Wind Lidar Research Articles

Evaluation of Vertical Profiles and Atmospheric Boundary Layer Structure Using the Regional Climate Model CCLM during MOSAiC

Regional climate models are a valuable tool for the study of the climate processes and climate change in polar regions, but the performance of the models has to be evaluated using experimental data. The regional climate model CCLM was used for simulations for the MOSAiC period with a horizontal resolution of 14 km (whole Arctic). CCLM was used in a forecast mode (nested in ERA5) and used a thermodynamic sea ice model. Sea ice concentration was taken from AMSR2 data (C15 run) and from a high-resolution data set (1 km) derived from MODIS data (C15MOD0 run). The model was evaluated using radiosonde data and data of different profiling systems with a focus on the winter period (November–April). The comparison with radiosonde data showed very good agreement for temperature, humidity, and wind. A cold bias was present in the ABL for November and December, which was smaller for the C15MOD0 run. In contrast, there was a warm bias for lower levels in March and April, which was smaller for the C15 run. The effects of different sea ice parameterizations were limited to heights below 300 m. High-resolution lidar and radar wind profiles as well as temperature and integrated water vapor (IWV) data from microwave radiometers were used for the comparison with CCLM for case studies, which included low-level jets. LIDAR wind profiles have many gaps, but represent a valuable data set for model evaluation. Comparisons with IWV and temperature data of microwave radiometers show very good agreement.

Quantification and correction of motion influence for nacelle-based lidar systems on floating wind turbines

Abstract. Inflow wind field measurements from nacelle-based lidar systems offer great potential for different applications including turbine control, load validation, and power performance measurements. On floating wind turbines nacelle-based lidar measurements are affected by the dynamic behavior of the floating foundations. Therefore, the effects on lidar wind speed measurements induced by floater dynamics must be understood. In this work, we investigate the influence of floater motions on wind speed measurements from forward-looking nacelle-based lidar systems mounted on floating offshore wind turbines (FOWTs) and suggest approaches for correcting motion-induced effects. We use an analytical model, employing the guide for the expression of uncertainty in measurements (GUM) methodology and a numerical lidar simulation for the quantification of uncertainties. It is found that the uncertainty of lidar wind speed estimates is mainly caused by the fore–aft motion of the lidar, resulting from the pitch displacement of the floater. Therefore, the uncertainty is heavily dependent on the amplitude and the frequency of the pitch motion. The bias of 10 min mean wind speed estimates is mainly influenced by the mean pitch angle of the floater and the pitch amplitude. We correct motion-induced biases in time-averaged lidar wind speed measurements with a model-based approach, employing the developed analytical model for uncertainty and bias quantification. Testing of the approach with simulated dynamics from two different FOWT concepts shows good results with remaining mean errors below 0.1 m s−1. For the correction of motion-induced fluctuation in instantaneous measurements, we use a frequency filter to correct fluctuations caused by floater pitch motions for instantaneous measurements. The correction approach's performance depends on the pitch period and amplitude of the FOWT design.

АЛГОРИТМ ОБНАРУЖЕНИЯ СДВИГА ВЕТРА НА МАЛЫХ ВЫСОТАХ НА ОСНОВЕ ЛИДАРНЫХ ДАННЫХ И АППРОКСИМАЦИИ МЕТОДОМ НАИМЕНЬШИХ КВАДРАТОВ

In order to detect the low-level wind shear at different scales accurately and efficiently, a lidar low-level wind shear warning algorithm is proposed based on least square fitting. First, the extracted reconstructed headwind profile is extended, and the least square curve fitting (polynomial fitting) is performed by using the extended data. Secondly, to get the slope of each segment of data, the extended part of the reconstructed headwind profile is removed, and the least square linear fitting is performed at the minimum scale by using the results of curve fitting. Thirdly, the optimal value (inflection point) of the reconstructed headwind profile is determined by the opposite signs of adjacent slopes. Finally, the occurrence and intensity of wind shear are determined. The performance of the algorithm is evaluated with simulation and observation experiments.

Characteristics of Coastal Low-Level Jets in the Boundary Layer of the Pearl River Estuary

It is well-known that coastal low-level jets (CLLJs) play an essential role in transporting heat, water vapor and pollutants. However, the CLLJ characteristics in the Pearl River Estuary have not been deeply revealed due to the lack of long-term observations. Based on the long-term observations from a wind lidar, we analyze the primary climatic characteristics of the CLLJs in the Pearl River Estuary and investigate their relationships with large-scale and local-scale synoptic systems. The results show that the CLLJs mainly appear during the flood season, with the most occurrence in May. The CLLJ occurrence during the flood season is mainly influenced by the large-scale north–south pressure gradient driven by the western Pacific subtropical high and terrestrial low-pressure systems. The occurrence of the CLLJs exhibits a distinct diurnal cycle with two different peaks in different seasons. One peak appears at nighttime, mainly during non-flood seasons. The other appears in the afternoon, mainly during the flood season. In the non-flood seasons, under the influence of cold air, the inertial oscillations triggered by the land–sea thermal contrast lead to CLLJ onset at nighttime in the Pearl River Estuary. During the flood season, the strong near-surface pressure gradient contributes to CLLJ onset in the afternoon, while the topography (blocking and passing) is more conducive to the occurrence of the CLLJs in the Pearl River Estuary. These findings reveal the formation mechanisms of the CLLJs over the Pearl River Estuary, thus providing a basis for further understanding the precipitation in the Pearl River Estuary and the occurrence of the CLLJs in other coastal areas with complex mountain ranges.

High-Spatial-Resolution Coherent Doppler Lidar With Pseudo-Random Phase-Shift Keying

A high-spatial-resolution coherent Doppler wind lidar (CDWL) incorporating pseudo-random phase-shift keying (PR-PSK) modulation is proposed and demonstrated. The pseudo-random phase coding technique can enhance the spatial resolution without broadening the backscattered spectrum but suffers from the non-instantaneous transition edges caused by the limited bandwidth. In this work, ideal binary PSK modulation is achieved by exploiting the zero crossing of the Mach-Zehnder modulator’s (MZM) transfer function, thus greatly reducing the bandwidth requirement. The amplitude shaping and phase modulation of the pulses are naturally aligned as they are realized together in one MZM. Meanwhile, a real-time bias monitoring scheme for the MZM is proposed to facilitate engineering applications. At laser peak power of 300 W, continuous radial wind profile measurement in 800 m is demonstrated, with spatial/temporal resolution of 3 m/0.5 s.

Atmospheric visibility correlates with photon travel time delay from frequency modulated continuous-wave Doppler wind lidar

ABSTRACT Atmospheric visibility, or meteorological optical range (MOR), is governed by light extinction by aerosols and is linked to air quality and Earth’s climate. A coherent frequency modulated continuous wave (FMCW) Doppler wind lidar has been used to measure the atmospheric roundtrip distance (target distance) in the period 24 March 2022 to 29 March 2022. A visibility sensor measured MOR independently. The independently measured MOR was found to correlate with the lidar roundtrip distance with a R2 value of 0.68. A first-order model explaining the observation is presented. The results are promising and indicate that more extensive research is worthwhile, in particular, a longer measurement time series covering more diverse atmospheric conditions and a dedicated visibility sensor located next to the lidar.

Assessment of turbulence intensity estimates from floating lidar systems

In the pre-construction phase of offshore wind energy projects floating lidar systems (FLS) are used for wind site assessment. Their measurements of mean wind speed and direction have proven to be accurate according to existing standards. But for the assessment of turbulence intensity (TI), a widely-accepted procedure and acceptance criteria are missing. This study investigates different evaluation methods, namely linear regression analysis and the key performance indicators (KPIs) presented by the Consortium for Advancing Remote Sensing (CFARS). The assessment is based on data from an offshore trial of the Fugro SEAWATCH Wind Lidar Buoy (SWLB) against the meteorological mast and a collocated fixed profiling wind lidar at Blyth, UK. The results show that the accuracy of TI estimates from FLS can be evaluated well, when the KPIs mean bias error (MBE) and representative TI error suggested by CFARS are used. We propose best-practice acceptance thresholds of ±1% for MBE and ±1.5% for the representative TI error. The motion-compensation approach of the SWLB works well and after compensation, its TI data are similar to the data from the fixed reference lidar. The impact of lidar-specific effects is minor in the analyzed data set and near-to-zero biases are found for all measurement elevations and wind speed bins in comparison to mast data.

Pseudorandom modulation continuous-wave narrowband sodium temperature and wind lidar

Abstract. We report the first pseudorandom modulation continuous-wave (PMCW) narrowband sodium temperature and wind lidar developed at the University of Science and Technology of China (USTC). The laser system uses a 1178 nm diode seed laser and a fiber Raman amplifier with a fiber-coupled acousto-optic frequency shifter (AOFS) to generate a narrowband 589.158 nm light with an output power of 1.5 W at three frequencies of v0, v+, and v−. Based on an innovative technique and algorithm, the main beam and the residual beam modulated by electro-optic modulator (EOM) with M pseudorandom sequence code (M-code) are separately directed to the vertical and eastward directions. The three-frequency light is designed in timing with the multiple-period 127-bit M-code groups. The uncertainties of the temperature and wind with the vertical and temporal resolutions of 1 km and 30 min under clear-sky conditions are estimated to be 5.0 K and 10 m s−1, respectively, at the sodium peak. The temperature and wind results are in good agreement with those observed by satellite and nearby ground-based meteor radar, demonstrating the reliability of the PMCW narrowband sodium lidar system for measuring the mesopause region's temperature and wind.

Calibration of Mean Wind Profiles Using Wind Lidar Measurements

This paper explores the applicability of Lidar wind measurements for the calibration of mean wind profiles depending on the extension in time and space of the available measurements. Starting from logarithmic wind speed profiles corresponding to different site conditions, pseudo-experimental wind speed profiles are generated artificially by adding a zero-mean Gaussian-distributed noise, representative of realistic measurement errors. Then, a least-square fitting procedure is applied to identify the roughness length and the zero-plane displacement. The results obtained show an increase in the scatter of the estimated parameters of the logarithmic law with increasing elevation of the lowest measurement point. Then, a parametric study is developed to analyse the influence of the number of available experimental profiles on the uncertainty associated with the estimated logarithmic law parameters. Based on the results obtained, it can be pointed out that the availability of measurements at low elevations is essential to identify the logarithmic mean wind profile using a reasonable number of observations.

Evaluating wind profiles in a numerical weather prediction model with Doppler lidar

Abstract. We use Doppler lidar wind profiles from six locations around the globe to evaluate the wind profile forecasts in the boundary layer generated by the operational global Integrated Forecast System (IFS) from the European Centre for Medium-range Weather Forecasts (ECMWF). The six locations selected cover a variety of surfaces with different characteristics (rural, marine, mountainous urban, and coastal urban). We first validated the Doppler lidar observations at four locations by comparison with co-located radiosonde profiles to ensure that the Doppler lidar observations were of sufficient quality. The two observation types agree well, with the mean absolute error (MAE) in wind speed almost always less than 1 m s−1. Large deviations in the wind direction were usually only seen for low wind speeds and are due to the wind direction uncertainty increasing rapidly as the wind speed tends to zero. Time–height composites of the wind evaluation with 1 h resolution were generated, and evaluation of the model winds showed that the IFS model performs best over marine and coastal locations, where the mean absolute wind vector error was usually less than 3 m s−1 at all heights within the boundary layer. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. For example, in Granada, which is near a high mountain range, the IFS model failed to capture a commonly occurring mountain breeze, which is highly dependent on the sub-grid-size terrain features that are not resolved by the model. The uncertainty in the wind forecasts increased with forecast lead time, but no increase in the bias was seen. At one location, we conditionally performed the wind evaluation based on the presence or absence of a low-level jet diagnosed from the Doppler lidar observations. The model was able to reproduce the presence of the low-level jet, but the wind speed maximum was about 2 m s−1 lower than observed. This is attributed to the effective vertical resolution of the model being too coarse to create the strong gradients in wind speed observed. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.

Impact Assessment of Dynamic Loading Induced by the Provision of Frequency Containment Reserve on the Main Bearing Lifetime of a Wind Turbine

The components of an operational wind turbine are continuously impacted by both static and dynamic loads. Regular inspections and maintenance are required to keep these components healthy. The main bearing of a wind turbine is one such component that experiences heavy loading forces during operation. These forces depend on various parameters such as wind speed, operating regime and control actions. When a wind turbine provides frequency containment reserve (FCR) to support the grid frequency, the forces acting upon the main bearing are also expected to exhibit more dynamic variations. These forces have a direct impact on the lifetime of the main bearing. With an increasing trend of wind turbines participating in the frequency ancillary services market, an analysis of these dynamic forces becomes necessary. To this end, this paper assesses the effect of FCR-based control on the main bearing lifetime of the wind turbine. Firstly, a control algorithm is implemented such that the output power of the wind turbine is regulated as a function of grid frequency and the amount of FCR. Simulations are performed for a range of FCR to study the changing behaviour of dynamical forces acting on the main bearing with respect to the amount of FCR provided. Then, based on the outputs from these simulations and using 2 years of LiDAR wind data, the lifetime of the main bearing of the wind turbine is calculated and compared for each of the cases. Finally, based on the results obtained from this study, the impact of FCR provision on the main bearing lifetime is quantified and recommendations are made, that could be taken into account in the operation strategy of a wind farm.

Aircraft Wake Recognition Based on Improved ParNet Convolutional Neural Network

The occurrence of wake can pose a threat to the flight safety of aircraft and affect the runway capacity and airport operation efficiency. To effectively identify aircraft wake, this paper proposes a novel convolutional neural network (CNN) method of aircraft wake recognition based on the improved parallel network (ParNet). Depthwise separable convolution (DSC) was introduced into the ParNet to make the wake recognition model lightweight. In addition, the convolutional block attention module (CBAM) was introduced into the wake recognition model to improve the capacity of the model to extract the spatial features of the wind field. The proposed aircraft wake recognition method was used to identify the aircraft wake based on the lidar wind field scanning image of Hong Kong International Airport. The best wake recognition effect was obtained with a recognition accuracy of 98.91% and an F1 value of 98.90%. As the number of parameters of the model was only 0.46 M, the aircraft wake could be identified on an ordinary computer. Thus, the proposed method can effectively identify aircraft wake.

Ground-Based Measurements of Wind and Turbulence at Bucharest–Măgurele: First Results

Doppler wind lidar measurements were used for the first time in Romania to analyse the wind and turbulence statistics for a peri-urban site located at Măgurele, southwest of Bucharest. Vertical and scanning measurements between December 2019 and November 2021 were processed using an existing toolbox. The statistics over the two-year period were performed on seasonal and diurnal cycle bases. The analyses showed a diurnal cycle for the horizontal wind speed, with lower values during daytime. In the upper part of the planetary boundary layer (PBL), the wind speed is lowest during the day and highest at night (near surface, the behaviour is reversed). The diurnal cycle has variations during the year (from approximately 500 m during midnight winter to approximately 1250 m during summer noon). The wind direction during autumn shows similarities with the summer season, with prevailing directions from east and northeast. The winter season is characterised by westerly winds. The most variable diurnal wind direction is observed during summer, with nighttime westerly winds and changing directions (from northeast to west) during daytime. The ERA5 reanalysis shows similar patterns for wind speed with Doppler wind lidar (slightly underestimated) and direction. The planetary boundary layer classes over the altitude region analysed shows the predominant convection during daytime and non-turbulent behaviour during nighttime. To a lesser extent, the intermittent turbulent class is observed during the growth and the decay of the mixing layer.

A Unified Formulation for the Computation of the Six-Degrees-of-Freedom-Motion-Induced Errors in Floating Doppler Wind LiDARs

This work presents an analytical formulation to assess the six-degrees-of-freedom-motion-induced error in floating Doppler wind LiDARs (FDWLs). The error products derive from the horizontal wind speed bias and apparent turbulence intensity. Departing from a geometrical formulation of the FDWL attitude and of the LiDAR retrieval algorithm, the contributions of the rotational and translational motion to the FDWL-measured total error are computed. Central to this process is the interpretation of the velocity–azimuth display retrieval algorithm in terms of a first-order Fourier series. The obtained 6 DoF formulation is validated numerically by means of a floating LiDAR motion simulator and experimentally in nearshore and open-sea scenarios in the framework of the Pont del Petroli and IJmuiden campaigns, respectively. Both measurement campaigns involved a fixed and a floating ZephIRTM 300 LiDAR. The proposed formulation proved capable of estimating the motion-induced FDWL horizontal wind speed bias and returned similar percentiles when comparing the FDWL with the fixed LiDAR. The estimations of the turbulence intensity increment statistically matched the FDWL measurements under all motional and wind scenarios when clustering the data as a function of the buoy’s mean tilt amplitude, mean translational-velocity amplitude, and mean horizontal wind speed.

Airborne coherent wind lidar measurements of the momentum flux profile from orographically induced gravity waves

Abstract. In the course of the GW-LCYCLE II campaign, conducted in Jan/Feb 2016 from Kiruna, Sweden, coherent Doppler wind lidar (2 µm DWL) measurements were performed from the DLR Falcon aircraft to investigate gravity waves induced by flow across the Scandinavian Alps. During a mountain wave event on 28 January 2016, a novel momentum flux (MF) scan pattern with fore and aft propagating laser beams was applied to the 2 µm DWL. This allows us to measure the vertical wind and the horizontal wind along the flight track simultaneously with a high horizontal resolution of ≈800 m and hence enables us to derive the horizontal MF profile for a broad wavelength spectrum from a few hundred meters to several hundred kilometers. The functionality of this method and the corresponding retrieval algorithm is validated using a comparison against in situ wind data measured by the High Altitude and Long Range (HALO) aircraft which was also deployed in Kiruna for the POLSTRACC (Polar Stratosphere in a Changing Climate) campaign. Based on that, the systematic and random error of the wind speeds retrieved from the 2 µm DWL observations are determined. Further, the measurements performed on that day are used to reveal significant changes in the horizontal wavelengths of the vertical wind speed and of the leg-averaged momentum fluxes in the tropopause inversion layer (TIL) region, which are likely to be induced by interfacial waves as recently presented by Gisinger et al. (2020).

A new Gaussian analytical wake model validated by wind tunnel experiment and LiDAR field measurements under different turbulent flow

Wind turbine wake has a great effect on wind power generation and fatigue loads of downstream wind turbines in wind farms. Analytical engineering wake model is adopted to evaluate the power loss caused by turbine wake for the optimization of wind farm layout. Gaussian distribution is often employed in wake model. Traditional Gaussian distributions, on the other hand, are unable to accurately describe wind speed especially near the wake boundary. Besides, the variable turbulent environment in wind farms with complex terrain poses a challenge to the turbine wake model. In this paper, the unfitness of the Gaussian wake model especially near the wake boundary is addressed and a Gaussian wake model with new turbulence intensity model is proposed. Compared with previous models, this new wake model has a more suitable wind speed distribution. The new wake model is then validated using wind tunnel measurements under different turbulence intensity. Results indicate that the new Gaussian wake model can more correctly predict the wind turbine wake than the previous Gaussian wake models. The new Gaussian wake model suitable shows a good application prospect in wind farm layout optimization which improves the power generation and reduces the power generation costs.

Wind profiles measurements and predictions for atmospheric acoustic propagation modeling

This work presents a comprehensive experimental system to measure meteorological conditions with both anemometers and a three-dimensional scanning Doppler LIDAR wind profiler. The LIDAR system captures real-time wind speed gradients at many locations along a particular heading. This work describes a method for extracting a cartesian grid of wind speeds gradients from a range height indicator (RHI) scan pattern. The LIDAR derived wind profiles are compared to logarithmic wind profiles based on single point traditional anemometer measurements. Differences in wind speed profiles observed using the two methods are presented and the implications on long range acoustic propagation modeling are discussed.

Atmospheric acoustic propagation modeling using heterogeneous wind profiles along the acoustic path

This work presents atmospheric sound propagation predictions using a parabolic equation solver that accounts for heterogeneous wind profile distribution along the acoustic path. Transmission loss predictions using both homogeneous and heterogeneous wind speeds information are compared with data. A three-dimensional scanning Doppler LIDAR wind profiler captures real-time wind speed gradients at many locations along the acoustic propagation path providing the heterogeneous wind speed profiles. The wind measurements are concurrent with a pitch catch transmission loss measurements. A long-range acoustic device on an anchored pontoon sends known chirp sequences to a seven-channel receiver array at the water’s edge at ranges up to approximately one kilometer. Additional synchronized meteorological observations include temperature, humidity, and wind measured with anemometers. Key differences in model results are highlighted and an assessment of the value of the computational cost is presented.

Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at Réunion island and the Observatoire de Haute-Provence

Abstract. The European Space Agency's (ESA) Aeolus satellite mission is the first Doppler wind lidar in space, operating in orbit for more than 4 years since August 2018 and providing global wind profiling throughout the entire troposphere and the lower stratosphere. The Observatoire de Haute-Provence (OHP) in southern France and the Observatoire de Physique de l'Atmosphère de La Réunion (OPAR) are equipped with ground-based Doppler Rayleigh–Mie lidars, which operate on similar principles to the Aeolus lidar and are among essential instruments within the ESA Aeolus calibration and validation (cal/val) program. This study presents the validation results of the L2B Rayleigh clear horizontal line-of-sight (HLOS) winds from September 2018 to January 2022. The point-by-point validation exercise relies on a series of validation campaigns at both observatories: AboVE (Aeolus Validation Experiment), held in September 2019 and June 2021 at OPAR and in January 2019 and December 2021 at OHP. The campaigns involved time-coordinated lidar acquisitions and radiosonde ascents collocated with the nearest Aeolus overpasses. During AboVE-2, Aeolus was operated in a campaign mode with an extended range bin setting allowing inter-comparisons up to 28.7 km. We show that this setting suffers from larger random error in the uppermost bins, exceeding the estimated error, due to lack of backscatter at high altitudes. To evaluate the long-term evolution in Aeolus wind product quality, twice-daily routine Météo-France radiosondes and regular lidar observations were used at both sites. This study evaluates the long-term evolution of the satellite performance along with punctual collocation analyses. On average, we find a systematic error (bias) of −0.92 and −0.79 m s−1 and a random error (scaled MAD) of 6.49 and 5.37 m s−1 for lidar and radiosondes, respectively.

Sub-meter wind detection with pulsed coherent Doppler lidar

High-resolution wind detection plays a crucial role in aviation safety and aerodynamics. In this work, the fine wind field within 700 meters is continuously detected at a resolution of 0.9 meters/0.5 seconds by a coherent Doppler wind LiDAR. A meter-scale perturbation by an electric fan is remotely sensed, and atmospheric turbulence with length scale down to 3 meters can be observed.