Impact Of Storms Research Articles

Threats of tropical cyclone on cropping systems and crop calendar of rice in India: Issues, policy practice gap and adaptation strategies

The Food and Agriculture Organization (FAO) has calculated that by 2050, we will need to grow 60 % more food to provide for a population of 9.3 billion people worldwide. India must increase its yearly food grain production from the current level of 252–333 million tonnes by 2050 in order to fulfil its expanding population demand. India is one of the nations most at risk from climate change due to its geophysical location and variability. This research explored the impact of cyclonic storm surges on crop calendars (‘Aman’ and ‘Boro’ rice) and also suggested adaption strategies during these conditions. This study showed that alteration of contemporary rice sowing and harvesting dates significantly impacts achieving sustained yields, surpassing all other crop management, soil, and other criteria. The origin and landfall of the cyclone of the Bay of Bengal (BoB) in pre- and post-monsoon season impede the goal of optimal rice production in Eastern and south-eastern India. We have estimated that ‘Rabi’ and ‘Kharif” rice production potential will increase by about 29 % with attainable changes to rice sowing and harvesting dates incorporating the severe cyclonic storm (SCS) landfall and rainfall in the study area. Our results also show that transformational benefits in rice yields are only possible in India if the convectional crop calendar changes with the modern scientific crop calendar. Managing the seasonal cropping calendar more effectively can benefit food security, economic success, and climate adaptability rice seed as a method for adaptation to ongoing climate change.

Long-range transport impact of a severe dust storm over the Yangtze River Basin region and its modeling sensitivity to dust emission scheme

Dust storms frequently occur in the spring over East Asia, affecting southern Mongolia and northeast China. An exceptionally powerful dust storm occurred in East Asia from March 14th to March 18th, 2021. To investigate the ability of climate models to simulate severe dust storms, we employed the Weather Research Forecast model coupled with chemistry (WRF-Chem) with Goddard Chemistry Aerosol Radiation and Transport (GOCART), SHAO and KOK dust emission schemes to simulate the evolution of this event and to characterize dust aerosols long-range transport. Results showed that this storm was caused by a Mongolian cyclone depicted at 850 hPa with a cold front, which swept dust aerosols southeastward across southern Mongolia to northeast China. Model evaluation with satellite-retrieved Aerosol Optical Depth (AOD) and observational PM10 concentrations revealed that the SHAO dust emission scheme performed better in simulating spatial and temporal distribution of AOD over the Gobi Desert (GD) but overestimated them over Taklimakan Desert (TD). In contrast, the GOCART dust emission scheme underestimated AOD over most areas except the Taklimakan Desert; the KOK dust emission scheme overestimated them over both TD and GD. Overall, the SHAO dust emission scheme had good performance in simulating the surface PM10 concentrations over the Yangtze River Basin (YRB) and depicted an increase in PM10 concentrations, which denoted the transport of dust aerosols over YRB. As a better description of the physical process of dust emission flux over the eastern region of the Gobi Desert, the SHAO dust emission scheme depicted well the spatial and temporal evolution of dust plume episodes, especially over northeast China and YRB. The significant differences in dust emission fluxes between the three dust emission schemes were attributed to the sensitivity of threshold friction velocity and erodibility factor. Thereunto, the SHAO dust emission scheme incorporated well soil particle size distribution and threshold velocity to produce the dust emission flux, which allowed higher dust emission flux over the eastern GD and under strong southwesterly transported dust aerosols to East Central China's region of North China Plain (NCP) and YRB. This study will help further the simulation of extreme dust events more accurately and the exploration of climate change's effect on dust events over East Asia.

Impacts of sand and dust storms on food production

Abstract Sand and dust storms (SDS) are common in the world’s drylands, regions that are also critically important for global food production. Agriculture is the most prevalent land use resulting in anthropogenic SDS sources, resulting in impacts on cropland and rangeland, but food production is also affected by impacts from natural SDS sources. This review assesses our knowledge of SDS impacts on all the major types of food production in terrestrial and oceanic environments, impacts that occur in all three phases of the wind erosion system: during particle entrainment, during transport, and on deposition. These effects are short term and long term, direct and indirect. Wind erosion is a major cause of land degradation and there is good evidence to indicate that the deleterious effects of SDS can reduce food production via substantially diminished yields of crops, pastures and livestock. However, it is also clear that soil dust plays an important role in major biogeochemical cycles—especially phosphorus, nitrogen and iron—with implications for the valuable environmental services provided by numerous ecosystems, both terrestrial and marine. Ultimately, these nutrients have particular significance for soil formation, ecosystem productivity and food webs on land and at sea, and hence the provision of food for human societies. Efforts to mitigate the negative impacts of SDS on the sustainability of agriculture should be balanced with an appreciation of the significance of soil dust to the Earth system.

Prediction of Pier Scour Depth under Extreme Typhoon Storm Tide

The Western Pacific region is highly vulnerable to typhoon storm surge disasters, with localized erosion posing a particularly prominent issue for coastal marine structures. The prevalence of extreme typhoon storm surges poses a significant threat to the safety of engineering projects in these areas. In this study, a parameterized wind field model with precise calculation of wind speed was employed to establish a numerical model for typhoon storm tides. Based on the Western Pacific typhoon data from 1949 to 2023, hydraulic simulations were conducted for Hangzhou Bay, Xiangshan Port, and Yueqing Bay, revealing maximum flow velocities of 4.5 m/s, 1.95 m/s, and 2.09 m/s, respectively. These velocities exceeded the maximum possible tidal flow by 0.47–1.17 m/s. Additionally, using Sun’s velocity formula, the initiation flow velocities were calculated to be 1.85 m/s, 1.81 m/s, and 2.06 m/s for the aforementioned locations. Through localized erosion tests conducted around typical bridge piers and the subsequent application of similarity criteria, the maximum depth of localized erosion in the study area was determined to range from 2.16 m to 16.1 m, which corresponds to 1.1–2.3 times the scour caused by the maximum tidal flow scenario. A comparison of the erosion test results with calculations based on several formulas demonstrated that the scour prediction formula proposed by Sun exhibited the highest accuracy. This study supplements the understanding of the impact of typhoon storm surges on bridge pier erosion and provides a scientific basis for the design of bridge foundations.

Optimizing coastal protection: Nature-based engineering for longitudinal drift reversal and erosion reduction

Traditional hard engineering solutions have shown weaknesses in mitigating erosion processes in vulnerable coastal areas, contributing in some cases to their aggravation, which makes it necessary to study innovative nature-based engineering solutions. This research deals with an in-depth analysis of hydro-morphodynamic modelling results for optimizing the geometry of maritime structures under longitudinal drift reversal conditions by mimicking and manipulating natural processes to promote wave energy dissipation and sediment retention through wave deformation due to obstacle interposition. The solutions draw inspiration from the full-scale observation data of two examples of longitudinal drift reversal. Additionally, numerical simulations were developed for predicting wave climate near the Iberian Peninsula shoreline under different scenarios. Hydrodynamics and morphodynamics modelling results are discussed based on the impact of a specific storm, considering different characteristics of protection structures, followed by parametric sensitivity analysis and comparative studies performed with an optimized solution. Results indicated this solution contributed to sediment accumulation downdrift near the shoreline, as there is no interruption of the longitudinal drift compared to traditional protection structures. At the alignment, the structure also improved nearshore sediment accretion, reduced areas of erosion relative to a no-structure scenario and exhibited behaviour akin to an emerged structure with its crest level. Compared to wholly submerged structures, it becomes a relevant coastal protection alternative, as it guarantees excellent protection on the adjacent coastal zone by safeguarding against tidal variations induced by storm surges and mean sea level rise due to climate change. Furthermore, there is a positive effect to help promote biodiversity whenever the structure is located in an intertidal zone. Despite the enormous computational effort required in the hydro-morphodynamic modelling process, this study shows that it is possible to create innovative engineering coastal solutions to induce longitudinal drift reversal and reduce erosion near the shoreline.

Inner Radiation Belt Simulations During the Successive Geomagnetic Storm Event of February 2022

AbstractStarting from 29 January 2022, a series of solar eruptions triggered a moderate geomagnetic storm on 3 February 2022, followed subsequently by another. Despite the typically minimal impact of unintense storms on space technology, 38 out of the 49 Starlink satellites underwent orbital decay, re‐entering Earth's atmosphere. These satellite losses were attributed to enhanced atmospheric drag conditions. This study employs numerical simulations, utilizing our test particle simulation code, to investigate the dynamics of the inner radiation belt during the two magnetic storms. Our analysis reveals an increase in proton density and fluxes during the transition from the recovery phase of the first storm to the initial phase of the second, primarily driven by intense solar wind dynamic pressure. Additionally, we assess Single Event Upset (SEU) rates, which exhibit a 50% increase in comparison to initial quiet conditions.

The Effects of Dust Storms on People Living in Beijing: A Qualitative Study.

Dust storms, which are common aversive occurrences in northern China, result from high winds, dry soil or dust, and soil surface disturbance. Exposure to dust storms, regardless of duration, can induce varying mental and physical distress levels. Recognizing the urgency of comprehending the impact of dust storms on residents and the scarcity of information on their effects on the indigenous civilians there, this study aims to address this gap by qualitatively sampling 29 participants from Beijing, a typical city in northern China. The current study seeks to gain insights into residents' dust storm experiences and explore their perspectives on effective coping mechanisms. The findings align with existing knowledge regarding the mental and physical repercussions of dust storms while identifying some emerging patterns of coping mechanisms already employed by residents in Beijing. Concerns regarding mental well-being, either directly influenced by the environmental conditions or indirectly stemming from disruptions to life routines on a broader scale, persistently dominate people's perceptions of dust storms. New themes emerged following the step-by-step exploration of feelings and coping mechanisms. This study aims to enlighten the public about the ramifications of the dust storms in Beijing and advocate for essential policy support.

Climate change impact and adaptation assessment for road drainage systems

Climate change exhibits a clear trend of escalating frequency and intensity of extreme weather events, posing heightened risks to drainage systems along the existing road networks. However, very few studies to date have investigated the consequences of projected future changes in rainfall on main road drainage and the resulting risk of road flooding. The work presented in this paper builds on the limited research by introducing a probabilistic model for assessing the impact of climate change on road drainage systems, incorporating climate uncertainty and drainage system variation. The probabilistic scenario-based model and associated framework offer a practical and innovative method for estimating the impact of short-duration storms under future climates for 2071–2100, in the absence of fine-resolution spatio-temporal data. The model also facilitates the assessment of the effectiveness of a climate adaptation strategy. An illustrative case-study of a road drainage system located in the south of Ireland is presented. It was found that the probability of road flooding during intense rainfall is projected to surpass the current acceptable limits set by Irish standards. Assessment of a proactive climate adaptation strategy implemented in 2015 indicated it may need to be adjusted to further reduce climate change impacts and optimise adaptation costs.

Association of Asian dust storms and PM2.5 with clinical visits for respiratory diseases in children

East Asia dust storms originated in China, bringing abundant suspended particulate matters (PMs), are investigated to examine the association between their arrivals and clinical visits for respiratory diseases (RCV – Respiratory disease Clinical Visit). Taiwan, located in the downwind with a well-documented health database from the National Health Insurance, is selected for the study. Children under the age of 17 years, because of their regular daily activities and outdoor exposures, who are diagnosed with respiratory disease, are our targeted population. We conducted a case-crossover design and used the conditional regression analysis to explore the relationship between the dust storms and RCV, for cases between 2000 and 2012, when severe dust storms were mostly recorded. In total, 2,253,092 patients were recruited. The analysis shows that the coming of dust storms significantly affects the condition of RCV in children. After adjusting for temperature, relative humidity, and air pollutant concentrations, dust storm in springtime is associated with an increase in RCV. In contrast, dust storm impact in wintertime is associated with a decrease in RCV. In addition, PM2.5 concentrations associated positively with RCV among children, especially in the southern region of Taiwan in springtime and in the central and southern regions of Taiwan in wintertime. In short, the results showed that the occurrence of dust storms affects the RCV in children. PM2.5 exposure is also responsible for the increase in children's RCV.

The Atmospheric Heating Mechanism over the Tharsis Bulge of Mars and the Impact of Global Dust Storms

Mars atmospheric dynamics are crucial for understanding its climate and weather patterns, especially over plateaus. Previous studies have explored localized atmospheric heating mechanisms over Mars plateaus only to a little extent. The local atmospheric heating dynamics over the Tharsis plateau, especially during global dust storms (GDSs), have not been quantitatively analyzed before. Based on reanalysis datasets, our analysis reveals that the central highlands of Tharsis experience ~130 K diurnal temperature fluctuations, driven by intense daytime convective activity. Surface temperature and near-surface air temperatures show fluctuations approximately 25 K and 20 K higher than those at similar latitudes, respectively. We quantify a super-adiabatic lapse rate around noon that suggests strong atmospheric instability, previously unquantified in this region. By dusk, the atmosphere stabilizes, presenting a homogenized condition. At aphelion, sensible heating and adiabatic terms control the atmospheric heating, while, at perihelion, radiative and sensible heating predominate. Notably, the onset of GDS significantly alters this dynamic, reducing the ground–air temperature gap from 17 K to 5 K and enhancing diabatic heating (adiabatic cooling) in the mid-to-lower (mid-to-upper) troposphere, with increases in radiative components up to 60 W/m2.

Impact of Hurricane Irma on coral reef sediment redistribution at Looe Key Reef, Florida, USA

Abstract. Understanding event-driven sediment transport in coral reef environments is essential to assessing impacts on reef species, habitats, restoration, and mitigation, yet a global knowledge gap remains due to limited quantitative studies. Hurricane Irma made landfall in the Lower Florida Keys with sustained 209 km h−1 winds and waves greater than 8 m on 10 September 2017, directly impacting the Florida Reef Tract (FRT) and providing an opportunity to perform a unique comprehensive, quantitative assessment of its impact on coral reef structure and sediment redistribution. We used lidar and multibeam derived digital elevation models (DEMs) collected before and after the passing of Hurricane Irma over a 15.98 km2 area along the lower FRT including Looe Key Reef to quantify changes in seafloor elevation, volume, and structure due to storm impacts. Elevation change was calculated at over 4 million point locations across 10 habitat types within this study area for two time periods using data collected (1) approximately 1 year before the passing of Irma and 3 to 6 months following the storm's impact as well as (2) 3 to 6 months after and up to 16.5 months after the storm. Elevation change data were then used to generate triangulated irregular network (TIN) models in ArcMap to calculate changes in seafloor volume during each time period. Our results indicate that Hurricane Irma was primarily a depositional event that increased mean seafloor elevation and volume at this study site by 0.34 m and up to 5.4 Mm3, respectively. Sediment was transported primarily west-southwest (WSW) and downslope, modifying geomorphic seafloor features including the migration of sand waves and rubble fields, formation of scour marks in shallow seagrass habitats, and burial of seagrass and coral-dominated habitats. Approximately 16.5 months after Hurricane Irma (during a 13-month period between 2017 and 2019), net erosion was observed across all habitats with mean elevation change of −0.15 m and net volume change up to −2.46 Mm3. Rates of elevation change during this post-storm period were 1 to 2 orders of magnitude greater than decadal and multi-decadal rates of change in the same location, and changes showed erosion of approximately 50 % of sediment deposited during the storm event as seafloor sediment distribution began to re-equilibrate to non-storm sea-state conditions. Our results suggest that higher-resolution elevation change data collected over seasonal and annual time periods could enhance characterization and understanding of short-term and long-term rates and processes of seafloor change.

Assessing hurricane impact on vegetation and endangered deer habitat using airborne lidar and multispectral images

In the lower Florida Keys, the endangered Florida Key deer and numerous other wildlife species inhabit a vulnerable island environment susceptible to storm surges and rising seawater due to low elevation and flat terrain. Timely and reliable assessment of vegetation damage from natural disasters, such as Hurricane Irma, is crucial for effective habitat management. The study’s overall objective is to examine Hurricane Irma’s impact on vegetation on No Name Key, Florida, using remote sensing. The study relates the area change in vegetation obtained from remote sensing analysis to Florida Key deer population changes following the storm. The methodology involved performing a thematic change detection analysis using the following data sources: (1) aerial multispectral images (for pre- and post-Hurricane), (2) airborne lidar data (for pre- and post-Hurricane), (3) an existing vegetation map, and (4) soil data. A Support Vector Machine (SVM) image classification algorithm was applied to pre- and post-storm input image stacks to create pre- and post-Hurricane Irma vegetation maps. We were then able to obtain the area change information (for various vegetation categories) by performing the change detection analysis of the 2 SVM-classified images. The differences in areas following the storm were calculated for 7 affected vegetation types. Using the area change information following Hurricane Irma, we estimated the number of deer supported by the storm-affected vegetation. These estimated deer numbers, based on the area differences in post-Hurricane Irma vegetation types, were compared to observed deer numbers collected during the post-Hurricane Irma Texas A&M Natural Resources Institute (NRI) deer field survey. The results showed the following: mangroves had the largest negative area changes (area loss), followed by pinelands, hardwoods/hammocks, developed areas, and buttonwoods. Freshwater marshes had the largest positive area changes (area gain). The deer's preferred vegetation areas had decreased post-Hurricane Irma, resulting in a reduced deer population compared to pre-storm numbers. The predicted number of the Key deer post-Hurricane Irma fell within a 95% confidence interval of the observed deer population from the post-storm field survey. The study findings and techniques could be applied to study climate change impact, especially sea level rise. This methodology can be valuable in assessing the impact of storms on other wildlife species in similar environments. The applications and methodology are especially relevant considering the increasing frequency and intensity of storm surges and the accelerating rate of sea level rise.

Harnessing LSTM and XGBoost algorithms for storm prediction

Storms can cause significant damage, severe social disturbance and loss of human life, but predicting them is challenging due to their infrequent occurrence. To overcome this problem, a novel deep learning and machine learning approach based on long short-term memory (LSTM) and Extreme Gradient Boosting (XGBoost) was applied to predict storm characteristics and occurrence in Western France. A combination of data from buoys and a storm database between 1996 and 2020 was processed for model training and testing. The models were trained and validated with the dataset from January 1996 to December 2015 and the trained models were then used to predict storm characteristics and occurrence from January 2016 to December 2020. The LSTM model used to predict storm characteristics showed great accuracy in forecasting temperature and pressure, with challenges observed in capturing extreme values for wave height and wind speed. The trained XGBoost model, on the other hand, performed extremely well in predicting storm occurrence. The methodology adopted can help reduce the impact of storms on humans and objects.

Landcover-based detection of rapid impacts of extreme storm on coastal landscape

On September 24, 2022, Post-Tropical Hurricane Fiona made landfall in Atlantic Canada and caused unprecedented damages to the coastal communities and ecosystems therein. The aftermath triggered local government and communities in Prince Edward Island (PEI), Canada to rethink current policies and practices for coastal protection in the context of climate change. This historic hazard represents the escalating frequency and intensity of extreme weather events that globally threaten coastal regions, accelerating coastal erosion and endangering communities. This study employs landcover-based detection to assess rapid storm impact of Fiona on coastline of PEI using Sentinel-2 satellite images, to gauge the efficacy of landcover-based detection and quantify storm-induced coastal environmental changes. Our results indicate that, following Fiona, over 51 km2 coastal land loss due to the erosion at beach foreshore and inundation at tidal flat, and over 11 km2 sand dune loss mainly on the PEI north shore. This constitutes a 3.5 % loss of coastal land resources within the 1798 km2 PEI coastal zone. Fiona also caused over 194 km2 area in coastal buffer zone showed temporal fluid-mud from the eroded sediments of sand dunes, cliffs, and tidal flats, suggesting the significant sediment loss from vertical structures in addition to the direct retreat. The landcover-based method can be regarded as a valuable tool for the storm impacts on coastal environments. Based on the coastal change pattern, more sustainable coastal protection and adaptation measures should be developed, focusing on reducing hydrodynamic intensity and improving erosion capacity, with consideration of the increasing likelihood of more intense and frequent storm events in a warming climate.

Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains

Abstract. The Taklamakan Desert (TD) is a major source of mineral dust emissions into the atmosphere. These dust particles have the ability to darken the surface of snow on the surrounding high mountains after deposition, significantly impacting the regional radiation balance. However, previous field measurements have been unable to capture the effects of severe dust storms accurately, and their representation on regional scales has been inadequate. In this study, we propose a modified remote-sensing approach that combines data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and simulations from the Snow, Ice, and Aerosol Radiative (SNICAR) model. This approach allows us to detect and analyze the substantial snow darkening resulting from dust storm deposition. We focus on three typical dust events originating from the Taklamakan Desert and observe significant snow darkening over an area of ∼ 2160, ∼ 610, and ∼ 640 km2 in the Tien Shan, Kunlun, and Qilian mountains, respectively. Our findings reveal that the impact of dust storms extends beyond the local high mountains, reaching mountains located approximately 1000 km away from the source. Furthermore, we observe that dust storms not only darken the snowpack during the spring but also in the summer and autumn seasons, leading to increased absorption of solar radiation. Specifically, the snow albedo reduction (radiative forcing) triggered by severe dust deposition is up to 0.028–0.079 (11–31.5 W m−2), 0.088–0.136 (31–49 W m−2), and 0.092–0.153 (22–38 W m−2) across the Tien Shan, Kunlun, and Qilian mountains, respectively. This further contributes to the aging of the snow, as evidenced by the growth of snow grain size. Comparatively, the impact of persistent but relatively slow dust deposition over several months during non-event periods is significantly lower than that of individual dust events. This highlights the necessity of giving more attention to the influence of extreme events on the regional radiation balance. This study provides a deeper understanding of how a single dust event can affect the extensive snowpack and demonstrates the potential of employing satellite remote sensing to monitor large-scale snow darkening.

Responses of Mesosphere Temperature to the Geomagnetic Storms on 8 and 15 September 2003

AbstractThe impact of geomagnetic storms on the mesosphere temperature has been controversial and lacks direct observational evidence. The intricate chemical and physical processes in the mesosphere, combined with the scarcity of observations, pose challenges to achieving a thorough comprehension of storm‐induced turbulences in this region. Currently, some investigations have characterized temperature responses during geomagnetic storms and the focus has largely been on changes above mesopause (∼90 km). In this work, the responses of temperature in the mesosphere (75–95 km) to the storms on September 8 and 15, 2003 and its causes are studied using observations from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite. It is found that (a) temperature responses for the moderate storm on September 15 manifest as increases within the latitude range of 80°S to 65°S, with peak values decreasing from approximately 15 K to around 7 K as latitude decreases, while for the minor strom of September 8 temperature changes only occur at ∼80°S with peaks of 7 K and −10 K, (b) the temperature responses can be transmitted down to 76–81 km, depending on the latitude and storm magnitude, and (c) there are significant fluctuations in both ozone (exceed 45%) and atomic oxygen (exceed 90%) after storm onset, highly correlated with temperature temporal and spatial variations. We suggest that the increases in ozone caused by the increases in atomic oxygen concentrations are the major contributor to rising temperature.

Magnetospheric Time‐History in Storm‐Time Magnetic Flux Dynamics: A Global Simulation Campaign

AbstractThis paper aims to quantify the magnetospheric magnetic flux contents under moderate to intense space weather conditions using global simulations. This study is a companion to Akhavan‐Tafti, Atilaw, et al. (2023, https://doi.org/10.1029/2023JA031832) where magnetic flux evolution is presented for a catalog of storm events, using Heliophysics System Observatory (HSO) observations. For this study, we used the Space Weather Modeling Framework (SWMF) in Geospace configuration to study magnetic flux dynamics for a subset of their storm events (15 events). Simulations reliably resolve the storm‐time magnetic flux Bz and current density |J| asymmetries across the different storm phases. It is revealed that: relative to the quiet period, flux content is enhanced during the storm sudden commencement (SSC) phase in the dayside by ΔBz/Bz, quiet = +17%, and reduced in the nightside magnetosphere (r[RE] < −6 RE) by −15%. At the same time, the cross‐tail current is found to enhance (|J| = 2 nA/m2), which suggests the storm impact in the nightside magnetosphere is much earlier in the storm cycle than previously shown. Concurring with previous studies, a significant depletion of magnetic flux by up to −40%, with day‐night and dawn‐dusk asymmetries, can be seen during the main and recovery phases. This corresponds to the enhanced current density (|J| = 5–8 nA/m2) at ∼6 RE further confirming the role of ring current in driving magnetospheric dynamics during the main and recovery phases. This is in contrast with the SSC phase wherein the Chapman‐Ferraro and cross‐tail currents are the dominant current systems.

Storm surge induced by 2019 Tropical Storm Pabuk and impact on the shoreline in Kuala Nerus Terengganu, east coast of Peninsular Malaysia

This study investigates the one-year shoreline impacts of 2019 Tropical Storm Pabuk and the morphological changes of beaches in the study area of Kuala Nerus in Malaysia mediated by the hydrodynamic conditions. The study used a numerical model that utilised the two-way coupling of the wave and hydrodynamic model of MIKE 21 to simulate the event. The impact of the event was determined by employing the Digital Shoreline Analysis System, along with regular in-situ measurements of beach profiles carried out monthly. The results show a significant retreat rate of −58 m/year at Tok Jembal, highlighting the significant erosive impact, particularly on the northwest side of the airport. Despite a storm surge height below the extreme thresholds (>1 m), the beach morphology and the presence of coastal protection structures exerted a significant modulating influence. Batu Rakit, which is characterised by a wide beach, exhibited increased wave run-up and erosion resulting from the combined effect of a tidal surge of 0.64 m and significant wave heights of more than 1.12 m. UMT and Teluk Ketapang, on the other hand, which are shielded by coastal structures and influenced by longshore currents, experienced beach accretion. The intensification of the recirculation current with the surge is postulated to have contributed to the pronounced erosion at Pengakalan Maras. Although the overall magnitude of the storm surge was not exceptional, this study emphasises the importance of studying the effects of storm surges on monsoonal coasts. The intricate interplay between waves and currents, elucidated by coupled hydrodynamic and wave modelling, is crucial for understanding the consequences of storms and for proactive coastal management strategies. This study emphasises the crucial role of detailed hydrodynamic modelling in developing effective erosion control measures, which is an ongoing challenge for coastal communities.

Biogeochemical dynamics in a marine storm demonstrates differences between natural and anthropogenic impacts

This study explores the impact of a wind storm on sediment resuspension and marine biogeochemical dynamics. Additionally, the storm took place during an expedition researching bottom trawling, enabling the direct comparison of certain natural and fisheries-related disturbances. The storm was initiated by a decline in atmospheric pressure and a 2 h period of gale force winds, which was followed by over 40 h of elevated bottom currents. Storm induced turbidity, potentially a cumulative post-fishing impact, was remarkably higher compared to what was observed in a recent trawling event. Storm-induced mixing and movement of water masses led to decreased silicate and increased phosphate concentrations in the water column, accompanied by lower salinity and higher fluorescence. The erosion depth of the seabed averaged around 0.3 cm during the peak turbidity period. Trawl-induced erosion in the area has been measured at over twice that depth, and has been linked to intermittent reductions in near-bed oxygen levels. In contrast, storm-induced turbidity coincided with increased oxygen due to wave mixing, suggesting inherent differences in how trawling and storms can oxidize reduced substances. These findings suggest that storms have a greater regional impact, whereas the local impacts of bottom trawling on biogeochemistry can be more significant.

The hard impact low probabilities’ impacts on power distribution system economy

Electricity distribution systems benefit customers, investors, and operational managers economically. However, natural hazards pose significant risks to these networks, contributing to economic instability. This study assesses the impact of low-probability, high-impact events, particularly storms, on asset management and lifespan within the electricity distribution industry. By introducing three key indicators—rate of return, service rate, and cost per asset—the research investigates how different assets respond to various risks. Each asset has a distinct threshold for risk tolerance, which diminishes as its lifespan increases. Utilizing a cost model and analyzing breakpoint curves, the study evaluates the effects of high impact and low probability (HILP) incidents on the indicators mentioned earlier, factoring in asset composition changes. The study assesses the impact of storms with varying intensities on a sample network by formulating economic relations and allocating budgets for HILP events across different network conditions. Results highlight the allocation of budgetary resources for securing assets of different ages within the network. Furthermore, sensitivity analysis explores how changes in network expansion coefficients and failure rates influence these factors. Notably, findings reveal that systems with slower development rates exhibit greater asset resilience; as demonstrated in scenario 3, the assets are strengthened from a 70-year life to a 6-year life for a 145 km storm.