Maximum Wind Research Articles

Leveraging Extended Range Weather Forecast for Groundnut Bud Necrosis Disease Forewarning: A Data-driven Approach

Background: Groundnut (Arachis hypogaea L.), a globally prominent oilseed crop, is experiencing significant losses due to the Groundnut Bud Necrosis Virus (GBNV). The extended range weather forecast (ERWF) provides timely weather information and protects crops from weather-induced biotic and abiotic risks. Methods: An ERWF-based GBNV disease forewarning study was conducted at Coimbatore, Tamil Nadu in 2023 and 2024. The ERWF output from Weather Research and Forecasting (WRFv4.4) with two microphysics (WSM3 and Kessler) were leveraged to forewarn the GBNV disease, using the thumb rule as adapted in Tamil Nadu Agricultural University-Agro Advisory Service (TNAU - AAS): Web cum Mobile App, which is maximum temperature ( greater than 33oC), relative humidity (40-70%), wind speed ( greater than 5 kmph) and rainfall (0 mm). Result: Among the two microphysics options, the WSM3 performed better and provided more usable ERWF than the Kessler scheme. The WSM3 based ERWF usability percentage was 50 to 100 for rainfall and 80-100 for all other weather variables. The higher performance of ERWF resulted in a more precise forewarning of thrips and GBNV. The first and peak activity of thrips and GBNV incidence was well correlated (70-80%) with the ERWF based forewarning.

Observation and Numerical Simulation of a Windshear Case at an Airport in the Qinghai-Tibet Plateau

This paper documents a windshear case for an airport in the Qinghai-Tibet Plateau and explores, for the first time, the capability for high-resolution numerical weather simulation of the wind shear features. The windshear appears to be associated with pulses of the wind speed in a low-level easterly jet. The features are basically reproduced quite well with the high-resolution numerical model, though some discrepancies are identified, such as the maximum wind speed of the easterly jet and the magnitude of the eddy dissipation rate as compared with the actual Doppler LIDAR observations. Statistical analysis has been performed between the observation and the simulation results. The sensitivity of the modeling result to the choice of turbulence parameterization scheme has also been studied. The study result shows that it is possible to forecast the windshear feature using a high-resolution numerical weather prediction model for an airport in the complex terrain of the Plateau.

Experimental study on wind-induced vibration and aerodynamic interference effects of flexible photovoltaics

This study investigates the wind-induced vibrations (WIVs) of photovoltaic (PV) modules possessing unique characteristics such as lightweight construction, low frequency, and susceptibility to wind loads, in contrast to stationary PV systems installed on rooftops and ground surfaces. The complex interference effects within rows of flexible PV arrays were investigated under varying angles of wind attack (AOAs) and inter-row distances, specifically focusing on wind directions of 0° and 180°. A comparative analysis of the WIV of a single row was also conducted. The findings indicated that both single- and multi-row PV modules experience flutter instability as wind speeds increase, resulting in significant vibrations at wind directions of 0° and 180°. Vertical vortex-induced vibrations (VIVs) were observed in multi-row arrays at lower wind speeds prior to the onset of flutter instability, whereas no VIVs occurred in the single-row configuration. Within the three-row array, the middle row exhibited the most significant VIVs. An increase in AOA was found to correlate with elevated maximum VIV responses, wind speed, and vortex amplitude. Throughout various flutter instability scenarios, the third row consistently maintained stable. Notably, the critical wind speed for flutter was lower at a wind direction of 180°, and the VIV response was more pronounced compared to that observed at 0°.

Human-caused ocean warming has intensified recent hurricanes

Abstract Understanding how rising global air and sea surface temperatures (SSTs) influence tropical cyclone intensities is crucial for assessing current and future storm risks. Using observations, climate models, and potential intensity theory, this study introduces a novel rapid attribution framework that quantifies the impact of historically-warming North Atlantic SSTs on observed hurricane maximum wind speeds. The attribution framework employs a storyline attribution approach exploring a comprehensive set of counterfactuals scenarios—estimates characterizing historical SST shifts due to human-caused climate change—and considering atmospheric variability. These counterfactual scenarios affect the quantification and significance of attributable changes in hurricane potential and observed actual intensities since pre-industrial. A summary of attributable influences on hurricanes during five recent North Atlantic hurricane seasons (2019–2023) and a case study of Hurricane Ian (2022) reveal that human-driven SST shifts have already driven robust changes in 84% of recent observed hurricane intensities. Hurricanes during the 2019–2023 seasons were 8.3 m s−1 faster, on average, than they would have been in a world without climate change. The attribution framework’s design and application, highlight the potential for this framework to support climate communication.

Normalized Hurricane Damage in the United States: 1900-2022

Abstract Since 1900, landfalling hurricanes have been the costliest of all weather-related disasters to afflict the continental United States. To provide a present-day (2022) re-evaluation of this risk, this study employs an improved normalization approach to better understand potential economic event losses in the context of contemporary societal conditions. The updated methodology identifies impacted coastal counties using the newly available radius of maximum winds at landfall. Hurricane Katrina is the most expensive hurricane since 1900, with a likely 2022 normalized cost of US$234 billion. Combined losses from the 50 most expensive hurricane events are ~US$2.9 trillion in normalized economic losses. The study also explores some “analogue storms” where comparisons can be made between two historic storms with similar landfall locations. For example, Category 5 Andrew (1992) has lower 2022 normalized losses than Category 4 Great Miami (1926), at US$125 billion vs US$178, most likely due to the significantly different radius of maximum wind size (10 vs 20 nm). As with previous studies, we conclude that increases in inflation, coastal population, regional wealth, and higher replacement costs remain the primary drivers of observed increases in hurricane-related damage. These upsurges are especially impactful for some coastal regions along the US Gulf and Southeast Coasts that have seen exceptionally high rates of population/housing growth in comparison to country-wide growth. Exposure growth trends are likely to continue in the future and, independent of any influence of climate change on tropical cyclone behavior, are expected to result in greater hurricane-related damage costs than have been previously observed.

Typhoon Storm Surge Simulation Study Based on Reconstructed ERA5 Wind Fields—A Case Study of Typhoon “Muifa”, the 12th Typhoon of 2022

A storm surge, classified as an extreme natural disaster, refers to unusual sea level fluctuations induced by severe atmospheric disturbances such as typhoons. Existing reanalysis data, such as ERA5, significantly underestimates the location and maximum wind speed of typhoons. Therefore, this study initially assesses the accuracy of tropical cyclone positions and peak wind speeds in the ERA5 reanalysis dataset. These results are compared against tropical cyclone parameters from the IBTrACS (International Best Track Archive for Climate Stewardship). The position deviation of tropical cyclones in ERA5 is mainly within the range of 10 to 60 km. While the correlation of maximum wind speed is significant, there is still considerable underestimation. A wind field reconstruction model, incorporating tropical cyclone characteristics and a distance correction factor, was employed. This model considers the effects of the surrounding environment during the movement of the tropical cyclone by introducing a decay coefficient. The reconstructed wind field significantly improved the representation of the typhoon eyewall and high-wind-speed regions, showing a closer match with wind speeds observed by the HY-2B scatterometer. Through simulations using the FVCOM (Finite Volume Community Ocean Model) storm surge model, the reconstructed wind field demonstrated higher accuracy in reproducing water level changes at Tanxu, Gaoqiao, and Zhangjiabang stations. During the typhoon’s landfall in Shanghai, the area with the greatest water level increase was primarily located in the coastal waters of Pudong New Area, Shanghai, where the highest total water level reached 5.2 m and the storm surge reached 4 m. The methods and results of this study provide robust technical support and a valuable reference for further storm surge forecasting, marine disaster risk assessment, and coastal disaster prevention and mitigation efforts.

Estimation of some Climatological Parameters by WEKA Software for Selective Regions in Iraq

An Estimation is a direct summation that can produce new data from past measurements. In this study, we confirm the possibility of using the (WEKA) program in estimating the monthly values of some climatological parameters and investigate the influence of the time series' length parameters on the accuracy of estimation for selected regions of Iraq. Satellite data were used, which represent the monthly values for each of the minimum and maximum temperature, wind velocity, and relative humidity for the 1981 – 2021 time period, the absolute error rate (MAE), and the square root of the error rate (RMSE) with the correlation ( R2) are also identified to test the confidence of the prediction. Using (WEKA) software, which depends only on the time series of the parameters in the estimation, 12 months were estimated for the mentioned parameters. The estimated values by WEKA were close to the satellite data, thus we can depend on the software as a good source of meteorological data. Also, the study indicates that the time series' length strongly affects the accuracy of the estimation, as the increase in the time series of weather parameters increases the estimate's accuracy, and this increase fluctuates among parameters and varies from one region to another.

Satellite-based evidence of upwelling separation off NW Iberia

A high-resolution image sequence of sea surface temperature (SST) and Chlorophyll-a (Chl-a), together with numerical model solutions, is used to study the spatio-temporal variability of the two variables under intermittent upwelling-favourable winds. It is shown that the evolution of the cross-shore SST and Chl-a profiles over the shelf is linked to the intensity, duration and temporal separation between the wind events. The model's realistic representation of the cross-shore SST supports the interpretation that the observed variability is governed, in the inner-shelf, by the offshore separation of upwelling divergence and, over the mid-shelf, by offshore Ekman transport and mesoscale circulation. The observation of an alongshore low SST/low Chl-a band, bounded by the 30 m and 50 m isobaths, for the days of maximum wind stress, matching the model's solution for the outcrop of colder subsurface waters, constitute a satellite-based evidence of upwelling separation from the coast. The results are in close agreement with previous works on upwelling in shallow waters, straight coastline and gentle slope, but were not yet reported in the study area off NW Portugal. This evidence prompts for the need to use high-resolution (<1 km) numerical models/imagery to properly assess the inner-shelf circulation in the region, and the effects on the marine ecosystem, namely the offshore transport of marine organisms or pollutants.

Advanced reference crop evapotranspiration prediction: a novel framework combining neural nets, bee optimization algorithm, and mode decomposition

Various critical applications, spanning from watershed management to agricultural planning and ecological sustainability, hinge upon the accurate prediction of reference evapotranspiration (ETo). In this context, our study aimed to enhance the accuracy of ETo prediction models by combining a variety of signal decomposition techniques with an Artificial Bee Colony (ABC)–artificial neural network (ANN) (codename: ABC–ANN). To this end, historical (1979–2014) daily climate variables, including maximum temperature, minimum temperature, mean temperature, wind speed, relative humidity, solar radiation, and precipitation from four arid and semi-arid regions in Egypt: Al-Qalyubiyah, Cairo, Damietta, and Port Said, were used. Six techniques, namely, Empirical Mode Decomposition, Variational Mode Decomposition, Ensemble Empirical Mode Decomposition, Local Mean Decomposition, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, and Empirical Wavelet Transform were used to evaluate signal decomposition efficiency in ETo prediction. Our results showed that the highest ETo prediction accuracy was obtained with ABC-ANN (Train R2: 0.990 and Test R2: 0.989), (Train R2: 0.986 and Test R2: 0.986), (Train R2: 0.991 and Test R2: 0.989) and (Train R2: 0.988 and Test R2: 0.987) for Al-Qalyubiyah, Cairo, Damietta, and Port Said, respectively. The impressive results of our hybrid model attest to its importance as a powerful tool for tackling the problems associated with ETo prediction.

Coastal lake sediments from Arctic Svalbard suggest colder summers are stormier

The Arctic is rapidly losing its sea ice cover while the region warms faster than anywhere else on Earth. As larger areas become ice-free for longer, winds strengthen and interact more with open waters. Ensuing higher waves also increase coastal erosion and flooding, threatening communities and releasing permafrost carbon. However, the future trajectory of these changes remains poorly understood as instrumental observations and geological archives remain rare and short. Here, we address this critical knowledge gap by presenting a continuous Holocene-length reconstruction of Arctic eolian activity using coastal lake sediments from Svalbard. Exposed to both polar Easterlies and Westerly storm tracks, sheltered by a bedrock barrier, and subjected to little post-glacial uplift, our study site provides a stable baseline to assess Holocene changes in the dominant wind systems of the Barents Sea region. To do so with high precision, we rely on multiple independent lines of proxy evidence for wind-blown sediment input. Our reconstructions reveal quasi-cyclic summer wind maxima during regional cold periods, and challenge the view that a warmer and less icy future Arctic will be stormier.

The research on the applicability of different typhoon wind fields in the simulation of typhoon waves in China’s coastal waters

Typhoon waves possess significant destructive potential, and their numerical simulation relies on accurate sea surface wind fields. An evaluation of different combinations of the radial air pressure distribution coefficient B and the radius of maximum wind speed (Rmax) in the Holland wind field (HWF) model was conducted to determine the optimal configuration. The HWF and the ERA5 wind field (EWF) were used as input wind fields to drive the typhoon wave model for China’s coastal waters. Validation results indicated that neither wind field accurately reflected real conditions; therefore, a hybrid wind field (HBWF) was created by combining HWF and EWF using weighting coefficients that vary with the radius of wind speed to enhance accuracy. Simulation results showed that the HBWF improved the accuracy of significant wave heights (SWHs), with a mean relative error of 25.29%, compared to 32.48% for HWF and 27.94% for EWF. Additionally, HBWF also demonstrated the best performance in terms of root mean square error (RMSE) and consistency index. Overall, the HBWF enhances the simulation accuracy of typhoon waves in China's coastal waters.

New Rankine Vortex Models Developed Based on SMAP Measurements

Abstract The L-band passive microwave radiometer on board the NASA Soil Moisture Active Passive (SMAP) satellite can measure brightness temperature to retrieve sea surface wind speed under tropical cyclone (TC) conditions without being affected by rainfall or signal saturation caused by high wind speeds. Based on this advantage, this paper used the SMAP wind products for parameterizing the key decay exponent α of the Rankine vortex model (a traditional parametric model of the TC wind field) and finally developed new Rankine models. The SMAP dataset included 67 TC cases. Through data statistics, we examined the relationship between α and the maximum wind speed Um, the relationship between α and the radius of maximum wind speed (Rm), and the relationship between Rm and the averaged radius of 17 m s−1 (R17). Results showed that the three relationships were both positive correlations, indicating that α can be parameterized in three empirical ways. The first way is to calculate solely with Um. The second way is to calculate solely with Rm. The third way is to calculate Um and Rm together. The three ways correspond to three new models: the SMAP Rankine Model-1 (SRM-1), the SMAP Rankine Model-2 (SRM-2), and the SMAP Rankine Model-3 (SRM-3). Finally, comparisons were made between the new models and three existing Rankine models, according to the model simulations and the Advanced Microwave Scanning Radiometer 2 measurements of 49 TC cases. Results showed that the SRM-3 performed best overall. Significance Statement Ocean surface wind fields are important driving factors for numerical models to guide evolution forecasting and risk assessment of tropical cyclones. The purpose of this study is to utilize the SMAP products to modify the traditional Rankine vortex model for tropical cyclone surface wind field estimation. Rankine decay exponent was found between 0.3 and 0.9 and positively dependent upon maximum wind speed and its radius. Based on these characteristics, the proposed new Rankine models could calculate the decay exponent and further the TC surface wind field symmetrically with high accuracy, simply using maximum wind and its radius. This paper shows a practical use of SMAP measurements on TC wind field monitoring, analyzing, and modeling.

Application research of wind profile radar in short-term heavy rainfall forecast of typhoon in Fujian Province

Based on wind profile radar data, this paper aims at different typhoon processes landed and affected Fujian from 2011 to 2019, according to the nature of typhoon rainstorm, it can be classified into outer precipitation before typhoon landed, main body precipitation and precipitation at the rear of typhoon, the change of the characteristic quantities in approaching time of the occurrence of short-term heavy rainfall was analyzed, and the typhoon case in 2020 was back calculated. The results show that, the characteristics of low-level jet streams (maximum wind speed at low altitude, minimum height of jet streams, and low-level jet stream index), as well as the magnitude of vertical wind shear below 700 hPa, have important indicative significance for the occurrence of short-term heavy rainfall. (1) More than 80 % of short-term heavy rainfall occurred 3 h before the low-level jet stream already existed. The maximum wind speed below 2 km was basically close to a normal distribution, and the occurrence of heavy precipitation showed a bimodal pattern. The percentage of wind speed between 8 and 32 m/s was the highest, exceeding 85 %. The wind direction of the strong wind is mainly NE, SE, and SW. Classification analysis showed that the distribution characteristics of wind speed of the main precipitation were the same as before, but the wind direction SE was higher than NE. The wind speed of pre-landfall precipitation was basically skewed, and the occurrence time of heavy precipitation followed a normal distribution. The percentage of wind speed between 16 and 32 m/s was the highest, and the wind direction was the same as before classification. The maximum wind speed of precipitation in the rear was basically bimodal distribution, with a relatively even distribution, and the wind direction was mainly SE and SW. (2) In the 3 h before the occurrence of short-term heavy precipitation, there was an increase in the maximum wind speed value, a decrease in the minimum extension height, and an increase in the low-level jet stream index I. As short-term heavy rainfall approached, the intensity of the low-level jet stream remained high and its proportion increased. The minimum achievable extension height gradually decreased and remained stable at a low value. In the first 2 h of heavy rainfall, the wind speed reached its maximum, the extension height was the lowest, and the low-level jet stream index I was the highest. Classifying and discussing it, the precipitation in the rear was different, and the lowest height decreased to the lowest at the time of occurrence, at which point the I value reached its maximum. The characteristics of the other two categories were the same as before the classification. (3) The vertical wind shear from the ground to different isobaric surfaces gradually decreased with the increase of height. With the approach of short-term heavy rainfall, the vertical wind shear of each layer basically decreased gradually, after the beginning of heavy rainfall, which decreased to the minimum. The characteristics of main body precipitation were the same as before the classification. Pre-landfall precipitation, in addition to the gradual decrease of vertical wind shear from the ground to 925 hPa, both 850 hPa and 700 hPa increased first and then decreased, vertical wind shear decreased to the minimum after the beginning of heavy rainfall. Precipitation at rear of typhoon, vertical wind shear from ground to 700 hPa increased compared with that before the occurrence of heavy rainfall, while wind shear from ground to 925 hPa and 850 hPa showed the characteristics of decreasing when heavy rainfall occurred. (4)The median values of various physical quantities before the occurrence of typhoon short-term heavy rainfall were selected as the thresholds of short-term heavy rainfall will occur. The intensity of LLJ is about 21 m/s, the lowest height is about 0.65 km, the LLJ index I is about 36 × 10−3s−1. Vertical wind shear from the ground to 925 hPa, 850 hPa and 700 hPa are respectively about 15.9 × 10−3s−1, 11.2 × 10−3s−1 and 5.1 × 10−3s−1.

Forecasting slipform labor productivity in the construction of reinforced concrete chimneys

The aim of this study is to identify the factors that influence productivity in the construction of reinforced concrete chimney (RCC) and to develop a predictive model for forecasting slipform labor productivity in RCC projects. In this scope, 73 “daily site reports” from two RCC constructions were utilized to calculate the slipform labor productivity. The efficiency value’s estimation part for the slipform process considered factors affecting productivity under four main categories: project information, weather conditions, job characteristics, and team-related information. The independent variables were identified as: man-hour value, RCC diameter, shell thickness, daily rising height, height of the working platform, concrete quantity, rebar quantity, minimum and maximum temperatures, maximum wind speed, rain conditions, and slipform quantity. The dependent variable is the efficiency value of slipform process. For this, an ensemble machine-learning technique, Gradient Boosting Machines, was used to predict slipform labor productivity in RCC constructions. According to the analysis, the R2 value is 0.900, indicating a high level of accuracy in the model’s predictions. The study found that the parameters with the highest impact on efficiency were daily rising height and slipform quantity. To validate the accuracy of the prediction model, a survey was conducted with technical experts, and the results were analyzed to investigate the model’s accuracy.

Optimal Design of Wind-Solar complementary power generation systems considering the maximum capacity of renewable energy

This paper proposes constructing a multi-energy complementary power generation system integrating hydropower, wind, and solar energy. Considering capacity configuration and optimization of the complementary power generation system, a dual-layer planning model is constructed. The outer layer aims to maximize the accessible scale of wind and solar energy, while the inner layer considers the matching degree between power output and grid load. The optimization uses a particle swarm algorithm to obtain wind and solar energy integration's optimal ratio and capacity configuration. The results indicate that a wind-solar ratio of around 1.25:1, with wind power installed capacity of 2350 MW and photovoltaic installed capacity of 1898 MW, results in maximum wind and solar installed capacity. Furthermore, installed capacity increases with increasing wind and solar curtailment rates and loss-of-load probabilities. When the loss-of-load probability is set to 3 %, the impact of wind and solar curtailment rates on the installed capacity ratio is relatively small. The complementary characteristics of wind and solar energy can be fully utilized, which better aligns with fluctuations in user loads, promoting the integration of wind and solar resources and ensuring the safe and stable operation of the system.

Regional frequency analysis of extreme wind in Pakistan using robust estimation methods

The quantile estimates of extreme wind speed are needed for various areas of interest using regional frequency analysis (RFA) and extreme value theory. These calculations are crucial for the coding of wind speed. The data was taken from the NASA official website at a 10-meter distance and measured in meters per second (m/s). RFA of annual maximum wind speed (AMWS) using L-moments is performed utilizing annual maximum wind speed data from sixteen sites (16) in Pakistan’s Khyber Pakhtunkhwa province. There are no sites that are found to be discordant. The wards method is used to construct a homogenous region and make two homogenous regions from 16 sites. The heterogeneity test justifies that both clusters are homogeneous. The most appropriate probability distribution from the Generalized Normal (GNO), Generalized Logistic (GLO), Pearson Type-3 (P3), Generalized Pareto (GPA), and Generalized Extreme Value (GEV) distributions is chosen to calculate regional quantiles. According to the L-moments diagram and Z statistics, the GEV for Cluster- Ι and GLO for Cluster- ΙΙ are the best suggestions from the others. Both clusters’ robustness is measured utilizing relative bias (RB) and relative root mean square error (RRMSE). Overall, GEV distribution is fit for cluster-Ι, and the GLO distribution is fit for cluster-ΙΙ. Utilizing the site mean and median as index parameters, we can also find at-site quantiles from regional quantiles. The study’s quantile estimates can be employed in codified structural designs with policy consequences.

Investigation of the characteristics of low-level jets over North America in a convection-permitting Weather Research and Forecasting simulation

Abstract. In this study, we utilized a high-resolution (4 km) convection-permitting Weather Research and Forecasting (WRF) simulation spanning a 13-year period (2000–2013) to investigate the climatological features of low-level jets (LLJs) over North America. The 4 km simulation enabled us to represent the effects of orography and the underlying surface on the boundary layer winds better. Focusing on the continental US and the adjacent border regions of Canada and Mexico, this study not only identified several well-known large-scale LLJs, such as the southerly Great Plains LLJ and the summer northerly California coastal LLJ, but also the winter Quebec northerly LLJ which received less focus before. All these LLJs reach their peak in the nighttime in the diurnal cycle. Thus, the different thermal and dynamic mechanisms forming these three significant LLJs are investigated in this paper. Inertial oscillation theory dominates in the Great Plain LLJ, and the California coastal LLJ is formed by the baroclinic theory, whereas the Quebec LLJ is associated with both theories. Moreover, the high-resolution simulation revealed climatic characteristics of weaker and smaller-scale LLJs or low-level wind maxima in regions with complex terrains, such as the northerly LLJs in the foothill regions of the Rocky Mountains and the Appalachians during the winter. This study provides valuable insights into the climatological features of LLJs in North America, and the high-resolution simulation offers a more detailed understanding of LLJ behavior near complex terrains and other smaller-scale features.

Characterizing surface pressure and wind fields of typhoons approaching Hong Kong

In this paper, 17 severe typhoons that have affected Hong Kong are simulated using an advanced numerical atmospheric simulation system - Weather Research and Forecasting model (WRF). The simulated surface pressure and wind fields of these typhoons are validated against a wide range of field observations. Then azimuth-dependent models for the radius of maximum winds and the Holland parameter are established statistically at the surface level. It is observed that the shape parameter of the Holland pressure model is smaller at the surface than that at the gradient level. And the Holland wind field model cannot well reproduce the simulated radial wind profiles due to the complexities of nonuniform surface conditions and typhoon dynamics. It is found that the modified Rankine model provides satisfactory estimates of typhoon wind speeds in Hong Kong. Additionally, wind field asymmetries of typhoons approaching Hong Kong are highly correlated with the typhoon track velocity, vertical wind shear and the angle between them. The proposed statistical models and identified characteristics of wind field asymmetries of typhoons will provide useful information for rapidly assessing typhoon wind hazards.

Study on wind load characteristics of gable roof under tornado

This research simulates the behavior of a tornado on a double-slope roof using the Ward tornado generator and the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SS{T_{k - \\omega }}$$\\end{document} turbulence model. The effects of different ground roughness, slope angle, and wind field position on the tornado load characteristics of gable roofs were studied. The tornado-generating device established the tornado field under various working conditions, and the simulation results were compared with the experimental data to verify the reliability of the simulation results. The wind pressure distribution of gable roofs with four different slope angles was analyzed to find the most unfavorable roof condition of the tornado field. The gable roof’s aerodynamic and wind pressure characteristics at various places in the tornado field were explored by comparing the wind pressure coefficients at five distinct positions on smooth and rough ground. The lift-drag and wind pressure coefficients of five kinds of ground roughness were calculated to determine the influence of different ground roughness on the aerodynamic force and partial pressure distribution of the gable roof. The ground roughness reduces the vortex ratio because the ground roughness reduces the maximum tangential wind speed and the radius of the vortex core. Therefore, the gable roof’s suction increases as the updraft increases.

Design and Implementation of Wind Speed-Based Radar Antenna Safety System Prototype

Air defense radar is a system that detects the presence of one or more air objects at a certain distance, altitude, and direction. One type of air defense radar used by the Indonesian National Armed Forces (TNI) is the Thomson TRS 2215D. An essential part of the radar is the rotating part of the radar antenna support called the antenna pivot. The rotation of the radar antenna must constantly be monitored and controlled for rotational stability at a speed of 6 Rotations per Minute (RPM) with a maximum wind speed of 120 km/h to prevent damage to the driving gear. Stormy weather with high wind speeds can cause the rotation speed of the radar antenna to be uncontrollable, which can cause damage. The solution offered in this study is to build a safety system that will lock the radar antenna automatically when the wind speed is detected to exceed tolerances and maintain the security of the radar antenna and its support system. The safety system was designed using an ESP32 Wi-Fi device equipped with an anemometer wind speed sensor, a Liquid Crystal Display (LCD) monitor, a Direct Current (DC) motor, and a Blynk Internet of Things (IoT) application. The test was conducted in a simulation using a multi-meter and oscilloscope measuring instrument. Testing the radar antenna's safety system prototype on a laboratory scale shows that the safety system can work as designed. The system can lock the radar antenna when the airflow is set at a speed of 54 km/h or 15 m/s, communication with the Blynk server works well, and the ESP32 device can transmit data at a maximum distance of 14 meters.