Wind Field Measurements Research Articles

The Flexible Array of Radars and Mesonets (FARM)

AbstractThe Flexible Array of Radars and Mesonets (FARM) Facility is an extensive mobile/quickly deployable (MQD) multiple-Doppler radar and in situ instrumentation network. The FARM includes four radars: two 3-cm dual polarization, dual frequency (DPDF), Doppler on Wheels (DOW6/DOW7), the Rapid-Scan DOW (RSDOW), and a quickly deployable (QD) DPDF 5-cm C band on Wheels (COW). The FARM includes three mobile mesonet (MM) vehicles with 3.5-m masts, an array of rugged QD weather stations (PODNET), QD weather stations deployed on infrastructure such as light/power poles (POLENET), four disdrometers, six MQD upper-air sounding systems and a Mobile Operations and Repair Center (MORC). The FARM serves a wide variety of research/educational uses. Components have deployed to >30 projects during 1995–2020 in the United States, Europe, and South America, obtaining pioneering observations of a myriad of small spatial- and temporal-scale phenomena including tornadoes, hurricanes, lake-effect snow storms, aircraft-affecting turbulence, convection initiation, microbursts, intense precipitation, boundary layer structures and evolution, airborne hazardous substances, coastal storms, wildfires and wildfire suppression efforts, weather modification effects, and mountain/alpine winds and precipitation. The radars and other FARM systems support innovative educational efforts, deploying >40 times to universities/colleges, providing hands-on access to cutting-edge instrumentation for their students. The FARM provides integrated multiple radar, mesonet, sounding, and related capabilities enabling diverse and robust coordinated sampling of three-dimensional vector winds, precipitation, and thermodynamics increasingly central to a wide range of mesoscale research. Planned innovations include S-band on Wheels Network (SOWNET) and Bistatic Adaptable Radar Network (BARN), offering more qualitative improvements to the field project observational paradigm, providing broad, flexible, and inexpensive 10-cm radar coverage and vector wind field measurements.

Aeroelastic stability analysis and failure damage evaluation of wind turbine blades under variable conditions

ABSTRACT Failure during the start and brake processes of a 1.5 MW horizontal axis wind turbine blade was examined using a measured wind field with fluid-structure coupling. The maximum blade displacement and stress with angular acceleration during the start process were 7.14% and 16.27%, respectively, larger than those without acceleration, whereas during braking they were 37.71% and 26.96% larger, respectively, without acceleration. Further, angular acceleration had a greater impact on the second-order frequency of vibration than the first-order, significantly impacting the braking process. The maximum dynamic stress and amplitude of the blades during starting were 4.35 MPa and 0.56 m, and during braking were 35.86 MPa and 3.13 m, respectively. Based on drone images of the blades, several failure modes were identified. This research will provide key inspection area guidance for employing drones to inspect blades to improve inspection efficiency. A large amount of damage images are collected and classified into damage levels, and an image processing system are established, which can quickly identify damage characteristics of the blade and export the inspection report quickly and accurately. Through a large number of drone detection experiments, this technology has a wide range of application prospects and extremely high efficiency.

Offshore wind farm global blockage measured with scanning lidar

Abstract. The objective of this paper was the experimental investigation of the accumulated induction effect of a large offshore wind farm as a whole, i.e. the global-blockage effect, in relation to atmospheric-stability estimates and wind farm operational states. We measured the inflow of a 400 MW offshore wind farm in the German North Sea with a scanning long-range Doppler wind lidar. A methodology to reduce the statistical variability of different lidar scans at comparable measurement conditions was introduced, and an extensive uncertainty assessment of the averaged wind fields was performed to be able to identify the global-blockage effect, which is small compared to e.g. wind turbine wake effects and ambient variations in the inflow. Our results showed a 4 % decrease in wind speed (accuracy range of 2 % to 6 %) at transition piece height (24.6 m) upwind of the wind farm with the turbines operating at high thrust coefficients above 0.8 in a stably stratified atmosphere, which we interpreted as global blockage. In contrast, at unstable stratification and similar operating conditions and for situations with low thrust coefficients (i.e. approx. 0 for not operating turbines and ≤ 0.3 for turbines operating far above rated wind speed) we identified no wind speed deficit. We discussed the significance of our measurements and possible sources of error in long-range scanning lidar campaigns and give recommendations on how to measure small flow effects like global blockage with scanning Doppler lidar. In conclusion, we provide strong evidence for the existence of global blockage in large offshore wind farms in stable stratification and the turbines operating at a high thrust coefficient by planar lidar wind field measurements. We further conclude that global blockage is dependent on atmospheric stratification.

Field measurement of wind pressure on a large-scale spatial structure and comparison with wind tunnel test results

Due to the features of light weight, high flexibility, and slight damping, large-scale spatial structures are very sensitive to wind load. Thus, special attention must be paid to wind effect on large-scale spatial structures. A wind pressure field measurement was carried out to characterize the actual wind pressure of a large-span spatial structure. Meanwhile, it is also intended to provide reliable full-scale measurements for verification of wind tunnel test results widely used in the design and construction of structure. In this study, both wind tunnel test and field measurement are utilized to investigate the properties of the wind pressure acting on a typical large-scale spatial structure. Specifically, wind pressure coefficients, spatial distribution, probability density distribution (PDF), non-Gaussian characteristics, and power spectral density (PSD) are fully compared and discussed based on the results of the wind tunnel test and long-term field measurement. The comparison results show that generally the results of the wind tunnel test have good agreement with those of the field measurement. In the meanwhile, the discrepancies between them are also observed. This study aims to fully investigate the wind effects on large-scale spatial structure and enhance the understanding of wind loads.

Real-Time Wind Field Estimation and Pitot Tube Calibration Using an Extended Kalman Filter

The airspeed is an important feedback signal for flight control, and its measurement accuracy is related to the safety of aircraft, especially for hybrid vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAV) in the transition phase. However, offline calibration of the pitot tube cannot fully simulate the situation in real cases, and this is why online calibration after installation is necessary. In addition, the environmental wind field creates a high risk for the conversion flight of a hybrid UAV, thus real-time wind field measurement of the flight field has great significance for the flight path planning of the conversion process. In this article, an innovative method for online calibration of pitot tube and wind field estimation is proposed. After establishing the extended Kalman filter (EKF) for estimation, an analysis method is proposed to analyze the observability of EKF under different flight strategies. Then, the hovering flight is selected as the experimental flight trajectory. The laboratory computer simulation and flight experiment results validate the theory and prove that the proposed method could re-calibrate the scale factor of the pitot tube and estimate the wind field.

A divergence-free inflow turbulence generator using spectral representation method for large-eddy simulation of ABL flows

The generation of inflow turbulence is the first necessary step to conduct a successful large-eddy simulation (LES) of atmospheric boundary layer (ABL) flows. It is required that the generated inflow turbulence is divergence-free and satisfies essential target statistical properties, including the two-point statistics of the flow described by the coherency function and the spatial correlation. In this paper, a computationally efficient synthetic inflow turbulence generation technique with explicitly defined two-point flow statistics is proposed based on the spectral representation method. The divergence-free condition is imposed on the generated turbulence through a posteriori procedure embedded in the Pressure-Implicit with Splitting of Operators (PISO) solver of OpenFOAM. The efficacy of the proposed method to represent one-point and two-point statistics is demonstrated by comparing the generated turbulence with wind field measurements taken at the Boundary Layer Wind Tunnel Laboratory of Western University. The proposed method is then applied to LES of ABL flows for three exposure conditions, and the wind profiles downstream of the inlet are examined. The mean velocity, turbulence intensity, integral length scale profiles, and the velocity spectra are in good agreement with the target experimental data, thus, indicating the potential of the method for computational wind engineering applications such as wind load evaluation studies. The implementation of the proposed method is available at https://github.com/GBitsuamlak/DFSR.

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

Detection of structures in the horizontal wind field over complex terrain using coplanar Doppler lidar scans

Coplanar scans from three Doppler lidars are used to retrieve the horizontal wind field in a horizontal plane of about 5 km × 5 km in size above the city of Stuttgart in south-western Germany. Stuttgart is located in moderate mountainous terrain that is characterized by a basin-shaped valley (Stuttgart basin) which opens into the larger Neckar Valley. Using the retrieved horizontal wind field, which is available on 22 days with a temporal resolution of 1 min and a horizontal resolution of 100 m, we investigate the mesoscale structure of the horizontal flow in the valleys with respect to time of the day, stratification and wind above the mean ridge height, and determine how fast the cells in the convective boundary layer move downstream, i.e. we estimate the convection velocity. The measurements reveal a large spatial and temporal variability of the flow. During stable conditions, the flow below the mean ridge height is decoupled from the flow aloft and downvalley wind dominates in the valleys. At the opening of the Stuttgart basin into the Neckar Valley outflow dominates during nighttime, whereas inflow into the basin prevails in the early morning. During thermally unstable conditions the flow in the valleys is mainly coupled to the flow aloft with a preference for upvalley wind direction. Convective cells moving downstream are detected in the horizontal wind field and a method to estimate the convection velocity from the horizontal wind field measurements is presented. The mean convection velocity is found to be higher by 24 % than the mean horizontal wind speed at the same height and about similar to the wind speed 100 m further up.

Spatiotemporal distribution of traffic emission based on wind tunnel experiment and computational fluid dynamics (CFD) simulation

With the increasing urbanization and motorization, transportation has become one of the primary sources of carbon emission and air pollution, causing serious diseases to city residents. This study focuses on assessing pollutant dispersion patterns under multi-scenario situations and verifying the effectiveness of computational fluid dynamics (CFD) numerical simulation model using wind tunnel experiments and field measurements. A single-vehicle model was built to obtain the spatiotemporal distribution of Carbon Monoxide (CO) concentrations around the vehicle. Pressure coefficients of monitoring points were measured to compare with the values from the wind tunnel test. Then, numerical simulations were extended to car-following platoon and empirical street canyon scenarios. On-site measurements were carried out to ensure that the CFD model reflects the actual flow field around a vehicle in a certain precision range for given experimental design. The results indicated that the traffic-related pollutants were concentrated in the semicircle with the exhaust pipe as the center, with a radius of 1.5 m behind the vehicle. The podium building structure in the street perpendicular to the prevailing wind direction tends to induce the deposition of pollutants at the corner and bottom of the podium. Exhaust concentration at the right-angle area of a podium building on the leeward side of the wind direction is 221.1% higher than that in the windward side. Findings of this study may shed light on the street architecture design and the future applications of CFD model to estimate pollutant concentration along urban street canyons, thus to eventually improve urban environmental sustainability.

Automation and New Capabilities in the University of Florida NHERI Boundary Layer Wind Tunnel

The Natural Hazards Engineering Research Infrastructure (NHERI) experimental facility at the University of Florida provides a diverse suite of experimental resources to support wind hazard research. The 40-m long Boundary Layer Wind Tunnel (BLWT) simulates boundary layer flows to characterize wind loading on rigid structural models and assess the response of aeroelastic structures. The use of experimental automation tools provides researchers unparalleled flexibility in their test configurations while supporting high throughput testing and data collection. The Terraformer, an array of 1116 roughness elements, can be rapidly reconfigured to generate terrain conditions in less than 90 seconds, the test section turntable can move automatically through a range of wind approach angles, and the instrumentation gantry can traverse preset paths to collect wind field measurements anywhere in the tunnel cross-section. These test automation tools, along with mechatronic structural models and real-time data transfer and processing, provide new opportunities in experimental wind tunnel testing. Recent cyber-physical wind tunnel testing projects highlight the benefits of these experimental automation tools. This paper will also discuss the most recent addition to the BLWT, the Flow Field Modulator (FFM). It consists of a 2D array of 319 individually controlled ducted fans driven by electronic speed controllers. The FFM expands the BLWT capabilities by supporting the simulation of non-monotonic profiles and nonstationary events such as gust fronts and downbursts, where mean velocity and turbulence distributions change over short spatial scales. The ability to simulate these flow conditions in a wind tunnel enables the investigation of a wide range of damaging conditions and the solutions for mitigating their impact on structures.

NOx Emission Flux Measurements with Multiple Mobile-DOAS Instruments in Beijing

NOX (NOX = NO + NO2) emissions measurements in Beijing are of great significance because they can aid in understanding how NOX pollution develops in mega-cities throughout China. However, NOX emissions in mega-cities are difficult to measure due to changes in wind patterns and moving sources on roads during measurement. To obtain good spatial coverage on different ring roads in Beijing over a short amount of time, two mobile differential optical absorption spectroscopy (DOAS) instruments were used to measure NOX emission flux from April 18th to 26th, 2018. In addition, a wind profile radar provided simultaneous wind field measurements for altitudes between 50 m and 1 km for each ring road measurement. We first determined NOX emission flux of different ring roads using wind field averages from measured wind data. The results showed that the NOX emission flux of Beijing’s fifth ring road, which represented the urban part, varied from (19.29 ± 5.26) × 1024 molec./s to (36.46 ± 12.86) × 1024 molec./s. On April 20th, NOX emission flux for the third ring was slightly higher than the fourth ring because the two ring roads were measured at different time periods. We then analyzed the NOX emission flux error budget and error sensitivity. The main error source was the wind field uncertainty. For some measurements, the main emission flux error source was either wind speed uncertainty or wind direction uncertainty, but not both. As Beijing’s NOX emissions came from road vehicle exhaust, we found that emission flux error had a more diverse sensitivity to wind direction uncertainty, which improved our knowledge on this topic. The NOX emission flux error sensitivity study indicated that more accurate measurements of the wind field are crucial for effective NOX emission flux measurements in Chinese mega-cities. Obtaining actual time and high resolved wind measurements is an advantage for mega-cities’ NOX emission flux measurements. The emission flux errors caused by wind direction and wind speed uncertainties were clearly distinguished. Other sensitivity studies indicated that NOX/NO2 ratio uncertainty dominated flux errors when the NOX/NO2 ratio uncertainty was >0.4. Using two mobile-DOAS and wind profile radars to measure NOx emission flux improved the quality of the emission flux measuring results. This approach could be applied to many other mega-cities in China and in others countries.

Study on turbidity prediction method of reservoirs based on long short term memory neural network

Turbidity is one of the important indicators in water quality management of reservoir. There are many factors affecting turbidity, and its time series is non-linear, making prediction difficult. Therefore, it is necessary to carry out research on reservoir turbidity prediction methods. In this study, the Long Short-Term Memory (LSTM) neural network was identified, validated and tested for the computation of turbidity in the Qingcaosha Reservoir. The model employed historical data of turbidity, water level, wind direction and wind speed over a period of 2 years at various monitoring points. Within 40 iterations of the model, the mean square error converged to less than 0.05 steadily, and the Nash efficiency coefficient of the 24 h prediction was above 0.5. It showed that the model has the characteristics of fast convergence, high stability, and accurate prediction, which meant this model can be well applied to prediction of reservoir turbidity. This study also tried to use the forecasted wind field data to improve the actual turbidity prediction of the reservoir. The results showed that the accuracy is slightly lower than the predicted result using the measured wind field data, but it was significantly higher than the prediction result using the extended wind field data at the previous time point. Therefore, using forecasted wind field data can effectively improve the accuracy of the actual reservoir turbidity forecast. The results of this study indicate that the LSTM neural network model is fast, stable, and highly accurate, indicating that it is suitable for prediction of turbidity in reservoirs and can provide support for water quality management of reservoirs.

A remote long-term and high-frequency wind measurement system: design, comparison and field testing

The wind field measurement of severe winds such as hurricanes (or typhoons), thunderstorm downbursts and other gales is important issue in wind engineering community, both for the construction and health monitoring of the wind-sensitive structures. Although several wireless data transmission systems have been available for the wind field measurement, most of them are not specially designed for the wind data measurement in structural wind engineering. Therefore, the field collection is still dominant in the field of structural wind engineering at present, especially for the measurement of the long-term and highfrequency wind speed data. In this study, for remote wind field measurement, a novel wireless long-term and high-frequency wind data acquisition system with the functions such as remote control and data compression is developed. The system structure and the collector are firstly presented. Subsequently, main functions of the collector are introduced. Also novel functions of the system and the comparison with existing systems are presented. Furthermore, the performance of this system is evaluated. In addition to as the wireless transmission for wind data and hardware integration for the collector, the developed system possesses a few novel features, such as the modification of wind data collection parameters by the remote control, the remarkable data compression before the data wireless transmission and monitoring the data collection by the cell phone application. It can be expected that this system would have wide applications in wind, meteorological and other communities.

Net CO<sub>2</sub> fossil fuel emissions of Tokyo estimated directly from measurements of the Tsukuba TCCON site and radiosondes

Abstract. We present a simple statistical approach for estimating the greenhouse gas emissions of large cities using accurate long-term data of column-averaged greenhouse gas abundances collected by a nearby FTIR (Fourier transform infrared) spectrometer. This approach is then used to estimate carbon dioxide emissions from Tokyo. FTIR measurements by the Total Carbon Column Observing Network (TCCON) derive gas abundances by quantitative spectral analysis of molecular absorption bands observed in near-infrared solar absorption spectra. Consequently these measurements only include daytime data. The emissions of Tokyo are derived by binning measurements according to wind direction and subtracting measurements of wind fields from outside the Tokyo area from measurements of wind fields from inside the Tokyo area. We estimate the average yearly carbon dioxide emissions from the area of Tokyo to be 70±21±6MtCyr-1 between 2011 and 2016, calculated using only measurements from the TCCON site in Tsukuba (north-east of Tokyo) and wind-speed data from nearby radiosondes at Tateno. The uncertainties are estimated from the distribution of values and uncertainties of parameters (±21) and from the differences between fitting residuals with polynomials or with sines and cosines (±6). Our estimates are a factor of 1.7 higher than estimates using the Open-Data Inventory for Anthropogenic Carbon dioxide emission inventory (ODIAC), but when results are scaled by the expected daily cycle of emissions, measurements simulated from ODIAC data are within the uncertainty of our results. The goal of this study is not to calculate the best possible estimate of CO2 emissions but to describe a simple method which can be replicated easily and uses only observation data.

Nebkha alignments and their implications for shadow dune elongation under unimodal wind regime

Compared with longer-crested linear dunes formed in the bimodal wind regime, little is known about the driving forces of linear dunes that elongate in the lee side of obstacles under a unimodal wind regime. Here, we present the flow dynamics and sand deposition patterns around the aligned nebkhas with different spacing distances (∆) based on computational fluid dynamics (CFD) simulation, wind tunnel experiment and field measurement. In terms of the relationships between the width of horseshoe vortex around two laterally aligned nebkhas (T1 and T2, respectively) and ∆, four wake flow patterns were identified: distinctly merged wake flow when ∆ → 0, merging flow when 0 < ∆ < T1 + T2, two isolated and weakly interfered flows when 0 ≪ ∆ < T1 + T2, and two independent wake flows when ∆ ≫ T1 + T2. Considered two aligned nebkhas with the same dimension of diameter D, ∆ < 1.5D commonly contributes to the merging and elongation of shadow dunes. We suggest that wake flow interference has been reported to produce a region of enhanced deposition with the minimum wind speed and shear stress, i.e., secondary deposition zone, which is determined by sediment supply and ∆ of nebkha alignments. Spatial distance ∆ between tandem aligned nebkhas strongly controls the morphology of bead-like shadow dunes. It is found that the elongation of shadow dunes in the unimodal winds can be well explained by the deflection flow around sand ridges, thus demonstrating the driving forces for the elongation of unimodal-wind-subjected shadow dunes.

Measurement and Prediction of Wind Fields at an Offshore Site by Scanning Doppler LiDAR and WRF

LiDAR-based wind speed measurements have seen a significant increase in interest in wind energy. However, reconstruction of wind speed vector from a LiDAR-measured radial wind speed is still a challenge. Furthermore, for extensive application of LiDAR technology, it can be used as a means to validate simulation and analytical models. To that end, this study employed scanning Doppler LiDAR for assessment of wind fields at an offshore site and compared Weather Research and Forecasting (WRF)-based mesoscale simulations and several wake models with the measurements. Firstly, the effect of carrier-to-noise-ratio (CNR) and data availability on the quality of scanning LiDAR measurements was evaluated. Analysis of vertical profiles show that the average wind speed is higher for wind blowing from the sea than that blowing from the land. Furthermore, profiles obtained from the WRF simulation also show a similar tendency in the LiDAR measurements in general, though it overestimates the wind speeds at higher altitudes. A method for reconstruction of wind fields from plan-position indicator (PPI) and range height indicator (RHI) scans of LiDAR-measured line of sight velocities was then proposed and first used to investigate the effect of coastal terrain. An internal boundary layer with strong shear could be observed to develop from the coastline. Finally, the flow field around wind turbine was measured using PPI scan and used to validate wake models.

Design of thermal wind sensor with constant power control and wind vector measurement method.

This paper presents a conceptual wind vector detector for measuring the velocity and direction of wind in enclosed or semi-enclosed large spaces. Firstly, a thermal wind sensor with constant power control was manufactured and then used as a wind velocity sensing unit. Secondly, a sensor bracket equipped with three thermal wind sensors was designed, the fluid dynamic response regularity of the measured wind field to the sensor bracket was analyzed using ANSYS Fluent CFD software, and then its structural parameters were optimized to improve measurement accuracy. The sensor bracket was fabricated via 3D printing. Finally, a unique wind vector measurement method was developed for the wind vector detector. Experimental results showed that the measured velocity range of the thermal wind sensor satisfied the requirements of being within 0–15 m/s with an accuracy of ±0.3 m/s, and the wind direction angle range of the wind vector detector was within 0–360° with an accuracy of ±5°. By changing the applied power control value of the thermal wind sensor and structural parameters of the sensor bracket, the measurement range and accuracy of the wind vector detector can be adjusted to suit different applications.

Development of a Building-Scale Meteorological Prediction System Including a Realistic Surface Heating

Microscale urban meteorological models have been widely used in interpreting atmospheric flow and thermal discomfort in urban environments, but most previous studies examined the urban flow and thermal environments for an idealized urban morphology with imposing neutral or homogeneous thermal forcing. This study has developed a new building-scale meteorological prediction system that extends the ability to predict microscale meteorological fields in real urban environments. A computational fluid dynamics (CFD) model has been developed based on the non-hydrostatic incompressible Reynolds-averaged Navier-Stokes (RANS) equations with a standard k-ε turbulence model, and the microscale urban surface energy (MUSE) model was coupled with the CFD model to provide realistic surface thermal boundary conditions in real urban environments. It is driven by the large scale wind and temperature fields predicted by the Korean operational weather prediction model. The validation results of the new building-scale meteorological prediction system were presented against wind tunnel data and field measurements, showing its ability to predict in-canyon flows and thermal environments in association with spatiotemporal variations of surface temperatures in real urban environments. The effects of realistic surface heating on pedestrian level wind and thermal environments have been investigated through sensitivity simulations of different surface heating conditions in the highly built-up urban area. The results implied that the inclusion of surface thermal forcing is important in interpreting urban flow and thermal environment of the urban area, highlighting a realistic urban surface heating that should be considered in predicting building-scale meteorology over real urban environments.

A Hybrid Prediction Model for Damage Warning of Power Transmission Line Under Typhoon Disaster

To bolster the resilience of power systems against typhoon disasters, this paper develops a holistic framework of wind disaster warning for transmission lines. This paper proposes a hybrid prediction model to quantify the transmission line damage probability under typhoon disaster based on extreme value type I probability distribution, Monte Carlo method, and Random Forest. Specifically, this paper uses the extreme value type I probability distribution and the Monte Carlo method to simulate the random wind field, and predict the damage probability of transmission lines under each wind field using the Random Forest method. This paper takes typhoon “Mangkhut” in 2018 as a case study, and compare the performance of the hybrid model based on random wind field with the Random Forest method under predicted and measured wind field. The results demonstrate that the hybrid model can effectively utilize wind speed data to obtain a more reliable prediction and achieves the best synthetic similarity to the actual damage situations.

Research on Wind Field Characteristics along Power Transmission Lines Based on Full-scale Measured Data in High-altitude and Strong Wind Regions

High-altitude regions are featured by complicated geographical environment, in which strong wind events occurs frequently. At present, the engineering meteorological data of relevant projects are limited. Moreover, the rationality of determination methods of design wind loads for power transmission lines in the high-altitude regions is still unclear, which severely threatens the safety of power transmission lines. Therefore, this paper focuses on actual full-scale measurements of wind fields along power transmission lines in the high-altitude strong wind regions. The average wind speed and turbulence intensity characteristics under the typical high-altitude terrains terrain are analysed. Through the profile fitting of power law profile and the analysis on probability of actually measured data, the value scopes of parameters, such as profile index, are obtained. Through comparing with existing Chinese codes, some theoretical reference and basis for the wind-resisting design and maintenance of power transmission lines in relevant regions are suggested.