Turbulence coherence in complex wind field: Focusing on its on-site characteristics based on multi-point clustering

Due to increased demands in transportation development, bridge construction has been extended to areas with complex wind fields. In addition to common flow features such as high wind speeds and strong turbulence intensity, in coastal areas, bridges are likely to be exposed to non-stationary and non-Gaussian high-speed wind fields during hurricane events. Bridges built in mountainous regions will experience varying wind directions, incident angles of attack (AOA), and wind speed variation due to undulating terrain. The complex wind fields are challenging to the bridge engineering community to which accurate calculation methods and suppression measures for bridge vibration are urgently required. In this paper, state-of-the-art research results are introduced through three categories: (a) the distinctive characteristics of complex wind fields in offshore and mountainous areas, (b) the categories of wind-induced vibrations for bridges, and (c) the suppression measures employed in engineering practices. Until now, the studies regarding the coupled bridge vibration in complex wind fields have made considerable progress, but a richer database of actual wind measurement results and more efficient simulation methods still need to be further established.

Evaluation of surface wind fields for prediction of directional ocean wave spectra during Hurricane Sandy

With the rise of the low-altitude economy, there is growing demand for performance and safety evaluation of logistics drones and urban aircraft operating in complex turbulent environments. Conventional wind tunnels, however, face challenges in simulating the non-uniform wind fields characteristic of urban low-altitude conditions, such as building wake flows, street canyon winds, and tornadoes. To address this gap, this study proposes a novel simulation device for low-altitude complex wind fields, which utilizes multi-fan coordinated control technology integrated with jet fan arrays, pressure-stabilizing chambers, and swirl fan systems to dynamically replicate horizontal flows, vertical flows, and specialized wind patterns. Numerical simulations using Ansys Icepak validate the effectiveness of the design: the optimized horizontal flow field achieves a wind speed of 83 m/s with a turbulence intensity ranging from 5% to 20%; the gust mode attains rapid response within 3 s; and high-fidelity simulations are achieved for wind shear, tornadoes (with a maximum tangential wind speed of 50 m/s), and downbursts (with a central vertical jet velocity of 40 m/s). Furthermore, for typical urban wind environments such as alley winds and intersection flows, the study elucidates the characteristics of abrupt wind speed variations and vortex dynamics induced by building obstructions. This research provides a new perspective and a potential technical pathway for testing low-altitude aircraft, assessing urban wind environments, and supporting related studies, thereby contributing to the advancement of complex wind field simulation technologies.

The parafoil has excellent gliding ability and operability for recovery of the first-stage booster, which makes the landing point of the first-stage booster controllable. However, during the recovery process, the wind field changes in real time due to changes in altitude and turbulent wind, which has a great influence on the trajectory and landing point of the parafoil recovery system. In order to realize accurate homing of the parafoil first-stage booster combination (PFC) in a complex wind field, an online trajectory planning algorithm based on the quartic Bézier curve is proposed in this paper. This algorithm combines the Bézier curve with the multiphase homing method and proposes a method to calculate the control points of the Bézier curve according to the time-varying wind field. First, a six-degrees-of-freedom model of the PFC is established, and the motion characteristics of the PFC are analyzed. Then, the drift of the PFC caused by the wind field is calculated, and it is superimposed on the target landing point to obtain the virtual landing point. On this basis, the quartic Bézier curve is used to plan the homing trajectory. The simulation results show that the algorithm has high computational efficiency for online trajectory planning. It can realize accurate homing of the PFC in complex wind fields with continuous unilateral brake deflections, which makes it conducive to practical application.

A climatological and numerical study of “Karakkaze,” a type of local wind in Japan, was conducted. First, winter days under a winter-type synoptic pressure pattern with daily minimum relative humidity of less than 40% were classified according to strong wind (wind speed ≥ 9 ms-1, Karakkaze day), medium wind (6 ms-1 ≤ wind speed -1), and weak wind (wind speed -1). Secondly, the spatial patterns of the surface wind in each category are confirmed by the Japan Meteorological Agency (JMA)-Automated Meteorological Data Acquisition System (AMeDAS) observation data. In addition, we compared the boundary-layer wind of the three categories using wind speed data from the observation tower of the Meteorological Research Institute (MRI) in Tsukuba and from the JMA wind profiler in Kumagaya. Finally, we performed one-dimensional numerical experiments using a column Planetary Boundary Layer (PBL) model to evaluate the impact of solar radiation and upper-level wind on the formation of the Karakkaze. The results are summarized as follows. On the strong-wind days, strong northwesterly winds appear in the area along the Arakawa River and the Tonegawa River from Maebashi. The surface wind speed has a clear diurnal variation with a peak in the early afternoon. Such a diurnal variation is observed up to a 200 m level, but this diurnal pattern nearly reverses itself between 200 m and 400 m levels. On weak-wind days, the diurnal variation pattern is similar to that in other two categories, but the reversed pattern appears at a 100 m level, not at a 200 m level. Stronger surface winds appear under a clearer winter-type pressure pattern. The correlation coefficient is 0.632 between the daily maximum surface wind speed and the daily mean wind speed at a height of 2759 m, whereas the correlation is 0.284 between the surface wind speed and daily sunshine duration, which, in a previous study, was suggested to be the most significant factor. Numerical experiments indicate that a large amount of solar radiation is a necessary condition for a strong daytime wind, but this is not a sufficient explanation for the difference in the surface wind speed between weak and strong-wind days.

Abstract. Empirical high-resolution surface wind fields, automatically generated by a weather diagnostic application, the WegenerNet Wind Product Generator (WPG), were intercompared with wind field analysis data from the Integrated Nowcasting through Comprehensive Analysis (INCA) system and with regional climate model wind field data from the Consortium for Small Scale Modeling Model in Climate Mode (CCLM). The INCA analysis fields are available at a horizontal grid spacing of 1 km × 1 km, whereas the CCLM fields are from simulations at a 3 km × 3 km grid. The WPG, developed by Schlager et al. (2017, 2018), generates diagnostic fields on a high-resolution grid of 100 m × 100 m, using observations from two dense meteorological station networks: the WegenerNet Feldbach Region (FBR), located in a region predominated by a hilly terrain, and its Alpine sister network, the WegenerNet Johnsbachtal (JBT), located in a mountainous region. The wind fields of these different empirical–dynamical modeling approaches were intercompared for thermally induced and strong wind events, using hourly temporal resolutions as supplied by the WPG, with the focus on evaluating spatial differences and displacements between the different datasets. For this comparison, a novel neighborhood-based spatial wind verification methodology based on fractions skill scores (FSSs) is used to estimate the modeling performances. All comparisons show an increasing FSS with increasing neighborhood size. In general, the spatial verification indicates a better statistical agreement for the hilly WegenerNet FBR than for the mountainous WegenerNet JBT. The results for the WegenerNet FBR show a better agreement between INCA and WegenerNet than between CCLM and WegenerNet wind fields, especially for large scales (neighborhoods). In particular, CCLM clearly underperforms in the case of thermally induced wind events. For the JBT region, all spatial comparisons indicate little overlap at small neighborhood sizes, and in general large biases of wind vectors occur between the regional climate model (CCLM) and analysis (INCA) fields and the diagnostic (WegenerNet) reference dataset. Furthermore, grid-point-based error measures were calculated for the same evaluation cases. The statistical agreement, estimated for the vector-mean wind speed and wind directions again show better agreement for the WegenerNet FBR than for the WegenerNet JBT region. A combined examination of all spatial and grid-point-based error measures shows that CCLM with its limited horizontal resolution of 3 km × 3 km, and hence too smoothed an orography, is not able to represent small-scale wind patterns. The results for the JBT region indicate significant biases in the INCA analysis fields, especially for strong wind speed events. Regarding the WegenerNet diagnostic wind fields, the statistics show acceptable performance in the FBR and somewhat overestimated wind speeds for strong wind speed events in the Enns valley of the JBT region.

Abstract. The existence of many different wind types in complex terrain and the difficulty of obtaining representative wind observations hinder the analysis of the general benefits of high-resolution climate modeling for winds. We show that the added value of kilometer (km)-scale modeling is particularly pronounced in mountainous terrain and increases substantially with wind speed, with the km-scale model and observations reaching twice larger speeds than a coarser model with 12 km grid spacing. At the same time, synoptically calm conditions are prone to local thermally generated circulations, such as slope flows with typically weak winds, whose modeling results can also be considerably affected by the model resolution. We therefore focus on the mountainous region of the southern Scandinavian Mountains and analyze the winds at two ends of the wind distribution: very strong winds, generally forced by large-scale weather systems, and local, thermally generated winds in synoptically calm conditions. Strong winds in the present climate are influenced more by the terrain height and high model resolution than by the large-scale forcing, while the future change is mostly governed by the global-model large-scale circulation change. For the thermal circulations in summer, in contrast to the coarse model, the km-scale model captures glacier downslope wind in the high mountains and the resulting convergence zone as well as the increased cloud cover where the glacier wind meets the daytime upslope wind. The future change in thermal circulations is primarily influenced by the future temperature change and the high model resolution. Because the future temperature changes are considerably less uncertain than the changes in large-scale circulation, the future of local thermal circulations can be estimated with less uncertainty compared to stronger winds.

Tropical cyclone phenomenon can give impacts such as heavy rain, strong winds, and high waves around its growth area. One of the tropical cyclones that has occurred is Seroja Tropical Cyclone which formed in the Sawu Sea on April 3, 2021. Therefore, this study aims to determine the effect of Seroja Tropical Cyclone on rainfall and surface wind speed in East Nusa Tenggara Province and the percentage comparison of rainfall and wind speed during the Seroja tropical cyclone event with the normal value of rainfall and surface wind speed over a 10-year period. The data used are daily rainfall and surface wind speed data during the Seroja tropical cyclone event, namely April 3 to 12, 2021 and daily average rainfall and wind speed data in April for 10 years in several affected districts in East Nusa Tenggara Province. Data processing is done by calculating the percentage comparison of rainfall and wind speed during the Seroja Tropical Cyclone event with normal rainfall and wind speed in several regions in East Nusa Tenggara. Based on the analysis, heavy to extreme rainfall and strong winds were found in several districts at a radius of about 400 km from the center of the cyclone. Although the category of this tropical cyclone is low, it is able to give impacts in the form of heavy to extreme rainfall and strong winds in the surrounding area. So it can be concluded that the tropical cyclone category does not directly affect rainfall and wind speed in an area, but the distance between the area and the center of the tropical cyclone is more influential in increasing rainfall and wind speed in an area. This is also proven by Sumaja's research in the case of tropical cyclones LUA and Narelle.

The record of span length for flexible bridges has been broken with the development of modern materials and construction techniques. With the increase of bridge span, the dynamic response of the bridge becomes more significant under external wind action and traffic loads. The present research targets specifically on dynamic performance of bridges as well as the transportation under strong wind. The dissertation studied the coupled vibration features of bridges under strong wind. The current research proposed the modal coupling assessment technique for bridges. A closed-form spectral solution and a practical methodology are provided to predict coupled multimode vibration without actually solving the coupled equations. The modal coupling effect was then quantified using a so-called modal coupling factor (MCF). Based on the modal coupling analysis techniques, the mechanism of transition from multi-frequency type of buffeting to single-frequency type of flutter was numerically demonstrated. As a result, the transition phenomena observed from wind tunnel tests can be better understood and some confusing concepts in flutter vibrations are clarified. The framework of vehicle-bridge-wind interaction analysis model was then built. With the interaction model, the dynamic performance of vehicles and bridges under wind and road roughness input can be assessed for different vehicle numbers and different vehicle types. Based on interaction analysis results, the framework of vehicle accident analysis model was introduced. As a result, the safer vehicle transportation under wind can be expected and the service capabilities of those transportation infrastructures can be maximized. Such result is especially important for evacuation planning to potentially save lives during evacuation in hurricane-prone area. The dissertation finally studied how to improve the dynamic performance of bridges under wind. The special features of structural control with Tuned Mass Dampers (TMD) on the buffeting response under strong wind were studied. It was found that TMD can also be very efficient when wind speed is high through attenuating modal coupling effects among modes. A 3-row TMD control strategy and a moveable control strategy under hurricane conditions were then proposed to achieve better control performance.

The altimeter wind speed algorithm at high wind speeds remains unsolved because of lack of observed data. In this study data at high wind speeds were generated using Yin's typhoon model, which consists of the Rankine vortex model and the angular momentum model with typhoon parameters, provided by the Joint Typhoon Warning Centre (JTWC). The accuracy of Yin's typhoon model can be validated by comparing it with recorded data from a weather station. By comparing the normalized radar backscatter cross‐section (NRCS) detected by the Jason‐1 altimeter with wind speed data inferred by Yin's typhoon model, an empirical algorithm valid for a range of wind speeds between 10 and 40 m s–1 is developed and proposed. The proposed algorithm is compared with the Jason‐1 operational algorithm and Young's altimeter wind retrieval algorithm. The study shows that, for the proposed algorithm and the operational algorithm for Jason‐1, the root mean square (RMS) errors are 3.38 and 3.60 m s–1, respectively, and the average relative errors are 18% and 19%, respectively, for wind speeds less than 27 m s–1. Hence, the proposed algorithm is in agreement with the operational algorithm for the Jason‐1 altimeter for wind speeds in the range 10–27 m s–1. However, the Jason‐1 operational algorithm is inaccurate for wind speeds above 27 m s–1 because the wind speeds used in the algorithm training process came from scatterometer wind products, and are significantly lower than those in strong wind and heavy rain conditions. Comparison of the proposed algorithm and Young's algorithm shows that the RMS errors are 6.27 and 15.18 m s–1, respectively, and the average relative errors are 16% and 59%, respectively, for wind speeds greater than 20 m s–1. The Holland typhoon model cannot accurately determine the outer wind field of typhoons since it extends cyclonic wind speeds to infinity. Young's altimeter wind retrieval algorithm depends on the Holland typhoon model, and the latter results in some errors. Compared with Young's altimeter wind retrieval algorithm, the proposed algorithm retrieves wind speeds with better accuracy. Therefore, the proposed algorithm, suitable for retrieving sea surface wind speeds in typhoons and other strong wind conditions, can be considered as supplementary to the Jason‐1 operational algorithm.

This study presents the monthly 10‐m wind speed climatology, decadal variability and possible trends in the North Atlantic and Europe from ERA5 reanalysis from 1979 to 2018 and investigates the physical reasons for the decadal variability. Additionally, temporal time series are examined in three locations: the central North Atlantic, Finland and Iberian Peninsula. The 40‐year mean and the 98th percentile wind speeds emphasize a distinct land‐sea contrast and a seasonal variation with the strongest winds over the ocean and during winter. The strongest winds and the highest variability are associated with the storm tracks and local wind phenomena such as the mistral. The extremeness of the winds is examined with an extreme wind factor (the 98th percentile divided by mean wind speeds) which in all months is higher in southern Europe than in northern Europe. Mostly no linear trends in 10‐m wind speeds are identified in the three locations but large annual and decadal variability is evident. The decadal 10‐m wind speeds were stronger than average in the 1990s in northern Europe and in the 1980s and 2010s in southern Europe. These decadal changes were largely explained by the positioning of the jet stream and storm tracks and the strength of the north–south pressure gradient in the North Atlantic. The 10‐m winds have a positive correlation with the North Atlantic Oscillation in the central North Atlantic and Finland on annual scales and during cold season months and a negative correlation in Iberian Peninsula mostly from July to March. The Atlantic Multi‐decadal Oscillation has a moderate negative correlation with the winds in the central North Atlantic but no correlation in Finland and Iberian Peninsula. Overall, our results emphasize that while linear trends in wind speeds may show a general long‐term trend, more information on the changes is obtained by analysing long‐term variability.

During recent years, wind energy has moved from an emerging technology to a nearly competitive technology. This fact, coupled with an increasing global focus on environmental concern and a political desire of a certain level of diversification in the energy supply, ensures wind energy an important role in the future electricity market. For this challenge to be met in a cost-efficient way, a substantial part of new wind turbine installations is foreseen to be erected in big onshore or offshore wind farms. This fact makes the production, loading and reliability of turbines operating under such conditions of particular interest.

Based on one year gradient wind data and the wind data of a strong typhoon observed by three meteorological towers located on the coast and at the inshore sea, the underlying surfaces of the meteorological towers were classified and the roughness lengths were calculated quantitatively. On the basis of strong wind characteristic representative assessment and sample selection on the wind data of strong typhoon Hagupit, the gust factor variation characteristics of tropical cyclones under different underlying surfaces were analyzed. The observed fact and variation rule were found as follows: 1) The roughness lengths under neutral atmospheric condition which were calculated using logarithmic wind profile fitting based on the observation data can describe the slight change of the underlying surface objectively. 2) The gust factor of strong typhoon wind didn’t have variation trends with wind speed. But the variation amplitude of the gust factor was rather large over rough underlying surface which had pronounced effect on the numerical design of structural engineering. 3) The variation of the gust factor with height satisfied power law or logarithmic law. The power law fitting was more suitable for smooth underlying surface while the logarithmic fitting was better over rough underlying surface. 4) The observation data also suggested that the relationship between gust factor and roughness length can be described by power or linear equation. 5) The gust factor observed in this typhoon case was different from the gust factor recommended by WMO: The gust factor of the offshore wind came from rough underlying surface was higher than the value recommended by WMO while the gust factor of the onshore wind came from smooth underlying surface is less than the WMO recommended value.

Cyclones can cause mass mortality of seabirds, sometimes wrecking thousands of individuals. The few studies to track pelagic seabirds during cyclones show they tend to circumnavigate the strongest winds. We tracked adult shearwaters in the Sea of Japan over 11 y and found that the response to cyclones varied according to the wind speed and direction. In strong winds, birds that were sandwiched between the storm and mainland Japan flew away from land and toward the eye of the storm, flying within ≤30 km of the eye and tracking it for up to 8 h. This exposed shearwaters to some of the highest wind speeds near the eye wall (≤21 m s-1) but enabled them to avoid strong onshore winds in the storm's wake. Extreme winds may therefore become a threat when an inability to compensate for drift could lead to forced landings and collisions. Birds may need to know where land is in order to avoid it. This provides additional selective pressure for a map sense and could explain why juvenile shearwaters, which lack a map sense, instead navigating using a compass heading, are susceptible to being wrecked. We suggest that the ability to respond to storms is influenced by both flight and navigational capacities. This may become increasingly pertinent due to changes in extreme weather patterns.

Long-term automated synoptic observing system (ASOS) data collected from 101 stations over a period of 50 years (1967–2016) were analyzed to investigate the distribution of strong winds on the Korean peninsula by utilizing a statistical method. The Gumbel distribution was used to estimate the wind speed for recurrence periods of 1, 10, 50, 75, and 100 years. For all recurrence periods, the coastal regions experienced higher wind speeds, which exceeded the strong wind advisory level, than the inland and metropolitan regions. The strong winds were predominantly induced by summertime typhoons, especially in the south and west coastal regions. In addition, nontyphoon factors, such as a topographical factor with atmospheric instability in a mountainous coastal region, can cause localized severe weather in the form of strong wind. By performing the weather research and forecasting (WRF) model simulation, an abrupt increase in wind speed up to 20 m·s−1 was reproduced under the condition of onshore prevailing winds heading toward a mountain ridge in a coastal region. Estimation of strong wind spatial distribution can help the region-to-region establishment of an action plan to prepare for damage caused by strong winds.