Impact Of Storms Research Articles

Empirical modelling of dust storm path attenuation for 5G mmWave

The rapid evolution of communication technologies, particularly the emergence of 5G mm-wave networks, presents unprecedented challenges, particularly in regions prone to dust and sandstorms. These environmental factors can significantly impact 5G signals by attenuating radio waves, leading to signal degradation. This paper investigates the complex interplay between dust storms and 5G mm-wave wireless communication, offering a novel and comprehensive analysis that extends beyond existing models. Our study investigates into the impact of dust storms on 5G mm-wave wireless communication, specifically focusing on signal attenuations under both non-line of sight (NLOS) and line of sight (LOS) conditions. Through the utilize of the NYUSIM channel simulator and exploration of parameters such as dust particle size, storm duration, and environmental factors, we present a detailed numerical results. In the NLOS scenario, path loss measurements record substantial values, highlighting the significant impact of dust storms across different mm-wave frequencies. Conversely, in the LOS scenario, our findings reveal distinct patterns of path loss and shadow fading, shedding light on the complex interaction between dust storms and signal propagation. This research marks a significant advancement in the field, providing a quantitative foundation for addressing dust-induced attenuation in 5G mm-wave communication. By emphasizing novel research methodologies and innovative ideas, our study contributes to a deeper understanding of the challenges posed by dust storms in 5G mm-wave wireless communication systems, paving the way for more effective mitigation strategies and network optimization techniques.

Machine learning approaches for anomalous storm pattern identification

ABSTRACT Anomaly detection is used to explore the link between data-driven anomalous storms and their socio-economic impact on countries within the North-West Pacific. Three anomaly detection models are trialled using three distinct algorithms on the storm tracks and temperature profiles of storms. A feature-based comparison of the top 5% of anomalous storms from each model is used to reveal variations in anomalous storm activity. Further to this, the socio-economic impact of the anomalous storms is assessed, revealing a link between the anomalous behaviour of storms and the impact experienced by countries on their path. A final cross-comparison shows that the k-Nearest Neighbour and Isolation Forest algorithms succeeded at identifying high-impacting storms. However, the agglomerative clustering model found many unique storms that had low impact. This highlights the importance of considering both trajectory and temperature in determining the severity and impact of erroneous storms.

Analyzing the Impact of Storm ‘Daniel’ and Subsequent Flooding on Thessaly’s Soil Chemistry through Causal Inference

Storm ‘Daniel’ caused the most severe flood phenomenon that Greece has ever experienced, with thousands of hectares of farmland submerged for days. This led to sediment deposition in the inundated areas, which significantly altered the chemical properties of the soil, as revealed by extensive soil sampling and laboratory analysis. The causal relationships between the soil chemical properties and sediment deposition were extracted using the DirectLiNGAM algorithm. The results of the causality analysis showed that the sediment deposition affected the CaCO3 concentration in the soil. Also, causal relationships were identified between CaCO3 and the available phosphorus (P-Olsen), as well as those between the sediment deposit depth and available manganese. The quantified relationships between the soil variables were then used to generate data using a Multiple Linear Perceptron (MLP) regressor for various levels of deposit depth (0, 5, 10, 15, 20, 25, and 30 cm). Then, linear regression equations were fitted across the different levels of deposit depth to determine the effect of the deposit depth on CaCO3, P, and Mn. The results revealed quadratic equations for CaCO3, P, and Mn as follows: 0.001XCaCO32 + 0.08XCaCO3 + 6.42, 0.004XP2 − 0.26XP + 12.29, and 0.003XMn2 − 0.08XMn + 22.47, respectively. The statistical analysis indicated that corn growing in soils with a sediment over 10 cm requires a 31.8% increase in the P rate to prevent yield decline. Additional notifications regarding cropping strategies in the near future are also discussed.

ВЛИЯНИЕ ГЕОМАГНИТНОГО ПОЛЯ НА ПОВЕДЕНИЕ НАСЕКОМЫХ

The review presents contemporary data on the influence of the geomagnetic field and its variations on insect behavior. The most probable mechanisms of magnetoreception in different species are discussed. The prospects for studying insect electroreceptors as magnetodetectors are considered. Special attention is paid to studies investigating the impact of geomagnetic storms on insects. Differences in primary magnetoreception mechanisms
 are considered a potential cause for divergences in the reactions of different insect species to geomagnetic
 disturbances.

Impact of the meteorological storm in the Moscow region in May 2017 on variations in upper atmosphere parameters

A numerical simulation of atmospheric wave propagation ahead of a strong pressure spike during a squall in Moscow on May 29, 2017, was performed using a three-dimensional version of the high-resolution nonlinear numerical model AtmoSym. The meteorological source was specified based on experimental observations of a network of 4 microbarographs located in the Moscow region. Wave perturbations in the upper atmosphere caused by the generation of internal gravity waves by the meteorological source were estimated.

Assessing the impact of cyclonic storm Tauktae on shoreline change in Mangaluru coast using geospatial technology

Cyclones are natural events that occur with atmospheric pressure variations. Compared to the eastern coast of India, the western coast has less cyclonic activity. Even though some of the cyclonic events turn into severe cyclonic storms and cause a huge impact on ecological and anthropogenic activities. This research focuses on the impact of cyclone Tauktae on the Mangalore coast. Cyclone Tauktae, one of the most powerful to pass through coastal Karnataka, caused significant damages, affecting 121 villages and resulting in four casualties. Utilizing geospatial techniques, this study employs Sentinel-2 satellite images to analyze shoreline changes during pre and post-cyclone Tauktae. A GIS technique involves the extraction of shorelines using 10-meter resolution images, with manual digitization excluding natural and man-made structures. Transect lines are generated with the help of DSAS to measure shoreline movement, distinguishing accretion and erosion. Rainfall conditions during the cyclone period are mapped using gridded rainfall data. The study area, encompassing ten coastal villages from Someshwara to Sasihithlu, is characterized by its vulnerability to cyclones. Results reveal substantial shoreline changes, with notable erosion in central and northern Mangaluru, Tannirbavi, and Hosabettu. Accretion is observed in south Someshwara and north Sashihitlu. Rainfall patterns are analyzed using Persian CCS gridded data, depicting the dynamic nature of precipitation during the cyclonic event. This research contributes valuable insights into the short-term effects of cyclonic storms on shorelines, emphasizing the importance of geospatial techniques for coastal management. The findings serve as a foundation for mitigating cyclonic impacts and enhancing resilience in the Mangalore coast, aiding future coastal management strategies

Impact of Hurricanes, Tropical Storms, and Coastal Extratropical Storms on Indoor Air VOC Concentrations

AbstractUnderstanding vapor intrusion (VI) temporal variability is key for the design of sampling strategies intended to assess reasonable maximum exposure of indoor air concentrations of volatile organic compounds (VOCs) as well as risk evaluation and mitigation planning. VI temporal variability has previously been shown to be dependent on the complex interactions of multiple independent variables—meteorological, hydrogeological, and human behavioral. Several meteorological variables, including barometric pressure, wind speed, and rainfall, are linked during tropical and extratropical storm events. High‐frequency meteorological and indoor VOC data from a series of seven tropical storms and four extratropical storms were collected at a single industrial building with multiple heating, ventilation, and air conditioning (HVAC) zones. The storms and sampling zones showed a variety of effects on trichloroethylene (TCE) concentrations in indoor air. In one zone (supply room), increases in TCE concentrations often, but not always, closely coincided with decreasing barometric pressure, sustained wind speeds over 32 km/h (20 mph), and differential pressures indicating subslab to indoor flow. A second zone, in a restroom, did not show a consistent pattern of temporal correlation between meteorological factors and indoor air concentrations. While peak indoor air concentrations may be associated with the passage of cyclonic storms at some sampling locations, this does not appear to be generalizable to all sampling locations. The observed increase in indoor air concentration potentially attributable to these storms is typically less than an order of magnitude and the duration ranges from a day to a week.

Storm Impacts on Mineral Mass Accumulation Rates of Coastal Marshes

AbstractCoastal marsh survival may be compromised by sea‐level rise, limited sediment supply, and subsidence. Storms represent a fundamental forcing for sediment accumulation in starving marshes because they resuspend bottom material in channels and tidal flats and transport it to the marsh surface. However, it is unrealistic to simulate at high resolution all storms that occurred in the past decades to obtain reliable sediment accumulation rates. Similarly, it is difficult to cover all possible combinations of water levels and wind conditions in fictional scenarios. Thus, we developed a new method that derives long‐term deposition rates from short‐term deposition generated by a finite number of storms. Twelve storms with different intensity and frequency were selected in Terrebonne Bay, Louisiana, USA and simulated with the 2D Delft3D‐FLOW model coupled with the Simulating Waves Nearshore (SWAN) module. Storm impact was analyzed in terms of geomorphic work, namely the product of deposition and frequency. To derive the long‐term inorganic mass accumulation rates, the new method generates every possible combination of the 12 chosen storms and uses a linear model to fit modeled inorganic deposition with measured inorganic mass accumulation rates. The linear model with the best fit (highest R2) was used to derive a map of inorganic mass accumulation rates. Results show that a storm with 1.7 ± 1.6 years return period provides the largest geomorphic work, suggesting that the most impactful storms are those that balance intensity with frequency. Model results show higher accumulation rates in marshes facing open areas where waves can develop and resuspend sediments. This method has the advantage of considering only a few real scenarios and can be applied in any marsh‐bay system.

Atmospheric environment characteristic of severe dust storms and its impact on sulfate formation in downstream city

This study comprehensively investigated the impact of dust storms (DSs) on downstream cities, by selecting representative DS events. In this paper, we discussed the characteristics of meteorological conditions, air pollutants, PM2.5 components, and their influence on sulfate formation mechanisms. During DSs, strong winds, reaching speeds of up to 10 m/s, led to significant increases in PM10 and PM2.5, with maximum concentrations of 2684.5 and 429 μg/m3, respectively. Primary gaseous pollutants experienced substantial reductions, with decline rates of 48.1, 34.9, 36.8, and 9.0 % for SO2, NO2, NH3, and CO, respectively. Despite a notable increase in PM2.5 concentrations, only 7.6 % of the total mass of PM2.5 was attributed to ionic and carbonaceous components, a much lower value than observed before the DSs (77.3 %). Concentrations of Fe, Ti, and Mn exhibited increases by factors of 6.5–14.1, 10.4–17.0, and 1.6–4.7, respectively. In contrast to the significant decrease of >76.2 % in nitrogen oxidation ratio (NOR), sulfur oxidation ratio (SOR) remained at a relatively high level, displaying a strong positive correlation with high concentrations of Fe, Mn, and Ti. Quantitative analysis revealed an average increase of 0.187 and 0.045 μg/m3 in sulfate from natural sources and heterogeneous generation, respectively. The heterogeneous reaction on mineral dust was closely linked to atmospheric humidity, radiation intensity, the form of metal existence, and concentrations of it. High concentrations of titanium dioxide and iron‑manganese oxides in mineral dust promoted heterogeneous oxidation of SO2 through photocatalysis during the daytime and metal ion catalysis during the nighttime. This study establishes that the metal components in mineral dust promote heterogeneous sulfate formation, quantifies the yield of sulfate generated as a result, and provides possible mechanisms for heterogeneous sulfate formation.

Impact of tropical storms on the banking sector in the British Colonial Caribbean

This paper investigates the impact of four historical tropical storms on the Colonial Bank’s operations in the British Caribbean between 1922 and 1927. By employing a high-frequency data set of bank transactions, this study reveals how these severe shocks influenced the banking activities of clients. The findings reveal a multifaceted and significant impact of tropical storm strikes on the banks’ operations, particularly a surge in borrowing via overdrafts of current accounts. Moreover, the study reveals the multifaceted nature of such storms’ impact on the bank’s functionality, with affected branches demonstrating an uptick in deposits and savings as a strategy to mitigate funding shocks. The results of the econometric analysis indicate that the impact of such storms on banks’ functionality during the early 20th century was significant and multidimensional. It highlights the critical role that the Colonial Bank plays in facilitating recovery from these devastating events and contributes to the existing literature by studying multiple shocks at different geographical locations and time frames.

Impact of a severe dust storm on aerosol properties and their radiative forcing over the Indian subcontinent during winter

The impact of a severe dust storm that originated over the Arabian Peninsula (AP) and travelled to the Indian subcontinent during 20–26 January 2022 is examined. According to the event's synoptic analysis, the Gulf of Oman, adjacent areas of Oman and Iran had strong mid-lower tropospheric westerlies because of the configuration of north-south cyclonic and anticyclonic circulation patterns generated by a sizable north-south pressure gradient. A strong westerly wind component continued down to surface level and brought large quantities of dust from the desert region of the Middle East to the Indian subcontinent. Overall, 90% of the monitoring locations over the Indian subcontinent (mostly the western region) exceeded the national tolerable level of 100 μg m−3 (PM10), with peaks as high as 650 μg m−3. Changes in optical and physical properties of aerosols varied in accordance with the dust loading, in which absorption aerosol optical depth denotes a 10% increase in absorbing aerosols. Due to the excessive cooling effect, the near-surface air temperature dropped by −6 °C from its daily climatology over a sizable zone of high aerosol loading. Additionally, the dust storm prolonged the winter's harshness by lowering temperatures (from pre-dust days) in some of the most severely afflicted areas to 10–12 °C. Changes in wind patterns at mid- and low levels have resulted in a temperature inversion (∼ 2.5 km), which prevented trapped dust particles from being diluted, which in turn increased the likelihood of a more significant decline in air quality and affecting human health/wealth.

Climate Resilience through AI-Driven Hurricane Damage Assessments

Evolving hurricane patterns intensified by climate change are expected to exacerbate economic hardships on coastal communities. Climate resilience for these communities requires both the capability to recover rapidly from devastating storms, and the ability to develop an accurate and actionable understanding of vulnerabilities to reduce the impact of future storms. Available data from past storms can provide invaluable insight in addressing both these requirements. Post-disaster preliminary damage assessments (PDAs) are a crucial initial step toward a rapid recovery. They also provide the most accurate information on the performance of various types of dwellings after the storm. Traditional door-to-door inspection methods are time-consuming and can hinder efficient resource allocation by governments in the aftermath. To address this, researchers have proposed automated PDA frameworks, often utilizing data from satellites, combined with deep convolutional neural networks. However, before such frameworks can be adopted in practice, the accuracy and fidelity of predictions of damage level at the scale of an entire building must be comparable to human assessments. To bridge this gap, we present an innovative PDA framework that leverages Ultra-High-Resolution Aerial (UHRA) images alongside state-of-the-art transformer models for multi-class damage predictions across entire buildings. Our approach leverages vast amounts of unlabeled data to enhance accuracy of prediction and generalization capabilities. Through a series of experiments, we evaluate the influence of incorporating unlabeled data, and transformer models. By integrating UHRA images and semi-supervised transformer models, our findings indicate that this framework overcomes critical limitations associated with satellite imagery and traditional CNN models, achieving an 88% multiclass accuracy, ultimately leading to more precise, efficient, and reliable damage assessments that are a first step towards building more climate resilient societies.

Controls on the morphological evolution of embayed beaches: Morphometry versus external forcing

AbstractThe morphological evolution of embayed beaches on a microtidal coast is assumed to largely respond to the degree of exposure to wave conditions, decreasing the mobility with increasing beach indentation (and vice versa). However, the number of sediment arrivals at the beach or the impact of extreme storms can modify this relationship. Here, we present an analysis of 10 embayed beaches along the Catalan coast with different morphometric and sedimentary characteristics to identify the most relevant parameters controlling the morphological evolution of these embayed beaches at the inter‐annual and decadal scales. The study was mostly based on LiDAR topographic data collected from 2012 to 2017, aerial photographs from 1945 to 2021, sediment sampling and a long‐term series analysis of the forcing parameters (waves, sea level, precipitation and land‐use changes). The results show a net loss of volume on all the studied beaches at an inter‐annual scale and a general shoreline retreat during the last few decades, suggesting the influence of common processes on the evolution of the studied beaches. Smaller pocket beaches with medium‐to‐high indentations are more sensitive to changes induced by local factors and show higher variability in the volume of the emerged beach and shoreline position than larger beaches. The most relevant factors influencing the evolution of the studied beaches on a decadal scale were identified as changes in sea level and the reduction in sediment inputs provided by streams due to land‐use changes in the drainage basin. At the inter‐annual scale, the impact of extreme events is the main factor controlling beach behaviour. These general trends can be opposite locally for beaches that receive large amounts of sediment via longshore transport from adjacent beaches.

The impact of extreme dust storms on the national photovoltaic energy supply

This study analyses the consequences of an extreme dust storm that occurred in March 2022 on the Spanish national photovoltaic (PV) energy supply. This event, indeed, substantially raised the particulate matter concentrations and the aerosol optical depths across the country, seriously affecting the surface radiation and posing a substantial threat not only to individual PV systems but also to the national electricity grid. The research, based on the analysis and the forecast of weather, environmental and electrical data, reveals that such event halved the capacity factor of the national PV fleet over a period longer than two weeks. A peak drop as high as 80% was registered, at national level, on the worst day. This underperformance also affected the market share of PV in the national electricity mix, whosemonthly average value fell from the predicted 10.9% to 7.1%. Despite the expectations, however, no significant difference in soiling was found compared to the typical losses, thanks to the occurrence of heavier-than-usual rainfall events. This facilitated the recovery of the national PV capacity, which returned to the expected performance factors as soon as the sky cleared.

Robust Wind Power Ramp Control Strategy Considering Wind Power Uncertainty

Recent climate change has worsened the risk of extreme weather events, among which extreme offshore wind storms threaten secure operation by inducing offshore wind power ramps. Offshore wind power ramps cause the instantaneous power fluctuation of interconnected onshore grids and may lead to unexpected load shedding or generator tripping. In this paper, considering offshore wind power uncertainties, we propose a novel robust coordinated offshore wind power ramp control strategy by dispatching thermal units, energy storage systems, and hydrogen storage systems cooperatively. First, the impact of extreme wind storms on an offshore wind farm output power ramp is analyzed, and the general framework of offshore wind power ramp control is presented based on the two-stage robust optimization considering the dual uncertainties of load demand and wind power. Second, a coordinated wind power ramp control model is established considering the operational characteristics of different ramp control sources such as thermal units, energy storage systems, and offshore wind farms. Third, a robust ramp control strategy is developed using the column-and-constraint generation (CC&G) algorithm. Simulation results show the effectiveness of the proposed ramp control strategy.

Impacts of dust storms on agriculture: A synthesis

Impacts of dust storms on agriculture: A synthesis

Integrating Structural Vulnerability Analysis and Data-Driven Machine Learning to Evaluate Storm Impacts on the Power Grid

Integrating Structural Vulnerability Analysis and Data-Driven Machine Learning to Evaluate Storm Impacts on the Power Grid

Responses at the stand and tree level to ice storm injuries in beech forests in eastern Serbia

The paper presents the study on the condition and structural stability of European beech (Fagus sylvatica L.) stands after the 2014 ice storm disturbance. The research was conducted in three pure beech stands on the Rtanj mountain in eastern Serbia. The stand condition after the ice storm was analyzed using changes in taxation elements. The assessment of tree damage was done according to the ICP Forests methodology, while the structural stability of the stands and individual trees was analyzed using the slenderness coefficient. The obtained results indicate very heterogeneous responses of beech stands to the negative impact of the ice storm. Heterogeneity is not only expressed between stands but also within individual stands. The stands after the ice storm are characterized by significantly reduced values of production indicators, but also by satisfactory stability, considering that the trees from the understory suffered the most. Statistically significant differences in the stability of trees of different dimensions expressed through the slenderness coefficient were determined. Consequently, the stands have maintained an appropriate level of stability thanks to the survival and resistance of the dominant trees that are the bearers of functions in these stands (trees with dbh > 40 cm). This indicates the great potential of silvicultural treatments that can increase the stability and resistance of stands in areas with a high risk of such phenomena. In addition, repressive action in the form of salvage logging has a very important role with the aim of ensuring the continuity of stands after damage has occurred.

The Impacts of Dust Storms With Different Transport Pathways on Aerosol Chemical Compositions and Optical Hygroscopicity of Fine Particles in the Yangtze River Delta

AbstractAerosol physicochemical properties during two dust storms (DS1: March 30–31, and DS2: May 7–8) are measured in 2021 in Nanjing, aiming to investigate the impacts of dust storms on aerosol chemical compositions and optical hygroscopicity in the Yangtze River Delta (YRD). During DS1, the dust air masses are transported in the lower atmosphere and pass through the inlands and sea areas before reaching the YRD region. During DS2, the dust air masses are transported in the upper atmosphere and pass through the inlands only. Both of them are accompanied by an increase in black carbon (BC) mass fraction and a decrease in nitrate mass fraction in fine particles (PM2.5, particles with diameters less than 2.5 μm) near the surface. However, the impacts on the mass fractions of organics or sulfate are adverse between DS1 and DS2. During dust‐influence periods the enlarged mass ratios of sulfate to nitrate (greater than 4) promote the occurrence of deliquescent behavior of ambient aerosols although dust aerosols can significantly suppress aerosol optical hygroscopicity. To improve model simulations of aerosol optical hygroscopicity, it is necessary to use a segment parameterization to describe aerosol light scattering enhancement factor during dust‐influence periods. The closure study of optical hygroscopicity parameters with two different methods reveals the impact of aerosol scattering Ångström exponent on the estimation of optical hygroscopicity parameter. The results highlight that the impact of dust storms on aerosol chemical compositions and optical hygroscopicity are different for DS events with different transport pathways.

Different effects between cold front and tropical cyclone on short-term morphodynamics in the Changjiang Delta

Global climate change is altering the frequency and intensity of extreme weather events such as typhoons and cold fronts, and this is inducing physical changes and adaptions in estuaries and coasts. We conducted a field campaign on the subaqueous Changjiang Delta front in September 2019 to improve understanding of storm impact on short-term hydro-morphodynamics. Over an 11-day period, during which both typhoon and cold front events occurred, in-situ data including flow velocities, suspended sediment concentrations (SSC), and bed-level changes were acquired using bottom tripod and buoyage systems, Significant wave height reached 5.0 m during the typhoon, and the depth-averaged current velocity increased to 1.7 m/s. The net near-bottom sediment flux was in the same direction as the wind and was 5.5 times of that under calm weather. During the cold-front, significant wave height reached 2.5 m, and the near-bottom SSC increased to 7.0 kg/m3. Bed-level changes were small (<2 cm) under pre-storm weather, while net deposition and erosion reached 15.8 cm and 16.8 cm, respectively, during the typhoon. Short-term changes in the sediment source-to-sink regime were detected in the subaqueous Changjiang Delta. The cold front enhances seaward sediment flushing from the delta towards the sea, while the typhoon drives sediment transport from the subaqueous delta towards Hangzhou Bay. We also observed rapid bed-level recovery following these extreme events. These findings improve our understanding of sediment transport under stormy conditions.