) datasets for seven mangrove forests across the country’s coastline. Second, we compare seasonal changes in soil nutrient levels for a specific site to further the arguments proposed in the literature and investigate the role of potential drivers of mangrove productivity. We find overall increasing trends for GPP over the past two decades for all seven mangrove sites with seasonal fluctuations closely connected to the tropical storm activities for three sites (Bhitarkanika, Pichavaram, and Charao). Additionally, organic carbon and nitrogen levels showed no significant trend, but phosphorus levels were higher during the post-monsoon-winter period for Bhitarkanika. Our findings expand the predictions of previous studies that emphasized the role of storm-induced nutrient fluxes and freshwater supply as primary drivers of productivity gradients in mangroves. Our study provides insights on how mangrove productivity may change with fluctuating frequency and magnitude of cyclones under a changing climate, implying the need for more mechanistic studies in understanding the long-term impact on mangrove productivity in the region.

Modeling the economic impact of incoming tropical cyclones using machine learning

Modeling the economic impact of incoming tropical cyclones using machine learning

A Cloud Native Machine Learning based Approach for Detection and Impact of Cyclone and Hurricanes on Coastal Areas of Pacific and Atlantic Ocean

Tropical Storms are one of the most dangerous natural disasters known to man. The concept of predicting these has been around for as long as they have existed. Improvements are made to reduce the error using newer techniques or better processes. In this research paper, we are trying to predict the occurrence of storms from the Pacific and the Atlantic Oceans on American land. The data is used to train various machine learning models and comparison is drawn between them to conclude the best for our application. The results are then shown on a map to get a visual representation using the folium library. The entire project is also deployed using Microsoft Machine Learning Azure to help with deployment over the web service. This paper hopes to present a system that accurately predicts and efficiently presents everything regarding the real-time occurrence of hurricanes and typhoons.

Do cyclone impacts really matter for the long-term performance of an offshore wind turbine?

With the transition on planning and construction of offshore wind turbine (OWT) from North Europe to other regions like America and East Asia, challenges are proposed for the direct application of international OWT experience to these territories due to disparate natural condition like cyclones. This article is intended to evaluate the impact of cyclone on the long-term performance of an OWT to be installed in cyclone-prone regions. To have a comprehensive consideration on the aero-hydro-structural-soil interaction, an improved decoupled method is proposed and validated for an onshore wind turbine before its application to an OWT. Two cyclone models combined with two wave theories are considered in the fatigue evaluation of an OWT under different working status, and their implications on the final estimation of fatigue damage are compared and discussed. The results obtained from this study indicate that the fatigue life reduction which is caused by cyclone, for an OWT can be conspicuous for a reasonable cyclone strength and average recurrence interval. This implies that potential premature failure of an OWT tower and relevant economic losses can be encountered during its service life if the cyclone contribution to fatigue damage is ignored in the initial conceptual design.

Summer Extreme Cyclone Impacts on Arctic Sea Ice

AbstractIn this study the impact of extreme cyclones on Arctic sea ice in summer is investigated. Examined in particular are relative thermodynamic and dynamic contributions to sea ice volume budgets in the vicinity of Arctic summer cyclones in 2012 and 2016. Results from this investigation illustrate that sea ice loss in the vicinity of the cyclone trajectories during each year was associated with different dominant processes: thermodynamic processes (melting) in the Pacific sector of the Arctic in 2012, and both thermodynamic and dynamic processes in the Pacific sector of the Arctic in 2016. Comparison of both years further suggests that the Arctic minimum sea ice extent is influenced by not only the strength of the cyclone, but also by the timing and location relative to the sea ice edge. Located near the sea ice edge in early August in 2012, and over the central Arctic later in August in 2016, extreme cyclones contributed to comparable sea ice area (SIA) loss, yet enhanced sea ice volume loss in 2012 relative to 2016. Central to a characterization of extreme cyclone impacts on Arctic sea ice from the perspective of thermodynamic and dynamic processes, we present an index describing relative thermodynamic and dynamic contributions to sea ice volume changes. This index helps to quantify and improve our understanding of initial sea ice state and dynamical responses to cyclones in a rapidly warming Arctic, with implications for seasonal ice forecasting, marine navigation, coastal community infrastructure, and designation of protected and ecologically sensitive marine zones.

Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 2: Modeling Component of the Research Program RENOVRISK-CYCLONE

The ReNovRisk-Cyclone program aimed at developing an observation network in the south-west Indian ocean (SWIO) in close synergy with the implementation of numerical tools to model and analyze the impacts of tropical cyclones (TC) in the present and in a context of climate change. This paper addresses the modeling part of the program. First, a unique coupled system to simulate TCs in the SWIO is developed. The ocean–wave–atmosphere coupling is considered along with a coherent coupling between sea surface state, wind field, aerosol, microphysics, and radiation. This coupled system is illustrated through several simulations of TCs: the impact of air–sea flux parameterizations on the evolution of TC Fantala is examined, the full coupling developed during the program is illustrated on TC Idai, and the potential of novel observations like space-borne synthetic aperture radar and sea turtles to validate the atmosphere and ocean models is presented with TC Herold. Secondly, the evolution of cyclonic activity in the SWIO during the second half of the 21st century is assessed. It was addressed both using climate simulation and through the implementation of a pseudo global warming method in the high-resolution coupled modeling platform. Our results suggest that the Mascarene Archipelago should experience an increase of TC related hazards in the medium term.

The impact of energetic tropical cyclones (typhoons) on the modern sediment magnetism along the South China coast

Tropical cyclones (TCs) often affect the surface sediments of coastal areas, and impact the sediment imprint. Although the sediment magnetism is sensitive to coastal changes, the understanding of the coastal magnetic minerals’ redistribution affected by TCs is far from adequate. Here, the magnetic and grain-size records from the seafloor sediments along the Leizhou Peninsula coast in South China before and after two violent TCs (Mangkhut and Barijat) occurred in September 2018 are present. The magnetic minerals mainly consist of magnetite, hematite, and goethite. For most sites, the content of hematite increased compared to magnetite and the magnetic minerals became coarser after the TCs subsided, while the amount of fine clay (<2 μm) decreased and the amount of coarse sand (500–2000 μm) increased. This is due to the preferential deposition of the lamellae hematite from the soils and the enhanced hydrodynamic transportation of suspended sediments. The mangrove forest resists the change to a certain degree, especially in the Leizhou Bay. The magnetic and grain-size properties are sensitive to the TC-induced deposits, and provide convincing tools to aid in detecting the paleo-TC activity in tropical coastal regions.

Impact of cyclones on hard coral and metapopulation structure, connectivity and genetic diversity of coral reef fish

Cyclones have one of the greatest effects on the biodiversity of coral reefs and the associated species. But it is unknown how stochastic alterations in habitat structure influence metapopulation structure, connectivity and genetic diversity. From 1993 to 2018, the reefs of the Capricorn Bunker Reef group in the southern part of the Great Barrier Reef were impacted by three tropical cyclones including cyclone Hamish (2009, category 5). This resulted in substantial loss of live habitat-forming coral and coral reef fish communities. Within 6–8 years after cyclones had devastated, live hard corals recovered by 50–60%. We show the relationship between hard coral cover and the abundance of the neon damselfish (Pomacentrus coelestis), the first fish colonizing destroyed reefs. We present the first long-term (2008–2015 years corresponding to 16–24 generations of P. coelestis) population genetic study to understand the impact of cyclones on the meta-population structure, connectivity and genetic diversity of the neon damselfish. After the cyclone, we observed the largest change in the genetic structure at reef populations compared to other years. Simultaneously, allelic richness of genetic microsatellite markers dropped indicating a great loss of genetic diversity, which increased again in subsequent years. Over years, metapopulation dynamics were characterized by high connectivity among fish populations associated with the Capricorn Bunker reefs (2200 km2); however, despite high exchange, genetic patchiness was observed with annual strong genetic divergence between populations among reefs. Some broad similarities in the genetic structure in 2015 could be explained by dispersal from a source reef and the related expansion of local populations. This study has shown that alternating cyclone-driven changes and subsequent recovery phases of coral habitat can greatly influence patterns of reef fish connectivity. The frequency of disturbances determines abundance of fish and genetic diversity within species.

Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 1: Overview and Observing Component of the Research Project RENOVRISK-CYCLONE

The international research program “ReNovRisk-CYCLONE” (RNR-CYC, 2017–2021) directly involves 20 partners from 5 countries of the south-west Indian-Ocean. It aims at improving the observation and modelling of tropical cyclones in the south-west Indian Ocean, as well as to foster regional cooperation and improve public policies adapted to present and future tropical cyclones risk in this cyclonic basin. This paper describes the structure and main objectives of this ambitious research project, with emphasis on its observing components, which allowed integrating numbers of innovative atmospheric and oceanic observations (sea-turtle borne and seismic data, unmanned airborne system, ocean gliders), as well as combining standard and original methods (radiosoundings and global navigation satellite system (GNSS) atmospheric soundings, seismic and in-situ swell sampling, drone and satellite imaging) to support research on tropical cyclones from the local to the basin-scale.

The Impact of Tropical Cyclones in Premonsoonal Season on Local Convection over the Al-Hajar Mountains in Oman during 2007–2018

The tropical cyclones (TCs) and convective storms have a significant impact on triggering widespread flooding in vulnerable areas. However, it is not clear whether the TCs stimulate the convective precipitation over the Al-Hajar Mountains in Oman or suppress it although it had been shown in many studies that TCs suppress the local convection development. This study aims to test the applicability of the hypothesis that the TCs suppress the convection over mountainous to the Al-Hajar Mountains. In order to test the hypothesis of tropical cyclones’ impact on local convection development over the Al-Hajar Mountains, this study considers three different cases during the premonsoon season between 2007 and 2018. The results revealed that weak local convection is reported over the Al-Hajar Mountains during the presence of the cyclones in the Arabian Sea and during the period of their direct impacts. The rainfall in these cases was mainly from stratiform clouds. Therefore, the impact of TCs on the convective suppression over the mountains is applicable to the Al-Hajar Mountains. This study will provide decision-makers and policy creators with knowledge as to whether the Al-Hajar Mountains are susceptible and vulnerable to the risk of torrential downpour, flash flooding, and thunderstorms as what is believed to be.

Spatiotemporal patterns and impact of a cyclone on the zooplankton community structure in a brackish coastal lagoon

Zooplankton communities in response to hydrological (salinity, turbidity, water temperature, nitrate, phosphate, silicate) and biological (phytoplankton density) variables were studied in the Asia’s largest brackish water lagoon, Chilika (India). Water samples were collected from 13 stations on a monthly frequency between July 2014–June 2015. A total of 141 species of holoplankton including Ciliophora, Foraminifera, Rotifera, Rhizopoda, Gastropoda, Cladocera, Copepoda, Ostracoda, Malacostraca, Chaetognatha, Chordata, Nematoda, and 18 types of planktonic larvae were identified. Copepods were the most dominant and diverse zooplankton in terms of their species richness, numerical abundance, and widespread distribution in the lagoon. The major holoplanktonic taxa were Acartia sp., Acrocalanus gibber, Acrocalanus gracilis, Acrocalanus longicornis, Euterpina acutifrons, Lecane sp., Oithona sp., Pseudodiaptomus serricaudatus, and Tintinnopsis tubulosa. The dominant planktonic larvae were bivalve veliger, copepod nauplii, cyphonautes larvae, gastropod veliger, and protozoea of lucifer. Canonical correspondence analysis showed that distribution of zooplankton assemblages was influenced by salinity, turbidity, and phytoplankton density. Indicator analysis demarcated 26 indicator zooplankton taxa. Of these, the most prominent indicator zooplankton such as Belzebub hanseni, Mesopodopsis orientalis, Chydorus sphaericus, and Corycaeus catus were characteristic to salinity gradient in southern sector, sediment resuspension in central sector, eutrophic conditions in northern sector, and tide-induced intrusion of marine forms in outer channel, respectively. Hudhud, a category 4 cyclone resulted decline in the abundances of zooplankton population. Copepod nauplii and copepodites were dominant during post-Hudhud and their succession was linked to the increased phytoplankton density due to an upsurge in the nutrient level in the northern sector of the lagoon. The present study provided a comprehensive detail on the zooplankton composition and their environmental drivers including the impact of a tropical cyclone from a tropical coastal lagoon system.