Coherent Doppler Wind Lidar Research Articles

A Probability-Constraint-Based Method based on the Honey Badger algorithm for wind estimation with coherent Doppler wind lidar

A Probability-Constraint-Based Method based on the Honey Badger algorithm for wind estimation with coherent Doppler wind lidar

Research on optimizing the optical local-oscillator power of Coherent Doppler LiDAR to enhance wind velocity measurements

Due to weak echo signals that become progressively overwhelmed by noise, measurement accuracy and effective detection range of the Coherent Doppler wind LiDAR (CDL) are often compromised. While increasing the optical local-oscillator power (OLP) can amplify the echo signal, it is constrained by the nonlinear effects of the detector. This paper introduces a method for optimizing the OLP in CDL systems. Theoretical analysis has been proposed to explore the amplification effect of OLP on echo signals, and the nonlinear effects of detectors have been studied. Simulations are performed to explore the influence of varying OLP on the signal-to-noise ratio (SNR) across different detector α (quadratic nonlinear coefficient) values. The spectral analysis method is used to directly compute the SNR of actual atmospheric wind field signals under various OLP settings. Results demonstrate consistency between calculated and simulated values, enabling determination of optimal OLP and the detector α values from fitted curves. Comparative experiments confirm significant enhancement in effective detection range (> 1.5 km) with ± 0.5 m/s accuracy. The innovation of this study lies in combining the OLP optimization method with real atmospheric wind field echo signal experiments. It addresses the challenges of directly measuring the nonlinear parameters of the detector and determining the optimal OLP. This study offers valuable theoretical and experimental insights for enhancing the wind measurement performance of CDL.

Demonstration and optimization of coherent Doppler wind LiDAR with low sampling resolution

A low sampling resolution scheme for coherent Doppler wind LiDAR (CDWL) is proposed. The CDWL offers advantages in precision and detection resolution but suffers from the requirement of high-speed data acquisition (DAQ) with high sampling resolution, such as 12- or 14-bit, which leads to an increase of the computational complexity and the system cost. The use of a DAQ system with lower sampling resolution can provide a solution to mitigate this problem. The feasibility of the proposed scheme is validated by simulations and experiments. The detection performance can be greatly affected by the quantization interval selected during sampling. It is shown that the optimal quantization interval exists and only depends on the carrier-to-noise ratio (CNR), and the optimal quantization intervals of several sampling resolutions are given at different CNRs. With the given optimal quantization configuration, the low sampling resolution data can be used for reliable wind field measurements. For long-distance detection with a CNR lower than −13dB, the CNR deterioration of 1-bit, 2-bit, 3-bit, and 4-bit signals can be as low as 2, 0.5, 0.2, and 0.1 dB.

Comparison and Verification of Coherent Doppler Wind Lidar and Radiosonde Data in the Beijing Urban Area

Comparison and Verification of Coherent Doppler Wind Lidar and Radiosonde Data in the Beijing Urban Area

Study on Daytime Atmospheric Mixing Layer Height Based on 2-Year Coherent Doppler Wind Lidar Observations at the Southern Edge of the Taklimakan Desert

Study on Daytime Atmospheric Mixing Layer Height Based on 2-Year Coherent Doppler Wind Lidar Observations at the Southern Edge of the Taklimakan Desert

Profiling of particulate matter transport flux based on dual-wavelength lidar and ensemble learning algorithm.

Transport flux (TF) is a significant particulate matter (PM) characteristic. This paper introduces an advanced dual-wavelength polarization aerosol and wind lidar (Wind Flux 3000) capable of independently observing the PM TF. The PM TF observation capability, which allows for simultaneous aerosol and wind measurements, was achieved by integrating a Mie-polarization particle lidar module and a coherent Doppler wind lidar module into a single lidar system. The primary measurement products of the Wind Flux 3000 include particulate extinction coefficient at 532 nm and 1550 nm, volume linear depolarization ratio at 532 nm (δp,532), wind speed (WS), wind direction (WD), vertical speed (VS), turbulence intensity (TI) and mixing layer height (MLH), retrieved by physical and proven algorithms. The PM concentration scales with the measured optical parameters and is also impacted by other environmental or meteorological parameters. Under the framework of the potential relationship between the PM concentration and the above parameters, the PM2.5 and PM10 concentration retrieval models were established using the stacking method of the ensemble learning technique; the models were trained using the in-situ data as true values, while the signal-to-noise ratio (SNR) at 1550 nm, δp,532, WS, WD, VS, the standard deviation of VS, TI, MLH provided by the Wind Flux 3000, as well as the relative humidity and temperature from ERA5, the hours of the day, and a "dust day" flag were used as inputs. The R2, RMSE, and MAE for the comparison between the predicted and true values of the PM2.5 test set are 0.857, 13.52 µg · m- 3, 9.16 µg · m- 3, and those of the PM10 test set are 0.926, 24.75 µg · m- 3, 14.39 µg · m- 3, respectively. The performance of the PM2.5 and PM10 concentration retrieval ensemble models is better than that of individual machine learning algorithms and better than that of the linear model. On 15th March 2023, a strong southeastward dust transport process with dust plume deposition was observed at Qingdao by the Wind Flux 3000. The analyses of the dust event demonstrated the Wind Flux 3000's ability to evaluate the transports of PM quantitatively.

Beam swinging coherent Doppler wind lidar utilizing wavelength switching through a single telescope.

We have developed a new, to the best of our knowledge, beam swinging coherent Doppler wind lidar (BS-CDWL) by employing a wavelength switching method using mass-produced components for wavelength division multiplexing (WDM) optical communication systems. This BS-CDWL also has a single and position-to-angle conversion telescope for multiple LOS measurement which contributes to cost-effectiveness. Preliminary wind sensing result is shown with measurable range of up to 350 m.

Observation and study of consecutive dust storms in the Taklimakan desert from March 16 to 27, 2022, using reanalysis models and lidar

A series of severe dust storms hit the Taklimakan desert between March 16 and 27, 2022, significantly deteriorating air quality throughout China. This study presents a comprehensive analysis of the vertical structure of aerosols during these dust storms, as well as their causes and impacts on China's regional and city-scale air quality, utilizing data from reanalysis models, coherent Doppler wind lidar, and air quality monitoring stations. During dust storms, intense wind layers increase dust emissions, resulting in reduced lidar detection ranges and signal strengths. In addition, lower temperatures prevail due to sunlight absorption and scattering. Moreover, high-speed winds at high altitudes increase dust particles that serve as cloud condensation nuclei, leading to increased humidity, decreased temperature, and precipitation. The Taklimakan desert's trough serves as a wind convergence zone, which promotes favorable conditions for the initiation of dust storms. Due to the steep pressure gradients, strong winds enter the Taklimakan desert through the gap between its mountains in the east, coming from northern Xinjiang and Inner Mongolia via the Hexi corridor, which facilitates the lifting and transport of dust aerosols. Dust is transported long distances from the Taklimakan desert to the eastern coasts, impacting numerous cities along the way. The emissions from these dust storms swept across most Chinese provinces. Even though each dust storm was over in the Taklimakan desert, its effects on China's air quality continued for several days. The coarse PM concentrations (PM10–2.5) in Hotan, Kashgar, Aksu, Korla, Hami, Xining, Yinchuan, Taiyuan, and Beijing spiked to levels around 14, 36, 11, 6, 7, 12, 11, 12, and 6 times higher than their 2022 averages, respectively. This study provides valuable insights into the causes and effects of the Taklimakan desert dust storms, helping authorities develop effective mitigation plans.

Demonstration on the performance enhancement of the 1.645 µm coherent Doppler lidar for long-range wind measurements with modification of laser transmitter and optical antenna

We have developed and experimentally investigated a long-range 1.645 µm coherent Doppler wind lidar (CDWL) system. A compact 1.645 µm single-frequency Er:YAG laser is utilized as the laser transmitter. The impact of laser transmitter parameters on wind detection was assessed using the figure of merit (FOM) concept. To enhance the measurement efficiency, the influence of wave aberrations on the heterodyne efficiency was analyzed. A Galilean telescope with an optical aperture of 100 mm is designed as the optical antenna based on the analysis. The line of sight (LOS) detection range exceeds 30.42 km with a data rate of 1 Hz at an elevation angle of 3.5°. To evaluate the effectiveness of the CDWL, comparison experiments were conducted between the 1.645 µm CDWL and a calibrated 1.55 µm CDWL, revealing a correlation coefficient of 0.9816 for the whole detection path in the wind velocity measurement.

Directly measuring the power-law exponent and kinetic energy of atmospheric turbulence using coherent Doppler wind lidar

Abstract. Atmospheric turbulence parameters, such as turbulent kinetic energy and dissipation rate, are of great significance in weather prediction, meteorological disasters, and forecasting. Due to the lack of ideal direct detection methods, traditional structure function methods are mainly based on Kolmogorov's assumption of local isotropic turbulence and the well-known -5/3 power law within the inertial subrange, which limits their application. Here, we propose a method for directly measuring atmospheric turbulence parameters using coherent Doppler wind lidar, which can directly obtain atmospheric turbulence parameters and vertical structural features, breaking the limitations of traditional methods. The first published spatiotemporal distribution map of the power-law exponent of the inertial subrange is provided in this study, which indicates the heterogeneity of atmospheric turbulence at different altitudes and also indicates that the power-law exponent at high altitudes does not fully comply with the -5/3 power law, proving the superiority of our method. We analyze the results under different weather conditions, indicating that the method still holds. The turbulent kinetic energy and power-law index obtained by this method are continuously compared with the results obtained with an ultrasonic anemometer for a month-long period. The results of the two have high consistency and correlation, verifying the accuracy and applicability of the proposed method. The proposed method has great significance in studying the vertical structural characteristics of atmospheric turbulence.

Pulse Accumulation Approach Based on Signal Phase Estimation for Doppler Wind Lidar.

Coherent Doppler wind lidar (CDWL) uses transmitted laser pulses to measure wind velocity distribution. However, the echo signal of CDWL is easily affected by atmospheric turbulence, which can decrease the signal-to-noise ratio (SNR) of lidar. To improve the SNR, this paper proposes a pulse accumulation method based on the cross-correlation function to estimate the phase of the signal. Compared with incoherent pulse accumulation, the proposed method significantly enhances the correlation between signals from different periods to obtain high SNR gains that arise from pulse accumulation. Using simulation, the study evaluates the effectiveness of this phase estimation method and its robustness against noise in algorithms which analyze Doppler frequency shifts. Furthermore, a CDWL is developed for measuring the speed of an indoor motor turntable and the outdoor atmospheric wind field. The phase estimation method yielded SNR gains of 28.18 dB and 32.03 dB for accumulation numbers of 500 and 1500, respectively. The implementation of this method in motor turntable speed measurements demonstrated a significant reduction in speed error-averaging 9.18% lower than that of incoherent accumulation lidar systems. In experiments that measure atmospheric wind fields, the linear fit curve slope between the measured wind speed and the wind speed measured via a commercial wind-measuring lidar can be reduced from 1.146 to 1.093.

Narrow-linewidth and low RIN Tm/Ho co-doped fiber laser based on self-injection locking.

A narrow-linewidth and low relative intensity noise (RIN) Tm/Ho co-doped fiber laser based on a saturable absorber and self-injection locking was demonstrated for the first time. Utilizing self-injection locking technology, the frequency noise power spectral density is remarkably reduced by more than 17.1 dB from 1.21 × 106 Hz2/Hz to 7.30 × 103 Hz2/Hz when the frequency is approximately 1 kHz. Furthermore, a laser with a linewidth compressed to a quarter of the original linewidth from 44.386 kHz to 2.850 kHz, a RIN of less than -127.74 dB/Hz, and an optical signal-to-noise ratio of more than 71.6 dB can be obtained. Using a delay fiber, the relaxation oscillation peak frequencies move to lower frequencies, from 27.9 kHz to 15.8 kHz. The proposed laser is highly competitive in advanced coherent light detection fields, including coherent Doppler wind lidar, high-speed coherent optical communication, and precise absolute distance coherent measurement.

Windshear Detection in Rain Using a 30 km Radius Coherent Doppler Wind Lidar at Mega Airport in Plateau

Convective weather is often accompanied by precipitation and windshear, seriously endangering the safety of aircraft during takeoff and landing. However, under rainfall conditions, conventional wind lidars have a limited detection range due to significant signal attenuation. To solve this problem, a 200 mm temperature-controlled telescope coated with a hydrophobic film is applied in the coherent Doppler wind lidar system to improve the detection capability in rain. The maximum detection range of the lidar is extended to 30 km and demonstrated at Kunming Changshui International Airport at an altitude of 2102 m. Firstly, the detection accuracy and maximum detection range of the lidar are verified. Through the analysis of the horizontal wind field under two typical convective weather conditions, it is found that convective weather often accompanies low-level convergence and divergence structures, leading to headwind shear and crosswind shear on the airport runway. From the vertical profile, it is shown that the triggering of convective weather is accompanied by low-level southwest winds and high-altitude northeastern winds. According to the statistics of wind speed and direction on clear and rainy days over 9 months, rainy days are usually caused by the invasion of cold air from Northeast China, resulting in airport windshear. In summary, the enhanced lidar can effectively identify and analyze windshear during rainy days, which is very useful for aviation safety, especially for takeoff and landing in all weather conditions.

Theoretical performance of a 1.5-µm satellite-borne coherent Doppler wind lidar using a planar waveguide optical amplifier with a demonstrated figure of merit: simulation of signal detection probability, measurement precision, and bias.

We report performance of a satellite-borne coherent Doppler wind lidar (SCDWL), which equips a planer waveguide amplifier (PWA) operating in a wavelength of 1.5 µm. The performance is defined by detection probability, measurement precision, and bias, and is characterized with a Doppler wind lidar (DWL) simulation that considers a realistic wind velocity profile, and instrumental and atmospheric parameters. Among the parameters, we carefully model those related to the PWA whose figure of merit has great impact on the performance of SCDWL and has shown rapid improvement in recent years. Moreover, we introduce three models for a backscattering coefficient (high, moderate, and low) to assess the influence from variation of atmospheric backscattering. Our simulation demonstrates that the SCDWL can work with reasonable performance for the target altitude of 6 km in the case of the high-backscattering model. The simulation also exhibits that the SCDWL can observe wind velocity at the altitude of 12 km if improved instrumental parameters or higher backscattering coefficients are considered. In addition, we reveal that non-uniform wind velocity distribution degrades the performance of the SCDWL and induces a bias between measured and real wind velocity.

Denoising coherent Doppler lidar data based on a U-Net convolutional neural network.

The coherent Doppler wind lidar (CDWL) has long been thought to be the most suitable technique for wind remote sensing in the atmospheric boundary layer (ABL) due to its compact size, robust performance, and low-cost properties. However, as the coherent lidar exploits the Mie scattering from aerosol particles, the signal intensity received by the lidar is highly affected by the concentration of aerosols. Unlike air molecules, the concentration of aerosol varies greatly with time and weather, and decreases dramatically with altitude. As a result, the performance of the coherent lidar fluctuates greatly with time, and the detection range is mostly confined within the planetary boundary layer. The original data collected by the lidar are first transformed into a spectrogram and then processed into radial wind velocities utilizing algorithms such as a spectral centroid. When the signal-to-noise ratio (SNR) is low, these classic algorithms fail to retrieve the wind speed stably. In this work, a radial wind velocity retrieving algorithm based on a trained convolutional neural network (CNN) U-Net is proposed for denoising and an accurate estimate of the Doppler shift in a low-SNR regime. The advantage of the CNN is first discussed qualitatively and then proved by means of a numerical simulation. Simulated spectrum data are used for U-Net training and testing, which show that the U-Net is not only more accurate than the spectral centroid but also achieves a further detection range. Finally, joint observation data from the lidar and radiosonde show excellent agreement, demonstrating that the U-Net-based retrieving algorithm has superior performance over the traditional spectral centroid method both in accuracy and detection range.

Real-Time Synchronous Acquisition and Processing of Signal in Coherent Doppler Wind Lidar Using FPGA

Coherent Doppler wind lidar has become a primary remote sensing technique for measuring atmospheric wind fields in recent years. However, the high bandwidth of the time domain echo signal has limited real-time data acquisition and processing. In this work, we propose a real-time data acquisition and preprocessing integrated solution. This approach is implemented using on-chip system field programmable gate array (FPGA) hardware while utilizing a 7-channel base-4 polyphase fast Fourier transform calculation module and a pipelined structure operation. Within a 1 s data collection time, the real-time rapid acquisition and spectral preprocessing of lidar echo signals at a range of 9.9 km can be achieved. We compare the observation data with the measurement data from Windcube100s and radiosondes, and the results indicate that the coherent wind lidar developed in this paper can detect heights above 4.0 km, with effective data acquisition rates of 82% and 61% in the height ranges of 1500–2000 m and 2000–2500 m, respectively. At the height range of 3.5 km, the correlations for horizontal wind speed and direction measured by the lidar were all above 0.99, with the wind speed and direction measurement deviations being better than 0.56 m/s and 8.40∘, respectively.

Thundercloud structures detected and analyzed based on coherent Doppler wind lidar

Abstract. The studies of intracloud discharges may shed light on the microphysical structure of thunderclouds, as both the magnitude and the sign of charge separation due to graupel collides with ice crystals within the strong updrafts are influenced by the surrounding environment. Here, a compact all-fiber coherent Doppler wind lidar (CDWL) working at the 1.5 µm wavelength is applied for probing the dynamics and microphysics structure of thunderstorms. Thanks to the precise spectrum measurement, multi-component spectra signals of thunderstorms can be analyzed by the CDWL. The spectrum width, skewness, and Doppler velocity of CDWL is used to separate and identify the particle composition and polarity. In the experiment, the thundercloud properties are detected by the CDWL, 10.6 cm Doppler weather radar (DWR), and Advanced Geosynchronous Radiation Imager (AGRI) onboard Fengyun-4 satellites. In particular, the spectrum width and skewness of the thundercloud below the 0 ∘C isotherm are increased, and when a cloud-ground lightning occurs, there is additional graupel with a velocity greater than 5 m s−1. It indicates that this region is a melting layer, and lightning activity changes the motion characteristics of graupel, affecting the charge structure of the whole thundercloud. In general, our findings provide details on the velocity, phase, and composition of particles in the outside updraft region of the thunderstorm. The identification and analysis of graupel is particularly important. It is proved that the precise spectrum of CDWL is a promising indicator for studying the charge structure of thunderstorms.

The Detection of Desert Aerosol Incorporating Coherent Doppler Wind Lidar and Rayleigh–Mie–Raman Lidar

Characterization of aerosol transportation is important in order to understand regional and global climatic changes. To obtain accurate aerosol profiles and wind profiles, aerosol lidar and Doppler wind lidar are generally combined in atmospheric measurements. In this work, a method for calibration and quantitative aerosol properties using coherent Doppler wind lidar (CDWL) is adopted, and data retrieval is verified by contrasting the process with synchronous Rayleigh–Mie–Raman lidar (RMRL). The comparison was applied to field measurements in the Taklimakan desert, from 16 to 21 February 2023. Good agreements between the two lidars was found, with the determination coefficients of 0.90 and 0.89 and the root-mean-square error (RMSE) values of 0.012 and 0.013. The comparative results of continuous experiments demonstrate the ability of the CDWL to retrieve aerosol properties accurately.

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.

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).