Wind Field Research Articles

Competing effects of wind and buoyancy forcing on ocean oxygen trends in recent decades

Ocean deoxygenation is becoming a major stressor for marine ecosystems due to anthropogenic climate change. Two major pathways through which climate change affects ocean oxygen are changes in wind fields and changes in air-sea heat and freshwater fluxes. Here, we use a global ocean biogeochemistry model run under historical atmospheric forcing to show that wind stress is the dominant driver of year-to-year oxygen variability in most ocean regions. Only in areas of water mass formation do air-sea heat and freshwater fluxes dominate year-to-year oxygen dynamics. The deoxygenation since the late 1960s has been driven mainly by changes in air-sea heat and freshwater fluxes. Part of this deoxygenation has been mitigated by wind-driven increases in ventilation and interior oxygen supply, mainly in the Southern Ocean. The predicted slowdown in wind stress intensification, combined with continued ocean warming, may therefore greatly accelerate ocean deoxygenation in the coming decades. The fact that the model used here, along with many state-of-the-art forced ocean models, underestimates recent ocean deoxygenation indicates the need to use forcing fields that better represent pre-industrial conditions during their spin-up.

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.

Numerical Simulation Investigation of Wind Field Characteristics and Acceleration Effects over V-Shaped Hills

Wind energy resources play an important role in sustainable development, and the accelerating effect of wind has been found in V-shaped hills, which informs the siting of wind turbines in this type of terrain. The wind field around the V-shaped hill was simulated using the CFD method. The impact of wind angle, hill pinch angle, and the distance between the hills on the wind field around the V-shaped hill was investigated. Wind acceleration effects at specific locations were studied and analyzed, and these findings were compared with established codes. It was observed that the wind speed at the hill’s top under each wind angle is significantly higher compared to other areas. Additionally, the acceleration ratio at the top generally exhibits a decreasing trend with increasing height. If the wind angle is 15° and the pinch angle is greater than or equal to 15°, or if the distance between the hills is less than or equal to 50 m, the wake zone will gradually transition from two to one. The distance between the hills minimally affects the acceleration ratio at the mid-height and top of the hill. Several codes exhibit inconsistency in specifying acceleration effects in hilly terrain. The findings in this paper align most closely with the American code at the base of the hill. At the hill’s top, the American code is the lowest above 100 m, while the Chinese code is the highest below 100 m. The findings in this paper fall between those of the Japanese and Australian codes. The formulas for the variation in wind speed acceleration ratio at typical locations with respect to height and the angle between the hills are provided.

Aeolus Winds Improve Arctic Weather Prediction

AbstractIt has been proven that assimilating winds from the Aeolus global Doppler Wind Lidar (DWL) would enhance the predictive skill of weather forecast models. In this study, we use a series of observing system experiments to examine how currently assimilated “operational” wind products and Aeolus winds impact environment and climate change Canada's global forecast system over the data‐sparse Arctic region. Aeolus winds improve the tropospheric wind and temperature forecasts by about 0.7%–0.9% of error reduction (a 15%–20% effect compared to the impact of operational wind products) while having little impact on specific humidity. In particular, Aeolus winds have an impact on forecasts of strong wind days on the wind and temperature fields that is double the impact for weaker wind days. On the other hand, the operational wind products do not show as large a discrepancy in impact between forecasts of disturbed and normal days. These findings suggest significant potential for global DWL observations to enhance severe weather prediction in polar regions.

In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes

Abstract. Between 14 March 2020 and 11 September 2021, meteorological measurement flights were conducted above the German Bight in the framework of the project X-Wakes. The scope of the measurements was to study the transition of the wind field and atmospheric stability from the coast to the sea, to study the interaction of wind park wakes, and to study the large-scale modification of the marine atmospheric boundary layer by the presence of wind parks. In total, 49 measurement flights were performed with the research aircraft Dornier 128 of the Technische Universität (TU) Braunschweig during different seasons and different stability conditions. Seven of the flights in the time period from 24 to 30 July 2021 were organised using a second research aircraft, the Cessna F406 of TU Braunschweig. The instrumentation of both aircraft consisted of a nose boom with sensors for measuring the wind vector, temperature and humidity and, additionally, a surface temperature sensor. The Dornier 128 was further equipped with a laser scanner for deriving sea state properties and two downward-looking cameras in the visible and infrared wavelength range. The Cessna F406 was additionally equipped with shortwave and longwave broadband radiation sensors for measuring upward and downward solar and terrestrial radiation. A detailed overview of the aircraft, sensors, data post-processing and flight patterns is provided here. Further, averaged profiles of atmospheric parameters illustrate the range of conditions. The potential use of the dataset has been already shown by the first few publications. The data of both aircraft are publicly available on the world data centre PANGAEA at https://doi.org/10.1594/PANGAEA.955382 (Rausch et al., 2023a).

Deep learning-based automated identification on vortex-induced vibration of long suspenders for the suspension bridge

Large amplitude vortex-induced vibration (VIV) of long suspenders, caused by vortex-shedding and wake flow, will decrease the service life of high-strength wires and its anchorage systems, hence listed as an essential monitoring indicator of the structural health monitoring system in the suspension bridges. Traditionally, a static vibration amplitude limitation is usually predefined and used to identify VIV from continuously monitored acceleration data of bridge suspenders. Due to the complexity of the starting vibration of the suspenders, it may not be able to flexibly adapt to the suspenders VIV under different conditions. In addition, transient but significant vibration events may not be captured since it relies only on static vibration amplitude limits without considering the temporal information of vibration. To address the above-mentioned issues, a novel framework to autonomously identify the suspenders VIV is proposed using the multimodal fusion techniques with deep neural networks. The main contributions of the methodology are: i) by calculating the wind field and vibration characteristic, two vibration response parameters are identified as indexes for the identification of suspenders VIV based on the significant difference method of big data analysis; ii) Two different modal information of time history images and power spectral density (PSD) sequences are used as inputs to the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) to extract the suspenders vibration response features from the time and frequency domain perspectives, respectively; and iii) The multimodal information is concentrated and enhanced by the multi-head attention (MHA) mechanism to achieve automated identification of the suspenders VIV. The proposed framework is validated with data collected from a full-scale long-span suspension bridge in comparison with the base model. The results show that the proposed framework can efficiently identify the full-cycle development process of the suspenders VIV. This study provides a convenient strategy for suspenders VIV identification, which can be used for bridge management and vibration mitigation device design.

Modal identification of wind turbine tower based on optimal fractional order statistical moments

AbstractIn vibration testing of civil engineering structures, the first two vibration modes are crucial in representing the global dynamic behavior of the structure measured. In the present study, a comprehensive method is proposed to identify the first two vibration modes of wind turbine towers, which is based on the analysis of fractional order statistical moments (FSM). This study offers novel contributions in two key aspects: (1) theoretical derivations of the relationship between FSM and vibration mode; and (2) successful use of 32/7‐order displacement statistical moment as the optimal FSM to identify wind turbine tower modes, by combining with noise resistance analysis, sensitivity analysis, and stability analysis, respectively. Using the proposed method, the FSM was first used to identify the modal vibration of wind turbine towers. By obtaining the response of the structure on the same vertical line, FSM was then calculated to estimate the corresponding structural modal vibration. Considering other influencing factors in the field test, the modal identification results of this index under different excitation forms and noise conditions were analyzed based on numerical simulation and verified with field wind tower test data. The results of the evaluation show that the proposed statistical moments of can accurately identify the first two vibration modes of wind turbine towers. This presents a new robust method for modal vibration identification, that is, simple and effective in its implementation.

Study on The Response Characteristics of Monopile Offshore Wind Turbines under Non-Gaussian loads in Typhoons

The fan structure is often seriously damaged under typhoon, so the study of the fan structure under typhoon is of great significance for its disaster prevention and mitigation. The actual measurement shows that the typhoon has obvious non-Gaussian characteristics, and the influence mechanism of this characteristic on the fan response characteristics is not clear. Therefore study the response characteristics of fans under non-Gaussian load. First, based on the autoregressive AR model, combined with the Johnson conversion model (JTM); second, the wind load is determined based on the specification; then the wind load. Finally, the response characteristics of 5MW fan are studied by characterizing the numerical cases of non-Gaussian fan with different strength of typhoon. The results show that the non-high characteristics of non-Gaussian wind field and the non-Gaussian characteristics become stronger with the strength of the non-Gaussian characteristics of wind field.

Seasonal variation of coastal currents and residual currents in the CAT BA – HA long coastal area (VIET NAM): Results of coherens model

The COHERENS model is used to investigate the temporal and spatial variation of the coastal currents in 2021 at the Cat Ba - Ha Long, northern Vietnam. The findings indicate that tidal oscillation has a notable impact on the current fields in short-term variations (hours to days). Meanwhile, the wind field and river discharge are the decisive factors affecting the seasonal variation of the current fields in Cat Ba - Ha Long coastal area. Furthermore, the characteristics of residual currents are significantly affected by river discharges and wind patterns, which vary across different months and seasons. During the southwest monsoon season (May to August), the residual currents have a prevailing direction towards the sea, from the west and south-southwest towards the east and north-northeast, reaching maximum speeds of approximately 0.1–0.15 m/s. Conversely, in the transitional and northeast monsoon seasons, the directions of residual currents are from the east-northeast to the west-southwest, with peak speed up to 0.2–0.25 m/s. Notably, the residual currents in the bottom and surface layers in the eastern-southwestern area of Cat Ba Island and the north of Ha Long Bay are in opposite directions.

Variation of Heliostat Wind Loads in a Radial Field Array Model

The design of heliostats throughout a concentrated solar power (CSP) plant are currently of uniform design, however, research into the variation in heliostat wind loading within a radially staggered field array can provide insight into potential material cost savings in heliostat field design. Experimental investigation was carried out on a field array model in the University of Adelaide large wind tunnel. A total of 64 heliostat models of size 0.1 × 0.1 m were radially arranged over four surround rows. Four 3-axis load cells were utilized to analyze field array cases of morning (0700 hours), noon (1200 hours), and evening (1700 hours) configurations. Angle calculations for beam reflection were made for the 21st March (equinox). Results show mean and peak drag force coefficients reduce with distance into the field for a 1700 hour case due to high upstream blockage. Comparing the downstream drag and lift force coefficients against each test configuration, when heliostats are at steep elevation angles, high flow blockage leads to a reduction of coefficients downstream (0700 hour and 1700 hour cases). When elevation angles are reduced (1200 hours), drag and lift coefficients increase with distance from the central tower in the downstream direction. Results also show the central tower increases load coefficients on downstream heliostats, and therefore should be considered in heliostat wind loading and field design.

Typhoon Early Warning and Monitoring Based on the Comprehensive Characteristics of Oceanic and Ionospheric Echoes from HFSWR: The Case of Typhoon Muifa

As devastating natural disasters, typhoons pose a tremendous threat to human society, making effective typhoon early warning and monitoring crucial. To address this challenge, High Frequency Surface Wave Radar (HFSWR), which can observe oceanic parameters such as typhoon wind fields in real time and even capture the dynamic changes in the ionosphere, has become an effective tool for typhoon monitoring. This paper investigates the interaction mechanisms about Typhoon-Acoustic Gravity Waves (AGWs)-Ionosphere, as well as Typhoon-Ocean Waves for HFSWR, and simulates these interaction processes within HFSWR. Then a typhoon early warning and monitoring scheme for HFSWR has been proposed: In the first stage, the S-shaped ionospheric disturbances observed by HFSWR are utilized as precursor signals for early typhoon warnings. In addition, the second stage involves analyzing changes in first-order oceanic echo spectral peak ratio to pinpoint when the typhoon eye enters the radar detection range, thus initiating the typhoon monitoring phase. Subsequently, the measured data from HFSWR collected during Typhoon “Muifa” (2212) in conjunction with the proposed scheme are evaluated in detail. The results indicate that AGWs generated by typhoons can propagate into non-typhoon areas within the detection range, causing S- shaped ionospheric disturbances and providing approximately 6 h of early warning. At around 8:05 (UTC+8), an increasing trend in the first-order spectral peak ratio was noted, indicating the entry of the typhoon eye into the detection range, which closely aligns with the official typhoon path and marks the transition to the monitoring phase. The proposed scheme is expected to enhance the capability for typhoon early warning and real-time monitoring in specific sea areas and mitigate the risks associated with typhoon-related disasters.

MR electrical properties mapping using vision transformers and canny edge detectors.

We developed a 3D vision transformer-based neural network to reconstruct electrical properties (EP) from magnetic resonance measurements. Our network uses the magnitude of the transmit magnetic field of a birdcage coil, the associated transceive phase, and a Canny edge mask that identifies the object boundaries as inputs to compute the EP maps. We trained our network on a dataset of 10 000 synthetic tissue-mimicking phantoms and fine-tuned it on a dataset of 11 000 realistic head models. We assessed performance in-distribution simulated data and out-of-distribution head models, with and without synthetic lesions. We further evaluated our network in experiments for an inhomogeneous phantom and a volunteer. The conductivity and permittivity maps had an average peak normalized absolute error (PNAE) of 1.3% and 1.7% for the synthetic phantoms, respectively. For the realistic heads, the average PNAE for the conductivity and permittivity was 1.8% and 2.7%, respectively. The location of synthetic lesions was accurately identified, with reconstructed conductivity and permittivity values within 15% and 25% of the ground-truth, respectively. The conductivity and permittivity for the phantom experiment yielded 2.7% and 2.1% average PNAEs with respect to probe-measured values, respectively. The in vivo EP reconstruction truthfully preserved the subject's anatomy with average values over the entire head similar to the expected literature values. We introduced a new learning-based approach for reconstructing EP from MR measurements obtained with a birdcage coil, marking an important step towards the development of clinically-usable in vivo EP reconstruction protocols.

Low-uncertainty wave tank testing and validation of numerical methods for floating offshore wind turbines

Abstract. Accurate simulation of the loads and motions of floating offshore wind turbines (FOWTs) in operation is key to the commercialisation of this technology. To improve such load predictions, a critical assessment of the capabilities and limitations of simulation methods for FOWTs is mandatory. However, uncertainties arise during the whole validation process of a numerical method. These can drastically impair the quality of the validation. In the case of FOWTs, the interaction between aerodynamic, hydrodynamic and mooring loads on the one hand and platform motions on the other hand causes a high level of uncertainty in the measurement data acquired in model tests. This also applies to comparing a numerical model to the test data, as these interactions make the distinction between cause and effect challenging. To address these challenges, several improvements to the validation process aiming to reduce the uncertainties are proposed and evaluated in this work. The major improvements are the measurement of the rotor thrust force excluding the tower top inertia loads, the wind field quality in the wave tank, a comparison of the rotor aerodynamics in the wind tunnel and wave tank, and the utilisation of hybrid simulations based on the measured platform motions. These steps are applied to wave tank tests of a FOWT utilising a single-point mooring and the subsequent validation of the numerical panel method panMARE. The improvements allowed for a considerable decrease in the random and systematic uncertainty in the model tests and made a valuable contribution to the distinction between cause and effect regarding the deviations between measurements and simulations.

Tropical Cyclone Wind Direction Retrieval Based on Wind Streaks and Rain Bands in SAR Images

Tropical cyclones (TCs) are associated with severe weather phenomena, making accurate wind field retrieval crucial for TC monitoring. SAR’s high-resolution imaging capability provides detailed information for TC observation, and wind speed calculations require wind direction as prior information. Therefore, utilizing SAR images to retrieve TC wind fields is of significant importance. This study introduces a novel approach for retrieving wind direction from SAR images of TCs through the classification of TC sub-images. The method utilizes a transfer learning-based Inception V3 model to identify wind streaks (WSs) and rain bands in SAR images under TC conditions. For sub-images containing WSs, the Mexican-hat wavelet transform is applied, while for sub-images containing rain bands, an edge detection technique is used to locate the center of the TC eye and subsequently the tangent to the spiral rain bands is employed to determine the wind direction associated with the rain bands. Wind direction retrieval from 10 SAR TC images showed an RMSD of 19.52° and a correlation coefficient of 0.96 when compared with ECMWF and HRD observation wind directions, demonstrating satisfactory consistency and providing highly accurate TC wind directions. These results confirm the method’s potential applications in TC wind direction retrieval.

Autonomous longitudinal separation control of aircraft in random wind fields based on MPC

Aiming at the problem of autonomous longitudinal separation under random disturbance of flight path, the random factor of high-altitude wind often leads to poor robustness of longitudinal separation between two aircraft. This paper proposes an autonomous longitudinal separation control method for aircraft based on model predictive control. Firstly, the nonlinear kinematic differential equation of the wind field difference between the two aircraft and the longitudinal separation is established, and the linear time-varying prediction model is derived. The longitudinal separation and path deviation distance of the two aircraft are selected as the optimization objectives, the high-altitude wind is the random disturbance, and the true airspeed and yaw angle of the leading aircraft are measurable. Terminal equality constraints are added to the air safety and aircraft performance constraints to maintain the stability of the system. To verify the effectiveness of the algorithm, within the prescribed simulation time of 120 seconds, this paper sets three groups of different expected intervals 12, 13, 14km. Through the designed MPC controller, by controlling the true airspeed and yaw angle of the trailing aircraft within the rolling time domain period, the interval curve between the two aircraft is relatively smooth and is always not less than the minimum safety interval of 10 km. It stabilizes at the expected target interval at the 74th, 90th and 118th seconds respectively, and begins to return to the route at the 58th, 74th and 95th seconds, and finally returns to the center line of the route; two groups of wind field control groups are set up, one group is the forecast wind intensity increased by 2 times, and the other group is the turbulent wind disturbance intensity increased by 8 times. Both can smoothly and stably establish the expected interval of 12 km at the 61st and 72nd seconds respectively.

Spatio-temporal averaging of jets obscures the reinforcement of baroclinicity by latent heating

Abstract. Latent heating modifies the jet stream by modifying the vertical geostrophic wind shear, thereby altering the potential for baroclinic development. Hence, correctly representing diabatic effects is important for modelling the mid-latitude atmospheric circulation and variability. However, the direct effects of diabatic heating remain poorly understood. For example, there is no consensus on the effect of latent heating on the cross-jet temperature contrast. We show that this disagreement is attributable to the choice of spatio-temporal averaging. Jet representations relying on averaged wind tend to have the strongest latent heating on the cold flank of the jet, thus weakening the cross-jet temperature contrast. In contrast, jet representations reflecting the two-dimensional instantaneous wind field have the strongest latent heating on the warm flank of the jet. Furthermore, we show that latent heating primarily occurs on the warm flank of poleward directed instantaneous jets, which is the case for all storm tracks and seasons.

A physical stochastic model of near-surface fluctuating wind fields

Modeling and simulation of atmospheric turbulence in coastal areas has emerged as a prominent area of research in recent years. This study presents a physical stochastic model to describe the horizontal coherence of fluctuating wind fields within the physical stochastic modeling frame. Based on the one-dimensional stochastic Fourier spectrum and isotropic turbulence theory, the horizontal coherence for fluctuating wind fields is expressed as a random function, with its probability information determined by the physical mechanism/background. The proposed physical stochastic model directly depicts the stochastic time series thereby enabling it to capture all probability information in detail comprehensively. The proposed model is numerically validated with the measured data obtained from an observation array constructed in Southeast China. This investigation holds significant potential for its application in wind-resistance design and reliability assessment of long-span structures.

Station-Keeping Control of Stratospheric Balloons Based on Simultaneous Optimistic Optimization in Dynamic Wind

Stratospheric balloons serve as cost-effective platforms for wireless communication. However, these platforms encounter challenges stemming from their underactuation in the horizontal plane. Consequently, controllers must continually identify favorable wind conditions to optimize station-keeping performance while managing energy consumption. This study presents a receding horizon controller based on wind and balloon models. Two neural networks, PredRNN and ResNet, are utilized for short-term wind field forecast. Additionally, an online receding horizon controller, based on simultaneous optimistic optimization (SOO), is developed for action sequence planning and adapted to accommodate various constraints, which is especially suitable due to its gradient-free nature, high efficiency, and effectiveness in black-box function optimization. A reward function is formulated to balance power consumption and station-keeping performance. Simulations conducted across diverse positions and dates demonstrate the superior performance of the proposed method compared with traditional greedy and A* algorithms.

A meso- to micro-scale coupled model under typhoon conditions considering vortex structure and coriolis effect for wind farms

Accurate simulations of typhoon-induced wind speeds on wind farms are crucial for the refined assessment of typhoon risks in wind turbines. Southeastern coastal area in China is rich in wind resources but is also severely threatened by typhoons. As an extremely destructive weather system with complex structures, the refined near-surface wind fields of typhoons are difficult to simulate by meso-scale models for risk assessment. Therefore, a coupled meso- and micro-scale model under typhoon conditions is proposed to simulate typhoon-induced winds on a wind farm. The Coriolis force is considered in the coupled model to reflect the rotating effect of typhoons caused by the vortex structure. A coupling algorithm based on objective analysis is proposed to construct boundary conditions at the coupling interface, to consider the variation of inflow variables in the vertical and cross-wind directions. Model constants of the two-equation turbulence model are calibrated based on typhoon field observations, to more reasonably simulate typhoons. A validation study is conducted, and the results show that the maximum wind speed on the wind farm simulated by the coupled model exhibits an increased accuracy compared with that of the meso-scale model, where the absolute error decreases by 34%.

Wind speed effect on infrared-image-based coal and gangue recognition with liquid intervention in LTCC

The commitment to achieving carbon neutrality by 2060 makes the clean transition of fossil energy production inevitable in China. As the primary fossil energy source, China produced approximately 4.66 billion tons of raw coal in 2023. Among them, in the fields of mining engineering and environmental science, the accurate recognition of gangue (one of the environmental pollutants produced by coal combustion is black-gray solid waste) from coal is crucial because it is a key step in reducing resource waste and environmental pollution. Hence, coal and gangue automatic recognition with high accuracy is very important for intelligent longwall top coal caving (LTCC) mining. A novel approach of “liquid intervention + infrared detection” is introduced to enhance the recognition accuracy when the exterior color of coal and gangue is similar. This study focuses on the infrared image recognition of coal and gangue after liquid intervention under varying wind speed conditions, and optimizes the image processing path. The effect of varying wind speed conditions on the recognition accuracy of coal and gangue after liquid intervention was analyzed, and the optimal wind speed range was determined. The morphological evolution characteristics of droplets under varying wind field conditions were studied by COMSOL two-phase flow interface. The results show that with the increase of wind speed, the surface contour of coal is gradually clear, and the overall recognition accuracy is also improved. When the high wind speed is 1.55 m/s, the recognition accuracy reaches 99.89%, and the recognition accuracy of other wind speed regions is also above 90% (within 7s). In addition, the numerical simulation can maintain the volume fraction of the droplet in a short time under the constant flow wind flow field, thus inhibiting the phenomenon that the recognition accuracy decreases with time. The simulation results are in good agreement with the physical experimental phenomena, which proves the reliability of the numerical simulation. This study is of great significance to the recognition of coal gangue types with low identification characteristics in LTCC, so as to ensure the primary economic benefits, ecological environment safety and sustainable development of coal mines.