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Abstract WRF wind forecasts from four operative schemes used by OHMC (Observatorio HidroMeteorológico de Córdoba), a test scheme (WRF-E) and two daily runs with 4 km horizontal resolution were analyzed. Wind simulations were compared with measurements from eight ground stations with anemometers at 10 m high during the period from June, 2019 to June, 2020. WRF-E incorporates more vertical levels, and an activated topo_wind option. The wind speed results show that WRF overestimates wind speed at most stations and the WRF-E model reduces the BIAS and the RMSE when compared with the operational models. The wind direction analysis shows that the higher the wind speed is, the more accurate the models are. In addition, a wind gust forecasting has been implemented and evaluated in this work. Wind gust correlation coefficient values are between 0.3 and 0.6, RMSE is between 3 and 5 m/s, and a positive BIAS(

The Chamoli district of the Himalayan state Uttarakhand experienced a glacier breakage leading to a devastating flash flood on 07 Feb 2021. The event claimed several lives and also destroyed the hydropower projects in the Rishiganga and Dhauliganga valleys. The initiation of strong wind gusts on 6th and 7th Feb 2021 and specifically 12 hours before the disaster (42, 45, and 41 km/hr) demonstrates the wind’s ongoing impact on the accumulated snow/glacier. It seems a significant contribution that might have resulted in the heat energy responsible for the breaking of the glacier leading to this disaster. Moreover, the analysis of thermal variability of land surface temperature (LST) shows the sudden change in the terrain during the disaster. It shows relatively lower temperature before the event due to snowfall over the study area on 5 Feb 2021 in comparison to that after the event. Research Highlights: The present study analyzes the hidden meteorological factor contributing to the glacier breakage which resulted in devastating flash flood in Chamoli district, Uttarakhand, on 07 February 2021. The missing parameter namely wind is validated using the observed values with the model computed values through data analysis. The Land Surface Temperature is calculated as an additional information to compare the pre and post disaster characteristics of the land confirming the presence of weak layer before the disaster. The presence of continuous wind gust in the narrow valley acted as a potential factor towards the disaster. [ABSTRACT FROM AUTHOR]

In this research, a wide-body aircraft was analyzed with critical monitoring of its states, a function of several control inputs (wind gust, turbulence, and microburst). The aerodynamic and stability coefficients of a Boeing 747-200 were obtained from previously published works and 6- DOF equations were formulated. Simulations were conducted for various control inputs to determine the aircraft's free response, as well as the forced response. In order to understand the nature of the atmosphere, three different models were incorporated, including (i) the Dryden Model, (ii) wind gust, and (iii) microburst. The aircraft was found to be stable in the longitudinal and lateral flight modes, with trim conditions agreeing with published data. For a vertical wind gust of −10 ft/s, the AoA and pitch rate were observed to oscillate sinusoidally and became stable with new trim conditions. These states were found to regain trim conditions once the gust was removed. In the case of 3D gust, it was found that the longitudinal modes achieved a new trim condition through Phugoid oscillations, whereas the lateral modes underwent short-period oscillations. For the case of turbulence, random fluctuations were observed for trim conditions with no unstable behavior. When considering the microburst case, it was found that the aircraft initially gained altitude in the region of the headwind; this was followed by a sharp descent under the influence of a vertical velocity component. [ABSTRACT FROM AUTHOR]

This paper presents a robust altitude control that merges the principles of active disturbance rejection control (ADRC) with the in-ground-effect model (IGE). To this end, a nonlinear extended state observer is designed along the vertical axis, taking attitude and altitude measurements. Then, the forces generated by low-level flight, ground effect and other external disturbances are estimated and used (as an anticipation term) together with a non-linear control law (as a feedback term) to reject them. Closed-loop stability is analyzed in the Lyapunov sense. Extensive numerical simulations and real-time experiments validate the proposal. Thanks to its simplicity, the control algorithm is easy to implement. It can be used for various maneuvers that depend on proximity to the ground, obstacles or surfaces, such as take-off, landing, inspection, surveillance and hovering. [ABSTRACT FROM AUTHOR]

Understanding the physical characteristics of severe pre-monsoon thunderstorms is crucial for mitigating the adverse impacts of natural disasters on people in tropical regions. On April 23, 2020, a severe storm affected the Chiang Khong District of the Chiang Rai Province in Northern Thailand, causing devastation to more than 500 houses with hail and strong winds. This study investigated the storm's physical characteristics using dual-polarimetric radar data from the Thai Meteo-rological Department (TMD). Using a combination of polarimetric radar variables, such as reflectivity (ZH), specific differential phase (KDP), differential reflectivity (ZDR), and copolar correlation coefficient (ρhv), fuzzy logic was utilized to classify the hydrometeor types. During the severe storm that affected the Chiang Khong District, hail and large raindrops were mixed in with the rain, according to the analysis. Two severe storms were observed in the unorganized mesoscale convective systems that were analyzed, with the second storm producing more intense effects due to the radar reflectivity shape of a bow echo that generated strong wind gusts. The Doppler radar data retrieved the wind field, indicating the convergence of intense local winds during the storm, which was consistent with the analysis results of synoptic-scale weather systems from ECMWF Reanalysis v5 (ERA5). In addition, a Hovmöller diagram revealed orographic enhancement of the convective cloud as the storm passed through mountainous regions prior to approaching the Chiang Khong District. The findings of this study can provide valuable information for TMD's near-real-time warning operation in order to minimize loss of life and property from future severe storms.

The lightweight nature of micro air vehicles (MAVs) makes them highly sensitive to perturbations, thus emphasizing the need for effective control strategies that can sustain attitude stability throughout translational movement. This study evaluates the performance of two controllers (Proportional-Integral-Derivative (PID) and Adaptive PID based on Sliding Mode Control (SMC)) on a MAV that is subjected to external disturbances. These controllers are initially simulated using MATLAB®/Simulink™ and then implemented in real-time on the Parrot Mambo Minidrone. The observation on the waypoint follower and the orbit follower in both simulation and experiment showed that the Adaptive PID (APID) controller is more effective and robust than the PID controller against external disturbances such as wind gusts. The study provides evidence of the potential of the APID control scheme in enhancing the resilience and stability of MAVs, making them suitable for various applications including surveillance, search and rescue, and environmental monitoring. [ABSTRACT FROM AUTHOR]

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This study analyses for the first time observed surface mean wind speed (SWS) and gusts over the Iberian Peninsula (IP) in the frequency domain for 1961–2019, with the goal of exploring sources of predictability in the interannual and decadal scales. The main result is the high significant correlation between surface winds and the stratospheric polar vortex for periods close to 1 year with a time lag of about 2–3 months with respect to the antiphase, that is, a negative correlation in which the polar vortex modulates winds in the region. Furthermore, we found that the SWS and gusts are decoupled for periods between 9 and 11 years with a marked seasonal dependence in its intensity. Finally, we detected discrepancies between the spectra shown by surface winds from observations and ERA5‐Land reanalysis, suggesting that simulated data do not accurately reproduce the variability of surface wind speeds. Plain Language Summary: In the climate system, there are oscillations that are repeated with specific time periods over time; the best known example is the El Niño‐Southern Oscillation, which affects much of the world's climate. In this study, we apply a spectral analysis to: (a) characterize the spectrum of near‐surface mean wind speed and gusts in the Iberian Peninsula; (b) relate the oscillations of both wind variables with those of other parameters of the climate system; and, (c) identify sources of predictability. The most outstanding result is the high significant correlation between the mean wind speed and gusts with the stratospheric polar vortex with a time lag of about 2–3 months. This means that with an anomalously weak (strong) polar vortex we might expect strong (weak) surface winds 2–3 months later. This study has direct socioeconomic and environmental implications for for example, wind energy production, agriculture and hydrology, pollutant dispersion, among others, as it could predict interannual‐ to decadal‐scales wind speed behavior in the region. Key Points: Surface winds correlate with the stratospheric polar vortex in periods close to 1 year, with a 2–3 months lag with respect to the anti‐phaseSurface mean wind speed and gusts are decoupled for periods between 9 and 11 years, being greater in summer and disappearing in winterSpectral analysis showed differences between observed and ERA5‐Land reanalysis surface winds [ABSTRACT FROM AUTHOR]

Today we are witnessing a multitude of destructive natural meteorological and hydrological phenomena that cause more financial and environmental losses to human life. One of the atmospheric phenomena that can have a direct impact on flight safety, transportation, structures, energy and many other aspects of human life is wind gust. The aim of this study was to investigate the temporal and spatial distribution of wind gust in Iran over a period of 15 years and to evaluate an experimental method called WPD to predict this phenomenon using the output of the WRF model. For this purpose, the data recorded in 32 synoptic stations between 2004 and 2018 were studied. The results showed that the number of wind gusts occurred in the southeast and northwest Iran was much higher than other regions, while the frequency of convective wind gusts has been higher in the western half of Iran. In general, the frequency of wind gust had an increasing trend during the studied period and reached its maximum in 2018. Moreover, most convective wind gust reports have been related to spring. The highest number of wind gust reports with 67% belonged to the first half of the year. However, only 13% of the reports belonged to the autumn. Most of the wind gusts were reported between 12:00 and 18:00 local standard time (0800 to 1400 UTC). Among several wind gust forecasting methods, the relationship used in the WRF post processing system (WPD) was selected and its performance in Iran was evaluated. The results of the method on 885 non-convective wind gust indicated the optimal performance of the method for forecasting wind gust in Iran (RMSE=3.23, MAE=2.83, MSE=13.4 and R=0.71). [ABSTRACT FROM AUTHOR]

Probability distributions of wind data in a short time scale, such as hourly, are critically important for the risk assessment in relation to wind energy, optimal route scheduling for commercial airlines and unmanned aerial vehicles. It is known that the probability distributions of wind direction, wind speed, and wind gust have a large variety—ranging from Weibull to Lognormal distributions. A systematic method is needed to determine which distribution best fits a given wind dataset in a very efficient manner. This paper attempts to provide such a method. It is the best group fitting (BGF) method that efficiently fits the hourly wind data to a large number of distributions simultaneously, in contrast to the traditional one-by-one data fitting. The BGF method utilizes a Python package named Fitter which uses Scipy package, tries 80 distributions simultaneously, and checks what is the most probable distribution. We then apply the BGF method for the hourly data of u-wind, v-wind, wind speed, and wind gust in four geologically different locations, including the Alta Wind Energy Center, the Rocky Mountain region, the Colorado Plateau, and the San Diego urban district. The performance of the commonly used distributions and a wider selection of distributions are ranked for these locations at different times of a day. Our datasets and results show that, in addition to the traditional distributions such as Weilbull distribution and Lognormal distribution, the Burr distribution class stands out among the wind distributions and even outperforms the most used distributions in the literature. Our fitting results to the operational wind data have demonstrated that it is feasible to use BGF to make an efficient group fitting, which may imply that BGF can be used to search for the best probability distribution from different hourly weather datasets. [ABSTRACT FROM AUTHOR]

Abstract This study analyses for the first time observed surface mean wind speed (SWS) and gusts over the Iberian Peninsula (IP) in the frequency domain for 1961–2019, with the goal of exploring sources of predictability in the interannual and decadal scales. The main result is the high significant correlation between surface winds and the stratospheric polar vortex for periods close to 1 year with a time lag of about 2–3 months with respect to the antiphase, that is, a negative correlation in which the polar vortex modulates winds in the region. Furthermore, we found that the SWS and gusts are decoupled for periods between 9 and 11 years with a marked seasonal dependence in its intensity. Finally, we detected discrepancies between the spectra shown by surface winds from observations and ERA5‐Land reanalysis, suggesting that simulated data do not accurately reproduce the variability of surface wind speeds.

In this research, a wide-body aircraft was analyzed with critical monitoring of its states, a function of several control inputs (wind gust, turbulence, and microburst). The aerodynamic and stability coefficients of a Boeing 747-200 were obtained from previously published works and 6- DOF equations were formulated. Simulations were conducted for various control inputs to determine the aircraft’s free response, as well as the forced response. In order to understand the nature of the atmosphere, three different models were incorporated, including (i) the Dryden Model, (ii) wind gust, and (iii) microburst. The aircraft was found to be stable in the longitudinal and lateral flight modes, with trim conditions agreeing with published data. For a vertical wind gust of −10 ft/s, the AoA and pitch rate were observed to oscillate sinusoidally and became stable with new trim conditions. These states were found to regain trim conditions once the gust was removed. In the case of 3D gust, it was found that the longitudinal modes achieved a new trim condition through Phugoid oscillations, whereas the lateral modes underwent short-period oscillations. For the case of turbulence, random fluctuations were observed for trim conditions with no unstable behavior. When considering the microburst case, it was found that the aircraft initially gained altitude in the region of the headwind; this was followed by a sharp descent under the influence of a vertical velocity component.

Storm Vaia on 29 October 2018, hit northeastern Italy and produced extensive damage in the immediacy of the event, including extensive tree felling in some places, as well as debris flow or earth flow landslides. This study aims to assess the susceptibility of the area following extreme events by evaluating the environmental criticality during strong winds and intense precipitation. Specifically, tree felling susceptibility due to wind and landslide susceptibility due mainly to precipitation were analysed by taking into consideration the geomorphological and environmental criticality of the areas under study. In particular, the area was modelled using fluid dynamics software, allowing an understanding of wind accelerations in relation to morphology, showing excellent agreement between the tree falls that occurred during the event and the areas with the highest wind gusts. With regard to landslides, an algorithm was prepared through GIS software that took into account the debris and earth flows that were activated during the extreme event in question, allowing the creation of a susceptibility map that delineated areas of high potential hazard. The final result is a landslide and tree-fall susceptibility map that determines the fragility of the territory during an extreme event. The procedures applied in the study area can be considered as a working method that allows critical values to be obtained for extreme events that can produce damage to the environment and beyond. It follows that this research also has an immediate application purpose by helping the political decision-maker in the choice of interventions to be implemented. [ABSTRACT FROM AUTHOR]

This paper addresses the time-varying rendezvous problem of a swarm of drones with the leader-follower consensus hierarchy. Each drone in the swarm is under the influence of external disturbances in the form of wind gusts. To control the swarm of perturbed drones, this paper proposes a fully distributed adaptive leader-following time-varying disturbance rejection pinning control for the rendezvous of drones using the framework of the extended state observer that depends on the state estimates of the neighboring agents rather than the actual states. The communication topology within the swarm is modelled using algebraic graph theory. Unlike most of the literature in which the leader agent act as a virtual reference generator, an active leader agent with non-zero control input is considered. The states of the leader drone are only available to a subset of the graph. The communication topology between leader-follower is directed while that between follower-follower is undirected. Based on the relative output information between the neighboring drones, the extended state observer estimates the local states and disturbances of each drone and the adaptive control actively compensates for the external disturbances simultaneously. Finally, it is shown analytically as well as in simulations that the time-varying rendezvous can be achieved by the proposed algorithm effectively.

It is difficult to analyse the action force of the wind in a way that considers the change in the height of its action, the change in direction, or the momentum required for the time of its action. Depending on the design codes of structures and buildings, wind action can be static or dynamic. In this article, we study the dynamic action of the wind on engineering structures (the object of study in this paper is truss structures), analysing in detail the phenomenon of pulsating cyclic loads and the fatigue of the elements of the structures because of its impact. First, we determine the cycle of the wind action, after which we extract its characteristics, such as the average load, the asymmetry of the cycle, the amplitude, and the frequency of the action using the data obtained for the wind from the meteorological services. Then, we evaluate the structure’s life by assessing the damage caused by this loading and cumulative accumulation. Also, in this material, we treat a specific case of a crane structure, where all the characteristics of wind action in the case of cyclic loads have been determined and the construction factor has been extracted as a characteristic that can be used in fast calculation by different engineers.

Abstract Short‐term forecasting of wind gusts, particularly those of higher intensity, is of great societal importance but is challenging due to the presence of multiple gust generation mechanisms. Wind gust observations from eight high‐passenger‐volume airports across the continental United States (CONUS) are summarized and used to develop predictive models of wind gust occurrence and magnitude. These short‐term (same hour) forecast models are built using multiple logistic and linear regression, as well as artificial neural networks (ANNs) of varying complexity. A suite of 19 upper‐air predictors drawn from the ERA5 reanalysis and an autoregressive (AR) term are used. Stepwise procedures instruct predictor selection, and resampling is used to quantify model stability. All models are developed separately for the warm (April–September) and cold (October–March) seasons. Results show that ANNs of 3–5 hidden layers (HLs) generally exhibit higher hit rates than logistic regression models and also improve skill with respect to wind gust magnitudes. However, deeper networks with more HLs increase false alarm rates in occurrence models and mean absolute error in magnitude models due to model overfitting. For model skill, inclusion of the AR term is critical while the majority of the remaining skill derives from wind speeds and lapse rates. A predictive ceiling is also clearly demonstrated, particularly for the strong and damaging gust magnitudes, which appears to be partially due to ERA5 predictor characteristics and the presence of mixed wind climates.

In this study, mathematical modeling of biplane quadrotor with slung load is proposed. Performance of the biplane quadrotor is degrade while swinging of the slung load so to compensate it nonlinear observer based backstepping controller is designed that can not only handle the disturbance generated by the slung load but can also capable to tackle partial rotor failure and wind gust. Simulation study carried out by considering slung load swinging (only for quadrotor mode), wind gust, and rotor failure (for all three modes) as the external disturbance and nonlinear observer is design to estimate it. Backstepping control technique is used to design controller for all three modes of biplane quadrotor. Simulation study shows that proposed control scheme is cable to handle the disturbance generated by the different sources in quadrotor biplane.

The flow past a square cylinder under the influence of a one dimensional gust was investigated using computational fluid dynamics (CFD). The effect of upstream wind gusts of the same amplitude but different duration was investigated with respect to their effect on the flow, the vortex-shedding, and the pressure distribution around the square cylinder. For the computations, a very large eddy simulation (VLES) model was implemented in an in-house code and validated against numerical and experimental results from the literature. The gusts of different duration were found to have a distinctly different effect. The short-duration gust causes a lock-on behavior with cessation of the alternating vortex shedding, and a symmetric pair-vortex was created above and below the square cylinder. It was observed that the pressure distribution on the lateral sides of the cylinder has the same magnitude and phase, which resulted in a zero total lift coefficient. In terms of a free-standing structures, such as a building, this would lead to zero instantaneous forces and pressure difference in the lateral direction with obvious implications for dynamic response and cross ventilation. [ABSTRACT FROM AUTHOR]

Wind gusts over the ocean can have a great influence on maritime transport and production operations. However, owing to the scarcity of marine observation data and the complex causes of wind gusts, the estimation and forecasting of gusts at sea are even more difficult. In this study, a gust estimation equation applicable to the Bohai Sea is established based on observation and reanalysis data, with representative observation stations on the coast and offshore in the Bohai Sea. During the process, partial correlation analysis and a significance test of correlation coefficient differences were used to further clarify the influence of average wind speed and vertical wind shear at different heights on wind gusts. The final gust estimation equation includes a mean wind speed term, a turbulence term, and a convection term, which are statistically significant contributors; in addition, there are clear physical meanings. Comparing two gust factor methods in this study, the average errors and fitting errors of the least squares gust estimation equation are the smallest. For wind gusts between 10 and 26 m/s, the fitting error in the gust estimation equation is 7.68–12.25% and 21.10–30.08% lower than those of the two gust factor methods in this study. The gust estimation equation better reflects the difference of wind gusts typical under different average wind speeds and vertical wind shear conditions, so a better prediction for wind gusts can be achieved.

Atmospheric currents, known as winds, are among the most important fields of study in different disciplines of science. One of the most important characteristics of wind is gustiness. Wind gust, among many other characteristics of the wind field, is studied extensively due to severe impacts that it may have on many aspects of human socio-economic activities. There are several models to predict wind gust speed. The results of these models always contain random and systematic errors that reduce the accuracy of predictions due to the lack of topographic resolution as well as the deficiencies of different physical schemes in the models. Consequently, post-processing is the most important process in the course of simulation and prediction using different types of models. Artificial neural network is one of the available tools that may be used to reduce errors of models by matching their outputs and observations. The aim of this study was to evaluate the performance of two models and artificial neural network in forecasting wind gust in Iran. First, a study was designed to examine two methods of the nonconvective wind gusts forecasting, i.e., the UK Meteorological Office (MOA) and WRF post-process diagnostic of wind gusts (WPD) performances. To investigate the performace of two methods, 1880 cases of non-convective wind gust observations of 32 synoptic stations in Iran, between 2013 and 2018, were studied. Four RMSE, MAE, MSE and R were used to measure the performace of those two methods. The results for WPD and MOA were 3.89, 3.07, 15.2, 0.66 and 4.37, 3.43, 19.1, 0.55, respectively. The results showed that the WPD method performed better than the MOA method. To post-process the wind gust forecasts with an artificial neural network, a feedforward multilayer perceptron with the back-propagation learning algorithm was designed. The model had a hybrid structure with a sigmoid activation function for the hidden layer and a linear transfer function in the output layer. Three training algorithms were used in the implementation of the model. Various combinations of normalized output variables of the WRF were used as input for network training and the target was observational wind gust speed. Seventy percent of the data were used for training, fifteen percent for testing and fifteen percent for validation. The results showed that the best way to combine the input parameters is to use 10m wind, sea level pressure, temperature and relative humidity resulting from the output of the WRF model and the wind gust speed resulting from both methods mentioned above. Also, the best algorithm for neural network training was the Levenberg-Marquardt algorithm. Finally, the implemented artificial neural network was able to improve the results of both wind gust speed prediction methods (WPD and MOA). Due to the relatively higher accuracy of the WPD method compared with MOA method in predicting the wind gust speed in Iran, the artificial neural network that assumed the prediction of this method as input, was more accurate than MOA method (RMSE, MAE, MSE and R were 2.05, 1.6, 4.21, 0.83 and 2.37, 1.86, 5.2, 0.77, respectively). [ABSTRACT FROM AUTHOR]

Urbanization has promoted economic growth but it can increase gust wind speed, which may lead to serious damage to infrastructures. This study uses the Weather Research and Forecasting model and a gust parametrization scheme to evaluate the mitigation impact of white roofs and green roofs on wind gust over the Pearl River Delta, an urban agglomeration in Southern China in June, July, and August of 2014. The results show that both white and green roofs decrease the gust wind speed by decreasing the mean wind speed, suppressing the turbulent motion and weakening the convection. The impacts of white roofs are stronger than those of green roofs. The daily mean reductions of gust wind speed are approximately 1.2–1.3 m s ^−1 (12%–16%) and 0.4–0.6 m s ^−1 (6%–10%) by white and green roofs, respectively. In general, the contribution of turbulence (60%–85%) to the gust wind speed is the largest, and the contribution of mean wind speed is approximately 10%–30%, however, the effect of deep convection is not obvious (0%–15%) on the decrease of gust wind speed. The effect of cooling roofs on reducing the gust wind speed is stronger during daytime than during nighttime, and the effect is more significant in city areas that have higher building densities. Based on the findings, this study is potentially beneficial for policy-makings in developing urban disaster mitigation methods.

WRF wind forecasts from four operative schemes used by OHMC (Observatorio HidroMeteorológico de Córdoba), a test scheme (WRF-E) and two daily runs with 4 km horizontal resolution were analyzed. Wind simulations were compared with measurements from eight ground stations with anemometers at 10 m high during the period from June, 2019 to June, 2020. WRF-E incorporates more vertical levels, and an activated topo_wind option. The wind speed results show that WRF overestimates wind speed at most stations and the WRF-E model reduces the BIAS and the RMSE when compared with the operational models. The wind direction analysis shows that the higher the wind speed is, the more accurate the models are. In addition, a wind gust forecasting has been implemented and evaluated in this work. Wind gust correlation coefficient values are between 0.3 and 0.6, RMSE is between 3 and 5 m/s, and a positive BIAS (<2 m/s) at most stations. [ABSTRACT FROM AUTHOR]

The presence of renewable energy sources in hybrid renewable energy systems is considered a significant challenge since the generation mainly depends on meteorological conditions. Hence, employing a robust and flexible energy storage system is, therefore, a crucial solution in such circumstances. This paper investigates the performance evaluation of both batteries and superconducting magnetic energy storage (SMES) systems integrated with hybrid solar-wind DC-bus microgrid. The study focuses on enhancing the system stability using both storage technologies during normal and extreme renewables instabilities like wind gusts and shadows, and sudden load variations. Moreover, the load voltage/frequency were preserved constant during the distinct instabilities using the inverter control system. Productive findings showed the superior performance of utilizing the SMES over the batteries and its potential to enhance the system power-quality. [ABSTRACT FROM AUTHOR]

A maximum wind gust speed of 79.3 kn was measured on 2 August 2011 at the Esenboğa International Airport (International Air Transport Association [IATA] code: ESB), which is located in Ankara, the capital of Turkey. This value is the highest maximum wind gust speed value measured at this airport over the last 60 years. At the time of this meteorological event, a thunderstorm with heavy rain (+TSRA) occurred, which reduced the runway visibility to 150 m. Total precipitation of 21.8 mm was measured during a 20-min period, and part of the apron was submerged. A multicellular severe convective storm (MSCS) caused this influential event. The purpose of this study is to investigate the meteorological conditions underlying this MSCS event. Synoptic and sounding reanalysis products obtained with the Weather Research and Forecasting (WRF) model (four nested domains were established with horizontal resolution of 27, 9, 3, and 1 km), in addition to satellite, radar, sounding, aviation routine weather report (METAR), selected aviation special weather report (SPECI), and automated weather observing system (AWOS) (on a minute basis) data obtained from the Turkish State Meteorological Service (TSMS), were analysed. During MSCS transition, the maximum radar-measured reflectivity value was 61.0 dBZ. Based on Stokes' theorem, maximum runway divergence and convergence values of 15.0 × 10–3 and 19.3 × 10–3 s−1, respectively, were calculated. As a result, it was found that compared to the low convective available potential energy (CAPE) value of 978.9 J kg−1, the 0- to 6-km above-ground-level (AGL) deep layer shear was high, at approximately 40 kn. [ABSTRACT FROM AUTHOR]

Wind energy is one of the premier renewable energy sources that have gained popularity during the last decade. Among the currently available wind energy conversion systems (WECS), doubly fed induction generator-based technology has been widely employed due to its superior advantageous. The key features of the DFIG-based WECS include its ability to capture more wind energy and support the grid with large reactive power during short disturbance events. On the other hand, DFIG is very sensitive to grid faults which affect its fault ride through (FRT) capability. Furthermore, extreme wind gust even for short durations may lead to the violation of the low voltage ride through (LVRT) threshold limits set by worldwide transmission line operators. This situation cannot be mitigated by the turbine blades pitch controller since the response of the pitch mechanical control is much slower than the rapid dynamic change in the wind speed during short duration of wind gust events. While DFIG FRT capability has been discussed in several papers in the literature, not much attention was given to the mitigation of the effects of extreme wind gust of short duration on the DFIG performance. In this paper, the effect of various levels of wind gust on the performance of a DFIG-based wind energy conversion grid-connected system is investigated and mitigated using a new controller for superconducting magnetic energy storage (SMES) unit. A combination of hysteresis current and fuzzy logic controllers is employed to control the voltage source converter and the DC-DC chopper interfacing the SMES coil with the investigated system. Simulation results reveal the effectiveness of the proposed SMES controller that can be easily implemented within existing as well as new WECS installations.

In Hungary, as in other countries around the world, intervention firefighting units often use a mechanically operated aerial ladder for high-altitude rescue tasks. The safe operation of the equipment is only possible under strict safety regulations and requires a high level of expertise from the operating staff. During each intervention, extraordinary events such as sudden wind gusts can occur, which can cause extreme overload of the structural members of aerial ladders and have adverse effects on the equipment that can lead to malfunctions and - even worse - to accidents. Therefore it is important to study the consequences of external influences on aerial ladders during operation. The examination was performed on a widely used Magirus M32-L aerial ladder. The reason for choosing this type of aerial ladder is because it has a wide operating range, therefore test results can be a good starting point for other similar equipment as well. In this paper the development of our beam model and the performed finite element simulations are presented. The aim of the research is to develop a model based on geometrical measurement data that is suitable for studying the effects of wind gusts on the ladder structure. With our research, we aim to contribute to the safe operation of aerial ladders and to prevent possible accidents.

Storm Vaia on 29 October 2018, hit northeastern Italy and produced extensive damage in the immediacy of the event, including extensive tree felling in some places, as well as debris flow or earth flow landslides. This study aims to assess the susceptibility of the area following extreme events by evaluating the environmental criticality during strong winds and intense precipitation. Specifically, tree felling susceptibility due to wind and landslide susceptibility due mainly to precipitation were analysed by taking into consideration the geomorphological and environmental criticality of the areas under study. In particular, the area was modelled using fluid dynamics software, allowing an understanding of wind accelerations in relation to morphology, showing excellent agreement between the tree falls that occurred during the event and the areas with the highest wind gusts. With regard to landslides, an algorithm was prepared through GIS software that took into account the debris and earth flows that were activated during the extreme event in question, allowing the creation of a susceptibility map that delineated areas of high potential hazard. The final result is a landslide and tree-fall susceptibility map that determines the fragility of the territory during an extreme event. The procedures applied in the study area can be considered as a working method that allows critical values to be obtained for extreme events that can produce damage to the environment and beyond. It follows that this research also has an immediate application purpose by helping the political decision-maker in the choice of interventions to be implemented.

The flow past a square cylinder under the influence of a one dimensional gust was investigated using computational fluid dynamics (CFD). The effect of upstream wind gusts of the same amplitude but different duration was investigated with respect to their effect on the flow, the vortex-shedding, and the pressure distribution around the square cylinder. For the computations, a very large eddy simulation (VLES) model was implemented in an in-house code and validated against numerical and experimental results from the literature. The gusts of different duration were found to have a distinctly different effect. The short-duration gust causes a lock-on behavior with cessation of the alternating vortex shedding, and a symmetric pair-vortex was created above and below the square cylinder. It was observed that the pressure distribution on the lateral sides of the cylinder has the same magnitude and phase, which resulted in a zero total lift coefficient. In terms of a free-standing structures, such as a building, this would lead to zero instantaneous forces and pressure difference in the lateral direction with obvious implications for dynamic response and cross ventilation.

Modelling wind speed and trends helps in estimating the energy produced from wind farms. This study uses statistical models to analyze wind patterns in Melbourne, Australia. Three-hourly wind data during 2004-2008 was obtained from the Australian Government, Bureau of Meteorology, for Avalon Airport, Essendon Airport, Point Wilson, and View Bank stations. A logistic regression model was used to investigate the pattern of 3-hourly winds and gust prevalence while a linear regression model was applied to investigate wind speed trends. The 3-hour periods of the day, month, and year were used as the independent variables in the analysis. At four stations, wind speed and wind gust prevalence were mostly high between 9 AM and 6 PM. The monthly wind and wind gust prevalence were high from November to January while the highest annual prevalence occurred in 2007. The wind speed increased from 7 AM to 6 PM within which the maximum occurred. The monthly wind speed increased from November to January where it attained the maximum, decreasing to a minimum in May. The annual mean wind speed was highest in 2007. [ABSTRACT FROM AUTHOR]

The probabilistic structure of significant mesoscale fluctuations in wind speed over Moscow is investigated. It is shown based on the data of long-term regular measurements at the Ostankino TV tower, as well as at other points of the megalopolis and in the surrounding countryside, that normalizing wind gusts makes it possible to obtain a unified probabilistic assessment of significant deviations of wind speed in the atmospheric boundary layer from the predicted values. A statistical analysis of long-term measurements of wind speed at six heights in Ostankino, at automatic meteorological stations at different points of the Moscow metropolis, special high-frequency measurements in the southwestern part of the capital, and remote sodar measurements of wind speed in urban and suburban areas showed that the distribution of normalized extreme deviations of wind speed has a general probabilistic structure and a universal distribution of maxima over the observation interval. Asymptotic parameters of the Gumbel distribution are given for the specified reference interval (3 h) and a sampling rate of automatic measurements (1 min). Although variations in the sampling rate and reference interval slightly change these parameters, they do not change the type of distribution. Conserving the shape of the distribution function of extreme values at different heights measured using different instruments at different observation points indicates that it is universal and allows us to estimate low probabilities of rare maximum wind gusts if the forecast of the average wind speed and energy of subgrid turbulent fluctuations are available from numerical models. [ABSTRACT FROM AUTHOR]

Strong and highly variable winds and gusts are major hazards to infrastructure, properties, and life. Consequently, accurate prediction and timely detection of wind gust intensity have always been a focus of interest for earth scientists and weather forecasters. In this study, The WRF (Weather Research and Forecasting) post-process diagnostic of wind gusts (WPD method) was utilized to predict non-convective wind gust speeds using the direct outputs of the WRF model. To improve the prediction accuracy of this method, the results were post-processed using an artificial neural network (ANN). Multiple different ANN algorithms were examined to achieve the most accurate predictions possible. The results were evaluated using observational data extracted from 32 synoptic stations across Iran during the time period from 2014 to 2018. The results indicate that employing a multilayer perceptron ANN with a hybrid structure, consisting of one input layer comprising five parameters (10 m wind speed, sea level pressure, temperature, relative humidity, and predicted wind gust speed obtained from the WPD method), one hidden layer with a sigmoid activation function and 12 neurons, one output layer with a linear activation function and using the BR (Bayesian Regularization) training algorithm, significantly improve the accuracy of the WPD wind gust speed prediction method. The RMSE for wind gust speed prediction has decreased from 3.68 m/s (WPD method) to 1.88 m/s for the validation dataset. Additionally, there were considerable improvements of 50 %, 74 %, and 17 % in the MAE, MSE, and R2, respectively. • It is possible to forecast the wind gust speed using the outputs of the WRF model. • The post-processing applied by ANN on the forecasts obtained by the WPD method, increased the accuracy of the forecast. • The most suitable algorithm for ANN training among the three selected algorithms was BR. • the best performance of the ANN is obtained by selecting 12 neurons for the hidden layer and five parameters as input. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to clarify the effects of operation of braking devices by sliding friction against rails (rail brake) on the dynamic characteristics of gantry cranes for container handling after runaway caused by unexpected wind gust by a numerical analysis and to obtain the scientific knowledge which serves to develop the technology for safe stopping. Dynamic characteristics of the crane were calculated by the dynamic numerical simulation analysis using FEM. The crane was modeled by three-dimensional beam elements. The interaction forces that define the resistance characteristics of the crane runaway generated at the contact part between wheels of the traveling system and the rails were modeled. And the interaction forces at the contact part between the rail brakes and the rails were also modeled. For the wind gust that becomes runaway driving source, the wind direction, the velocity distribution in the vertical direction and the time change of the wind velocity were modeled. The load that the crane receives by the wind was calculated based on the ISO standard of the wind load assessment of cranes. In the analysis conditions of this paper, the runaway of the whole crane started when the driving wheels of the land side became slide state after those of the sea side became slide state. The dynamic characteristics through the stop of the crane after the operation of the rail brakes concerning cases of varying rail brake operation characteristics were analyzed and considered. The operating characteristics were defined by the time increase rate of the pressing load of the brake shoe, dPB/dt, the maximum value of it, PBmax, and the timing that the operation starts. The crane reached the stop after the runaway velocity decreased with the swing of the rail longitudinal direction of the crane structural system which consists mainly of the legs, the boom and the girder. When the acceleration of the upper part of the crane structural system increases by the rail brake operation, the generated inertial force reached the level that should be considered in checking of the structural safety. Finally, the relationship between the braking distance as an evaluation index of braking performance of the rail brake and the braking operation characteristics was presented and discussed.

An investigation of the effects of wind gusts on the directly interconnected wind generators is reported, and techniques toward the mitigation of the wind gust negative influences have been proposed. Using a directly interconnected system approach, wind turbine generators are connected to a single synchronous bus or collection grid without the use of power converters on each turbine. This bus can then be transformed for transmission onshore using High Voltage Alternating Current, Low-Frequency Alternating Current or High Voltage Direct Current techniques with shared power conversion resources onshore connecting the farm to the grid. Analysis of the potential for instability in transient conditions on the wind farm, for example, caused by wind gusts is the subject of this paper. Gust magnitude and rise time/fall time are investigated. Using pitch control and the natural damping of the high inertial offshore system, satisfactory overall system performance and stability can be achieved during these periods of transience.

The merging of a fast-moving bow echo with a convective cell of a hook-echo signature was studied by using polarimetric radar detections. Gusts with wind speeds near 35 m s−1 were recorded by the surface station, which caused significant damage. A convective cell with a mesovortex signature, which is hereafter referred to as a mini-supercell, was observed over the northeast of the bow echo before the convective merging. It was found that the mesovortex possessed cyclonic circulation and resembled a supercell-like feature. The merging of the bow echo and the mini-supercell strengthened the updraft near the apex of the bow echo. The enhanced updraft was also demonstrated by the appearance of a differential reflectivity (ZDR) column with a topmost height of 4 km above the melting layer (~4 km). The bow was separated into northern and southern sectors after merging with the mini-supercell, leading to the gusty wind over the surface of the south sector.

During the trajectory tracking process and low altitude flight of quadrotor, wind gust and ground effect will significantly affect the accuracy and stability of the controller. Therefore, it is vital for a quadrotor to have a robust controller against multiple disturbances. To mitigate this challenge, an active anti-disturbance control strategy based on generalized extended state observer is proposed in this article. Firstly, quadrotor dynamics is modeled as cascaded translational and rotational loops, and the characteristics of wind gust and ground effect are analyzed. Secondly, two generalized extended state observers are constructed for those loops respectively to estimate and attenuate the impact of wind gust and ground effect, and the position and attitude controller are designed based on backstepping method. Finally, real time experiments are carried out on hovering and circle trajectory tracking conditions. The results illustrate that the proposed controller has more advantages in high precision trajectory tracking and low altitude flight of quadrotor in existence of multiple disturbances. [ABSTRACT FROM AUTHOR]

Due to the low converters rating and cost of doubly fed induction generator (DFIG) along with its ability to function under variable wind speed, DFIG has been widely employed in wind energy conversion systems (WECSs). Unfortunately, the performance of DFIG is sensitive to the variation in the operating conditions and disturbance events at the grid side. This includes wind gust, voltage fluctuation and faults at the point of common coupling of the DFIG and the grid. In this study, a model‐free adaptive control (MFAC) is developed for a unified power flow controller (UPFC) in order to improve the overall dynamic performance of a DFIG‐based WECS during wind gusts and enhance the fault ride through capability of the DFIG during various disturbance events. The effective performance of the proposed controller is assessed through a comparison with a conventional proportional–integral (PI) controller optimised by a modified flower pollination algorithm. Results reveal the superiority of the proposed UPFC‐MFAC technique over the conventional PI controller currently used in most of the UPFC‐WECS applications. [ABSTRACT FROM AUTHOR]

The paper is a follow-up of the recent study on the assessment of discrete wind gust parameters impacting a flexible lightweight structure as a first step towards the evaluation of the worst-case scenario caused by strong wind gusts (JWEIA 231, 105207, 2022). The present study goes beyond by suggesting an optimization framework which allows to determine the worst-case scenario automatically. For this purpose, a stochastic response surface algorithm with a surrogate model based on radial basis functions is chosen. The algorithm relies on costly evaluations of the objective function, which consist of CPU-time intensive fully coupled fluid–structure interaction (FSI) high-fidelity simulations including the pre- and post-processing of the results. Besides the parallelization of the coupled FSI solver, a parallel version of the optimization algorithm allows to carry out several costly evaluations simultaneously. The Metric Stochastic Response Surface algorithm determines the worst case fast. Then, it continues to explore the optimization space to ensure that the global extremum is reached. A sensitivity study on relevant parameters of the optimization algorithm is conducted. Typically, for the present FSI setup, an optimization run takes one week with 6 evaluations in parallel to compute 100 different configurations. The worst case is found after about one third of the evaluations. The increase of parallel evaluations drastically reduces the wall-clock time, but the worst case is found later after half of the evaluations. This later finding is due to the parallel nature of the algorithm. Finally, the various sources of uncertainties that arise throughout the entire procedure are assessed and discussed. • Methodology to find the worst-case scenario of flexible structures under gust load. • Surrogate-based optimization algorithm to minimize costly FSI simulations. • High-fidelity fluid and structure modeling to capture transient effects. • Deterministic discrete gust model for a total control of its shape. • Application on a air-inflated flexible membrane in a turbulent boundary layer. [ABSTRACT FROM AUTHOR]

In this study, an investigation of a new thunderstorm intensity index (TSII) derived from lightning data is performed, along with its relationship to rain, wind, hail and waterspouts as well as instability indices (CAPE, LI, KI, and DLS). The study area is located in the northeastern Adriatic and includes various terrain types in a relatively small area (coastal, flatlands, hills and valleys, and mountain regions). The investigated period covers 11 years (2008–2018). The mathematical algorithm standing behind the TSII is based on the well-established methodology of lightning jump, allowing us to recognize areas where intensification in thunderstorms occurred. Our results suggest that these areas (with a positive TSII) experience significantly higher rain intensities and have higher total amounts of precipitation compared with areas where thunderstorms did not generate a TSII. Moreover, 76% of thunderstorm hail cases were associated with the presence of a TSII within a 15 km distance. The maximum reported wind speed also has higher values on a day with a TSII. Out of 27 waterspout events associated with lightning, 77% were related to a TSII. Due to the good spatial (3 km × 3 km) and high temporal (2 min) resolution of lightning data, the TSII can recognize even a local and short-lived intense system that is often misread by radars and satellites due to their inferior temporal resolution. The TSII is designed to be used as a climatological and diagnostic variable that could serve in lieu of more established data sources (e.g., station measurements and observations, radar imagery, etc.) if they are unavailable.

Environmental degradation, for example, by wind erosion, is a serious global problem. Despite the enormous research on this topic, complex methods considering all relevant factors remain unpublished. The main intent of our paper is to develop a methodological road map to identify key soil–climatic conditions that make soil vulnerable to wind and demonstrate the road map in a case study using a relevant data source. Potential wind erosion (PWE) results from soil erosivity and climate erosivity. Soil erosivity directly reflects the wind-erodible fraction and indirectly reflects the soil-crust factor, vegetation-cover factor and surface-roughness factor. The climatic erosivity directly reflects the drought in the surface layer, erosive wind occurrence and clay soil-specific winter regime, making these soils vulnerable to wind erosion. The novelty of our method lies in the following: (1) all relevant soil–climatic data of wind erosion are combined; (2) different soil types “sand” and “clay” are evaluated simultaneously with respect to the different mechanisms of wind erosion; and (3) a methodological road map enables its application for various conditions. Based on our method, it is possible to set threshold values that, when exceeded, trigger landscape adjustments, more detailed in situ measurements or indicate the need for specific management.