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Modern technologies, such as airborne laser scanning (ALS) and advanced data analysis algorithms, allow for the efficient and safe use of resources to protect infrastructure from potential threats. This publication presents a study to identify trees that may fall on highways. The study used free measurement data from airborne laser scanning and wind speed and direction data from the Institute of Meteorology and Water Management in Poland. Two methods were used to determine the crown tops of trees: PyCrown and OPALS. The effect of wind direction on potential hazards was then analyzed. The OPALS method showed the best performance in terms of detecting trees, with an accuracy of 74%. The analysis showed that the most common winds clustered between 260° and 290°. Potential threats, i.e., trees that could fall on the road, were selected. As a result of the analysis, OPALS detected between 140 and 577 trees, depending on the chosen strategy. The presented research shows that combining ALS technology with advanced algorithms and wind data can be an effective tool for identifying potential hazards associated with falling trees on highways. [ABSTRACT FROM AUTHOR]

To determine near-surface winds within and above vegetation canopies for operational environmental applications, a wind model must run at high-resolution (O(1-10 m)), in a few minutes, using limited input information, and requiring minimal computing resources (e.g., personal computers). Current research models simulate large domains at coarse resolution or small domains at fine scale, but canopy simulations can take days. Fast- modeling approaches are used to solve large complex wind fields, but they oversimplify the roughness elements' distribution impact on momentum exchanges. To overcome these deficits, the fast-running wind model QUIC-URB (Quick Urban and Industrial Complex) was augmented with a high-resolution canopy wind solver. The wind model includes a non-local factor that describes how momentum propagates through the canopy and how sub-canopy jets appear under certain conditions. QUIC-URB was also coupled with the mesoscale WRF (Weather Research and Forecasting) model to downscale wind fields from a few kilometers to a meter. The new QUIC Canopy Model resolves 3-D wind fields over hundreds of millions of cells in less than 30 s per time step on a personal computer. It was compared to two canopy models for real quasi-homogeneous and heterogeneous canopies. An error analysis shows that the model was relatively accurate with a normalized root-mean-square error of about 0.2 m s-1in the quasi-homogeneous canopy, and a mean absolute error of 0.3 m s-1. The new model is suitable for coupling with pollution dispersion, wildfire spread, and numerical weather prediction models over weakly complex terrain, defined here as a mildly undulating environment with gradual changes in elevation and a heterogeneous distribution of plants. [ABSTRACT FROM AUTHOR]

In this study, we propose a two-parameter symmetric tropical cyclone (TC) pressure model, derived from the fundamental equations of the TC wind field. This model rectifies the deficits of the traditional TC pressure model mathematically. It incorporates a new parameter into the Holland pressure model and establishes relationship equations between the new parameter, Holland parameter B, and TC attributes such as pressure difference, maximum wind speed radius, geographical latitude, and inflow angle. This derivation is achieved theoretically. Our model not only tackles the limitations of the traditional pressure model by meeting the gradient wind equations, but it also resolves the uncertainty issue of parameter B arising from varied factor selection, data time frames, and research maritime areas. As practical applications, we apply both this model and the corresponding wind field model to five TC profiles. Further, we juxtapose them with primary pressure and wind field models and conduct error and statistical significance analyses. Our findings reveal that the two-parameter model produces results on par with the Holland model and superior to Fujita and Takahashi models. Notably, reanalysis of the wind field consistently underestimates the wind field near the maximum wind speed. Hence, a hybrid wind field, synthesized from the modeled and reanalyzed wind fields, appears to be one of the most effective methodologies for reconstructing a tropical cyclone's wind field. [ABSTRACT FROM AUTHOR]

To determine near-surface winds within and above vegetation canopies for operational environmental applications, a wind model must run at high-resolution (O(1–10 m)), in a few minutes, using limited input information, and requiring minimal computing resources (e.g., personal computers). Current research models simulate large domains at coarse resolution or small domains at fine scale, but canopy simulations can take days. Fast-modeling approaches are used to solve large complex wind fields, but they oversimplify the roughness elements’ distribution impact on momentum exchanges. To overcome these deficits, the fast-running wind model QUIC-URB (Quick Urban and Industrial Complex) was augmented with a high-resolution canopy wind solver. The wind model includes a non-local factor that describes how momentum propagates through the canopy and how sub-canopy jets appear under certain conditions. QUIC-URB was also coupled with the mesoscale WRF (Weather Research and Forecasting) model to downscale wind fields from a few kilometers to a meter. The new QUIC Canopy Model resolves 3-D wind fields over hundreds of millions of cells in less than 30 s per time step on a personal computer. It was compared to two canopy models for real quasi-homogeneous and heterogeneous canopies. An error analysis shows that the model was relatively accurate with a normalized root-mean-square error of about 0.2 m s−1 in the quasi-homogeneous canopy, and a mean absolute error of 0.3 m s−1. The new model is suitable for coupling with pollution dispersion, wildfire spread, and numerical weather prediction models over weakly complex terrain, defined here as a mildly undulating environment with gradual changes in elevation and a heterogeneous distribution of plants.

Modern technologies, such as airborne laser scanning (ALS) and advanced data analysis algorithms, allow for the efficient and safe use of resources to protect infrastructure from potential threats. This publication presents a study to identify trees that may fall on highways. The study used free measurement data from airborne laser scanning and wind speed and direction data from the Institute of Meteorology and Water Management in Poland. Two methods were used to determine the crown tops of trees: PyCrown and OPALS. The effect of wind direction on potential hazards was then analyzed. The OPALS method showed the best performance in terms of detecting trees, with an accuracy of 74%. The analysis showed that the most common winds clustered between 260° and 290°. Potential threats, i.e., trees that could fall on the road, were selected. As a result of the analysis, OPALS detected between 140 and 577 trees, depending on the chosen strategy. The presented research shows that combining ALS technology with advanced algorithms and wind data can be an effective tool for identifying potential hazards associated with falling trees on highways.

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Prediction and reanalysis of storm surge rely on wind and pressure fields from either parametric tropical cyclone wind models or numerical weather model reanalysis, and both are subject to large errors during landfall. This study assesses two sets of wind/pressure fields for Hurricane Florence that made landfall along the Carolinas in September 2018 and appraises the impacts of differential structural errors in the two suites of modeled wind fields on the predictive accuracy of storm surge driven thereby. The first set was produced using Holland 2010 (H10), and the second set is the Hurricane Weather Research and Forecasting (HWRF) reanalysis created by the NWS National Centers for Environmental Prediction (NCEP). Each is validated using a large surface data set collected at public and commercial platforms and then is used as input forcing to a 2-D coastal hydrodynamic model (Delft3D Flexible Mesh) to produce storm surge along the Carolina coasts and major sounds. Major findings include the following. First, wind fields from HWRF are overall more accurate than those based on H10 for the periphery of the storm, though they exhibit limitations in resolving high wind speeds near the center. Second, applying H10 to the best track data for Florence yields an erroneously spike in wind speed on September 15th when the storm reduced to a tropical depression. Third, HWRF wind fields exhibit a progressively negative bias after landfall, likely due to deficiencies of the model in representing boundary layer processes, and to the lack of assimilation of surface product after landfall for compensating for these deficiencies. Fourth, using HWRF reanalysis as the forcings to Delft3D yields more accurate peak surges simulations, though there is severe underestimation of surge along the shoreline close to the track center. The peak surge simulations by Delft3D are biased low when driven by H10, even though over several locations the H10 model clearly overpredicts surface wind speeds. This contrast highlights the importance of resolving wind fields further away from the center in order to accurately reproduce storm surge and associated coastal flooding. [ABSTRACT FROM AUTHOR]

In this study, we propose a two-parameter symmetric tropical cyclone (TC) pressure model, derived from the fundamental equations of the TC wind field. This model rectifies the deficits of the traditional TC pressure model mathematically. It incorporates a new parameter into the Holland pressure model and establishes relationship equations between the new parameter, Holland parameter B, and TC attributes such as pressure difference, maximum wind speed radius, geographical latitude, and inflow angle. This derivation is achieved theoretically. Our model not only tackles the limitations of the traditional pressure model by meeting the gradient wind equations, but it also resolves the uncertainty issue of parameter B arising from varied factor selection, data time frames, and research maritime areas. As practical applications, we apply both this model and the corresponding wind field model to five TC profiles. Further, we juxtapose them with primary pressure and wind field models and conduct error and statistical significance analyses. Our findings reveal that the two-parameter model produces results on par with the Holland model and superior to Fujita and Takahashi models. Notably, reanalysis of the wind field consistently underestimates the wind field near the maximum wind speed. Hence, a hybrid wind field, synthesized from the modeled and reanalyzed wind fields, appears to be one of the most effective methodologies for reconstructing a tropical cyclone’s wind field.

The East China Sea is an ocean region with frequent typhoons, typhoons are also the main reason for inducing typhoon waves. The complexity of typhoon waves is closely related to the complexity of typhoon wind field. In previous studies, symmetrical wind field models or superimposed wind field models were usually used to simulate typhoon waves. However, the actual wind fields are asymmetric, and the asymmetry is affected by many factors. Therefore, three wind field models are used to simulate the wind field of Typhoon Muifa that moved through the East China Sea. Moreover, the abovementioned wind field models are used to drive the third-generation wave model SWAN to simulate the wave field and wave spectrum of Typhoon Muifa. Studies show that the values generated by the asymmetric wind field model are most consistent with the actual measurement data. This is especially the case if the typhoon center is closer to the station. The accuracy of the typhoon waves simulated using the asymmetric wind field model is better than that of the other two wind field models. The asymmetric wind field can reflect the asymmetric characteristics of the typhoon well. The substantial wave heights on the right side of typhoon’s path are substantially higher than those on the left side of path. Additionally, the maximum wave spectral density and total energy of waves as simulated by the asymmetric wind field are both larger than those of the other two wind field models. Thus, the asymmetric wind field model is more suitable for the numerical simulation of typhoon waves in the East China Sea.

The hazards induced by tropical cyclones (TCs), for example, high winds, extreme precipitation, and storm tides, are closely related to the TC surface wind field. Parametric models for TC surface wind distribution have been widely used for hazards and risk analysis due to their simplicity and efficiency in application. Here we revisit the parametric modeling of TC wind fields, including the symmetrical and asymmetrical components, and its applications in storm tide modeling in the North Atlantic. The asymmetrical wind field has been related to TC motion and vertical wind shear; however, we find that a simple and empirical background‐wind model, based solely on a rotation and scaling of the TC motion vector, can largely capture the observed surface wind asymmetry. The implicit inclusion of the wind shear effect can be understood with the climatological relationship between the general TC motion and wind shear directions during hurricane seasons. For the symmetric wind field, the widely used Holland wind profile is chosen as a benchmark model, and we find that a physics‐based complete wind profile model connecting the inner core and outer region performs superiorly compared to a wind analysis data set. When used as wind forcing for storm tide simulations, the physics‐based complete wind profile integrated with the background‐wind asymmetry model can reproduce the observed storm tides with lower errors than the often‐used Holland model coupled with a translation‐speed‐based method. Plain Language Summary: The socioeconomic repercussions incurred by tropical cyclones (TC) are closely related to the TC surface wind distribution. Considering the symmetrical feature of mature TCs' structure, parametric wind profile models—depicting the mean surface wind speed at various radial distances to the TC center—have been widely applied in TC‐related hazard and risk assessment, mainly due to their simple mathematical expression and computational efficiency in application. In this study, we show that a physics‐based complete wind profile model, connecting the inner and outer TC cores, performs superiorly compared to the widely used Holland wind model when validated against a wind analysis data set. We also find that a simple background wind model can well capture the observed surface wind asymmetry. When used as wind forcing for storm tide simulations, the complete wind profile integrated with the background‐wind model can reproduce the observed storm tides along the U.S. East and Gulf coasts with lower errors than the often‐used Holland model coupled with a translation‐speed‐based method. Key Points: A physics‐based complete wind profile model shows a better capability of depicting the TC symmetrical wind than the Holland wind modelA background‐wind‐based model can capture the TC wind asymmetry well with computational efficiencyThe physics‐based wind profile coupled with the background‐wind model may be a better way of forcing TC‐induced storm tide simulations [ABSTRACT FROM AUTHOR]

In this paper, we study the feasibility of sending drones to deliver goods from a depot to a customer by solving what we call the Mission-Feasibility Problem (MFP). Due to payload constraints, the drone can serve only one customer at a time. To this end, we propose a novel framework based on time-dependent cost graphs to properly model the MFP and tackle the delivery dynamics. When the drone moves in the delivery area, the global wind may change thereby affecting the drone’s energy consumption, which in turn can increase or decrease. This issue is addressed by designing three algorithms, namely: (i) compute the route of minimum energy once, at the beginning of the mission, (ii) dynamically reconsider the most convenient trip towards the destination, and (iii) dynamically select only the best local choice. We evaluate the performance of our algorithms on both synthetic and real-world data. The changes in the drone’s energy consumption are reflected by changes in the cost of the edges of the graphs. The algorithms receive the new costs every time the drone flies over a new vertex, and they have no full knowledge in advance of the weights. We compare them in terms of the percentage of missions that are completed with success (the drone delivers the goods and comes back to the depot), with delivered (the drone delivers the goods but cannot come back to the depot), and with failure (the drone neither delivers the goods nor comes back to the depot). [ABSTRACT FROM AUTHOR]

The sun's position in the sky appears to strongly influence the vertical wind gradient within the atmospheric boundary layer. This study uses a quantitative research design that combines the position of the sun along with surface wind speeds to estimate the wind gradient. The model applies to uncluttered simple terrain and requires only 10 m wind speed data to extrapolate wind speeds and wind turbine energy production to heights of 60 m or more. The average daytime and nighttime model wind speed errors are 1.7% and 2.4%, respectively. The average daytime and nighttime model turbine energy production errors are 3.8% and 6.1%, respectively. The model offers a practical and low-cost alternative to tall tower systems to assess wind resources, especially for remote sites. [ABSTRACT FROM AUTHOR]

Abstract Different wind models are being used for the operational safety evaluation of a high-speed train exposed to crosswinds. However, the methodology for simulating natural wind is of substantial importance in the wind–train system, and different simplified forms of natural wind result in different levels of accuracy. The purpose of the research in this paper is to investigate the effects of different wind models on the operational safety evaluation of high-speed trains. First, three wind models, namely, steady wind model, gust wind model, and turbulent wind model, are constructed. Following this, the algorithms for computing the aerodynamic loads using the wind models are described. A multi-body dynamic model of a vehicle is then set up using the commercial software “Simpack” for investigating the dynamic behavior of a railway vehicle exposed to wind loads. The rollover risks corresponding to each wind model are evaluated by applying the definition of characteristic wind curves (CWC). The results indicate that the CWC computed using the gust wind model is marginally higher than that computed using the turbulent wind model; the difference is less than 1%. With regard to the steady wind model, the assurance coefficient substantially affects the final CWC. A reasonable agreement of CWC between the steady wind model and turbulent wind model can be obtained by applying an “appropriate value” of the assurance coefficient. This study included a systematic analysis of the operational safety evaluation results using different wind models; the analysis can serve as a reference basis for different engineering accuracy requirements.

Accuracy of flow angles measurements becomes crucial as the aircraft approaches higher angle of attack. Flight path reconstruction (FPR) is an excellent tool for air data calibration. An important element of air data calibration is the estimation of wind velocities. The objective of this paper is to evaluate different approaches of wind estimation within the framework of FPR. Flight test data of a high performance aircraft is subjected to FPR and the estimated wind velocities and flow angle trajectories are presented and discussed to demonstrate the impact of wind estimation on aircraft flow angles. Results clearly show that accuracy of reconstructed flow angles improves when time varying wind models are used. The proposed analytical wind model is found to be as effective as augmented parameters in Extended Kalman filter and computationally less intensive. [ABSTRACT FROM AUTHOR]

Wind has a significant influence on the operational flight safety. To quantify the influence of the wind characteristics, a wind series generator is required in simulations. This paper presents a method to model the stochastic wind based on operational flight data using the Karhunen–Loève expansion. The proposed wind model allows us to generate new realizations of wind series, which follow the original statistical characteristics. To improve the accuracy of this wind model, a vine copula is used in this paper to capture the high dimensional dependence among the random variables in the expansions. Besides, the proposed stochastic model based on the Karhunen–Loève expansion is compared with the well-known von Karman turbulence model based on the spectral representation in this paper. Modeling results of turbulence data validate that the Karhunen–Loève expansion and the spectral representation coincide in the stationary process. Furthermore, construction results of the non-stationary wind process from operational flights show that the generated wind series have a good match in the statistical characteristics with the raw data. The proposed stochastic wind model allows us to integrate the new wind series into the Monte Carlo Simulation for quantitative assessments.

Cup and sonic anemometers were operated in and about an empty pen (60 m × 68 m) on the outer (south) edge of a large cattle feedlot in southern Alberta. Mean wind speed, measured at constant height above ground, varied by more than a factor of four across the pen, the spatial transects being distinct for different wind directions—implying (for instance) that efforts to quantify feedlot gas emissions by micrometeorological methods will be prone to error, unless the drastic lateral inhomogeneity of wind statistics is accounted for. A subset of the observations, selected for southerly winds and weak thermal stratification, were aggregated and compared with steady-state, three-dimensional numerical simulations using “ASL3D”, a Reynolds-averaged Navier–Stokes model with eddy viscosity closure that represents the influences both of feedlot windbreak fences and of topography (Wilson, 2018). Simulations confirm that wind drag on the tall ( H  ≈ 3 m), low porosity (25%) slatted wooden fences was by far the dominant aerodynamic disturbance at this site. Various options were tested for the placement of computational domain boundaries, and it was found that the influence of fences at the faraway edges of neighbouring pens is practically negligible in comparison with that of the fences lying immediately upwind—that is, the transect of relative mean wind speed within the instrumented pen was largely determined by the nearest upwind fence(s). It is also concluded that when the mean wind is obliquely incident on low porosity fences of this type, simulations are improved if the horizontal wind component tangential to the fence is forced to vanish (at the fence). [ABSTRACT FROM AUTHOR]

The steady-state, Reynolds-averaged momentum equations, with a simple eddy viscosity closure, are solved numerically to compute the spatial variation in surface-layer mean windspeed over irregular, gently rolling terrain. Simulations, with both this non-linear model “ASL3D” and (for comparison) with the pre-existing linear “Mixed Spectral Finite-Difference” or MSFD model, are compared with observed winds from anemometers aligned on a 140 m transect in a rolling field near Lacombe, Alberta. Recorded wind speeds, normalized and aggregated by wind direction sector, characterize local wind variation over terrain whose elevation varied by roughly ±10 m over a radius of about half a kilometer from the instrumented transect. For northeast and southwest winds particularly, both models agree well with the observations. In southeast winds, observed spatial variation of the wind was weak, except that an anemometer close to fences and gates recorded distinctly lower speeds: provided those obstructions are represented by adding a localized sink in the momentum equations, the ASL3D model transect is (again) in quite good agreement with the observations. For northwest winds, however, agreement of modelled and measured transects is poor, presumably because a steep, wooded slope lay upwind from the anemometer array. Overall the linear correlation coefficient between modelled and observed fractional deviations of wind speed from the reference value is 0.72. Other than as regards the flexibility to represent such complications as fences, plant canopies (etc.), computed wind fields over for the present terrain do not suggest any compelling advantage of the more laborious non-linear model (ASL3D) over the semi-analytical MSFD treatment. It is concluded that, when applied over gentle terrain, the skill intrinsic to even such a simple paradigm as ASL3D (and MSFD) represents a meaningful and potentially useful alternative to the neglect of lateral inhomogeneity. [ABSTRACT FROM AUTHOR]

An evaluation of the effect of bottom friction, wind drag coefficient, and meteorological forcing is conducted using a tightly coupled wave and circulation model, SWAN + ADCIRC (i.e., Simulating WAves Nearshore + ADvanced CIRCulation), to hindcast the storm surge of Hurricane Rita (2005). Wind drag coefficient formulations of Powell, Zijlema, and Peng & Li are used to calculate wind stresses. Bottom friction and wind drag coefficients are systematically increased and decreased to quantify their impacts on the hindcast. Different meteorological forcing options are applied to study the effect of wind fields on storm surge development and propagation. Simulated water levels are compared with observed data collected from about 150 locations. It is evident that a lower bottom friction causes higher and faster surge propagation, and earlier arrival of inundation peak at locations far from the land fall. Drag coefficients of Powell, with or without a cap of 0.002, and Zijlema produce similar results, while that of Peng & Li slightly overpredicted the surge. Wind fields may cause overprediction or underprediction of the surge, depending on the choice of the wind model. A good agreement is found between Zijlema's findings and this study; that simultaneously decreasing or increasing both bottom friction and wind drag essentially provides the same hindcast results. [ABSTRACT FROM AUTHOR]

With UAVs becoming increasingly popular in the industry, vertical take-off and landing (VTOL) convertiplanes are emerging as a compromise between the advantages of planes and multicopters. Due to their large wing surface area, VTOL convertiplanes are subject to a strong wind dependence on critical phases such as take-off, landing, and hovering. Developing a new and improved unmanned aerial vehicle (UAV) is often expensive and associated with failures and accidents. This paper proposes the dynamic characterization of a commercial VTOL convertiplane UAV in copter mode and provides a novel method to estimate the aerodynamic forces and moments for any possible wind speed and direction. Starting from Euler's equations of rigid body dynamics, we have derived the mathematical formulation to precisely consider aerodynamic forces and moments caused by any wind speed and direction. This unique approach will allow for VTOL convertiplane UAVs to be trained and tested digitally in take-off, hovering, and landing maneuvers without the cost and hassle of physical testing, and the dependence on existing wind conditions. A digital twin of a VTOL convertiplane UAV in copter mode has been modeled and tested in the Gazebo robotics simulator. Take-off, hovering and landing maneuvers have been compared with and without the wind physics model. Finally, the simulator has been tested against real flight conditions (reproducing the mean wind speed and direction only), showing a natural and realistic behavior. • VTOL UAVs are most affected by wind during critical phases. • Aerodynamic coefficients are determined all around the aircraft. • Wind forces and moments are modeled for any incoming direction. • A software-in-the-loop flight controller replicates real flight behavior. • Flight tests correlate with simulation experiments. [ABSTRACT FROM AUTHOR]