Identifying cloud, precipitation, windshear, and turbulence by deep analysis of the power spectrum of coherent Doppler wind lidar

Reconstruction for beam blockage of lidar based on generative adversarial networks

Doppler lidar is an active laser remote sensing instrument. However, beam blockage caused by low-altitude obstacles is a critical factor affecting the quality of lidar data. To reconstruct the line of sight velocities (LOSV) in areas with beam blockages and to evaluate the effectiveness of reconstruction results, the LOSV-filling network (LFnet) approach based on generative adversarial networks (GANs) and an evaluation scheme based on the degree of blockage are proposed in this paper. The LFnet comprises two adversarial models. The first adversarial model captures the structural features of LOSV to output the edge map, and the second adversarial fills in the blockage area using the edge map. We have built a packaged dataset consisting of training, validation and test datasets with mask sets. Then the sensitivity of the reconstruction effectiveness with different shielding conditions is studied, to reveal the mechanism of shielding influencing the reconstruction. A series of indicators were used to evaluate the model's performance, including the traditional indicators and the proposed indicator of root mean square error (RMSE). Finally, LFnet was demonstrated in a practical application in an airport. The complete process of an easterly gust front is reconstructed with RMSE less than 0.85 m/s, which has significance for flight safety.

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.

Estimation of atmospheric refractive index structure constant using an InGaAs/InP single-photon detector

Remote sensing of atmospheric refractive index structure constant ($\boldsymbol{C}_{\boldsymbol{n}}^2$) using lidar incorporating a single-photon detector (SPD) is proposed. The influence of turbulence on the fiber coupling efficiency with different fiber modes is analyzed. $\boldsymbol{C}_{\boldsymbol{n}}^2$ can be derived from the ratio of the backscattering signals counted on single-mode and multimode fiber-coupling channels of the SPD. In the experiment, by eliminating the shot noise effect on the fluctuation of the ratio, the lowest coupling ratio is used to retrieve $\boldsymbol{C}_{\boldsymbol{n}}^2$ and demonstrated by comparing to the results measured from a large aperture scintillometer (LAS). Good agreement between results from the LAS and the lidar is achieved. The correlation coefficients are 0.90, 0.89, and 0.89, under three different weather conditions.

Suppression of crosstalk in coding CDWL by active FOV modulation with a deformable mirror

Coding technology provides new ideas for spatial resolution enhancement of coherent Doppler wind lidar (CDWL). To improve the performance of coding CDWL for ultra-fine-wind field detection, the crosstalk between neighboring laser pulses is analyzed in theory. The strong backscattered signal from aerosols in near field region will interfere with the weak atmospheric signal, making the accuracy of Doppler shift estimation deteriorate seriously. Considering the formation mechanism of crosstalk, a solution based on adaptive field of view (FOV) modulation is proposed to suppress the crosstalk which is validated by numerical simulation and experiment. Dynamic range of the backscatter intensity is controlled from 10 dB to 2 dB within the distance of 50 m to 300 m, thus the crosstalk is accordingly suppressed.

Coherent Doppler wind lidar signal denoising adopting variational mode decomposition based on honey badger algorithm

Coherent Doppler wind lidar (CDWL) is used to measure wind velocity distribution by using laser pulses. However, the echo signal is easily affected by atmospheric turbulence, which could decrease the effective detection range of CDWL. In this paper, a variation modal decomposition based on honey badger algorithm (VMD-HBA) is proposed and demonstrated. Compared with conventional VMD-based methods, the proposed method utilizes a newly developed HBA to obtain the optimal VMD parameters by iterating the spectrum fitness function. In addition, the Correlation Euclidean distance is applied to identify the relevant mode and used to reconstruct the signal. The simulation results show that the denoising performance of VMD-HBA is superior to other available denoising methods. Experimentally, this combined method was successfully realized to process the actual lidar echo signal. Under harsh detection conditions, the effective detection range of the homemade CDWL system is extended from 13.41 km to 20.61 km.

Turbulence Detection in the Atmospheric Boundary Layer Using Coherent Doppler Wind Lidar and Microwave Radiometer

The refractive index structure constant (Cn2) is a key parameter used in describing the influence of turbulence on laser transmissions in the atmosphere. Three different methods for estimating Cn2 were analyzed in detail. A new method that uses a combination of these methods for continuous Cn2 profiling with both high temporal and spatial resolution is proposed and demonstrated. Under the assumption of the Kolmogorov “2/3 law”, the Cn2 profile can be calculated by using the wind field and turbulent kinetic energy dissipation rate (TKEDR) measured by coherent Doppler wind lidar (CDWL) and other meteorological parameters derived from a microwave radiometer (MWR). In a horizontal experiment, a comparison between the results from our new method and measurements made by a large aperture scintillometer (LAS) is conducted. The correlation coefficient, mean error, and standard deviation between them in a six-day observation are 0.8073, 8.18 × 10−16 m−2/3 and 1.27 × 10−15 m−2/3, respectively. In the vertical direction, the continuous profiling results of Cn2 and other turbulence parameters with high resolution in the atmospheric boundary layer (ABL) are retrieved. In addition, the limitation and uncertainty of this method under different circumstances were analyzed, which shows that the relative error of Cn2 estimation normally does not exceed 30% under the convective boundary layer (CBL).

Real-Time Synchronous 3-D Detection of Air Pollution and Wind Using a Solo Coherent Doppler Wind Lidar

The monitoring and tracking of urban air pollution is a challenging environmental issue. The approach of synchronous 3-D detection of wind and pollution using a solo coherent Doppler wind lidar (CDWL) is developed and demonstrated. The 3-D distribution of pollutant is depicted by the backscatter coefficient based on signal intensity of CDWL. Then, a high-resolution wind field is derived to track the local air pollution source with its diffusion and to analyze transboundary air pollution episodes. The approach is experimentally implemented in a chemical industry park. Smoke plumes caused by point source pollutions are captured well using plan position indicator (PPI) scanning with low elevation. A typical source of pollution is located, combining the trajectory of the smoke plume and the horizontal wind vector. In addition, transboundary air pollution caused by the transport of dust storms is detected in a vertical profile scanning pattern, which is consistent with the results of national monitoring stations and backward trajectory models. Our present work provides a significant 3-D detection approach to air pollution monitoring with its sources, paths, and heights by using a solo-CDWL system.

Microburst, Windshear, Gust Front, and Vortex Detection in Mega Airport Using a Single Coherent Doppler Wind Lidar

Accurate wind shear detection is crucial for aviation safety, especially in landing and departure. A new approach for windshear alerting is proposed and demonstrated. This approach monitors orthogonal wind components in multiple runways using single coherent Doppler wind lidar (CDWL). First, the two orthogonal components of the wind field are retrieved from radial speed by an updated variational method. Then, the heading wind and cross wind on different runways are calculated simultaneously, without the location restriction of the single lidar. Finally, a windshear alerting message is generated through quantitatively evaluating the distribution of shear ramps over the monitoring area. The new CDWL-based approach for windshear alerting is implemented at the Beijing Daxing International Airport. The retrieved horizontal wind from the lidar is consistent with that from anemometers. Thanks to its high spatial/temporal resolution, some meteorological phenomena of aviation hazards, including microburst, windshear, gust front, and vortex are well captured. Particularly, all 10 windshear cases reported by crews are successfully identified during the windshear verification experiment, demonstrating the effectiveness and robustness of the new approach.

Dark/bright band of a melting layer detected by coherent Doppler lidar and micro rain radar

Observation of a melting layer using a 1.55 µm coherent Doppler lidar (CDL) is first presented during a stratiform precipitation event. Simultaneous radar measurements are also performed by co-located 1.24 cm micro rain radar (MRR) and 10.6 cm Doppler weather radar (DWR). As a well-known bright band in radar reflectivity appears during precipitation, an interesting dark band about 160 m below that in lidar backscattering is observed. Due to the absorption effect, the backscattering from raindrops at 1.55 µm is found much weaker than that at short wavelengths usually used in direct detection lidars. However, the CDL provides additional Doppler information which is helpful for melting layer identification. For example, a spectrum bright band with broadened width and sign conversion of skewness is detected in this case. After a deep analysis of the power spectra, the aerosol and precipitation components are separated. The fall speed of hydrometeors given by CDL is found smaller than that of MRR, with the differences of approximately 0.5 m/s and 1.5 m/s for the snow and rainfall, respectively. To illustrate the influence of absorption effect, simulations of the backscatter coefficient and extinction coefficient of aerosol and rainfall are also performed at the wavelength range of 0.3 ∼ 2.2 µm using the Mie theory.

Spatial resolution enhancement of coherent Doppler wind lidar using differential correlation pair technique

A high spatial resolution coherent Doppler wind lidar (CDWL) incorporating the differential correlation pair (DCP) technique is proposed and demonstrated. By employing pulse pair with appropriate window functions, the spatial resolution can be enhanced, as the common parts of the correlation pair can be eliminated in the differential data processing. The performance of the new method is validated in the comparison experiment with the CDWLs adopting conventional schemes. Under a given peak power, the DCP technique provides higher wind velocity accuracy compared with a conventional pulsed CDWL where the laser spectral broadening caused by short pulses can be avoided and the carrier-to-noise ratio is improved. At a laser peak power of 250 W, with a spatial and temporal resolution of 3.3 m and 1 s, continuous radial wind profiling over 700 m is realized with a maximum error of 0.1 m/s.

Photon-counting distributed free-space spectroscopy

Spectroscopy is a well-established nonintrusive tool that has played an important role in identifying and quantifying substances, from quantum descriptions to chemical and biomedical diagnostics. Challenges exist in accurate spectrum analysis in free space, which hinders us from understanding the composition of multiple gases and the chemical processes in the atmosphere. A photon-counting distributed free-space spectroscopy is proposed and demonstrated using lidar technique, incorporating a comb-referenced frequency-scanning laser and a superconducting nanowire single-photon detector. It is suitable for remote spectrum analysis with a range resolution over a wide band. As an example, a continuous field experiment is carried out over 72 h to obtain the spectra of carbon dioxide (CO2) and semi-heavy water (HDO, isotopic water vapor) in 6 km, with a range resolution of 60 m and a time resolution of 10 min. Compared to the methods that obtain only column-integrated spectra over kilometer-scale, the range resolution is improved by 2-3 orders of magnitude in this work. The CO2 and HDO concentrations are retrieved from the spectra acquired with uncertainties as low as ±1.2% and ±14.3%, respectively. This method holds much promise for increasing knowledge of atmospheric environment and chemistry researches, especially in terms of the evolution of complex molecular spectra in open areas.

Cloud Seeding Evidenced by Coherent Doppler Wind Lidar

Evaluation of the cloud seeding effect is a challenge due to lack of directly physical observational evidence. In this study, an approach for directly observing the cloud seeding effect is proposed using a 1548 nm coherent Doppler wind lidar (CDWL). Normalized skewness was employed to identify the components of the reflectivity spectrum. The spectrum detection capability of a CDWL was verified by a 24.23-GHz Micro Rain Radar (MRR) in Hefei, China (117°15′ E, 31°50′ N), and different types of lidar spectra were detected and separated, including aerosol, turbulence, cloud droplet, and precipitation. Spectrum analysis was applied as a field experiment performed in Inner Mongolia, China (112°39′ E, 42°21′ N ) to support the cloud seeding operation for the 70th anniversary of China’s national day. The CDWL can monitor the cloud motion and provide windshear and turbulence information ensuring operation safety. The cloud-precipitation process is detected by the CDWL, microwave radiometer (MWR) and Advanced Geosynchronous Radiation Imager (AGRI) in FY4A satellites. In particular, the spectrum width and skewness of seeded cloud show a two-layer structure, which reflects cloud component changes, and it is possibly related to cloud seeding effects. Multi-component spectra are separated into four clusters, which are well distinguished by spectrum width and vertical velocity. In general, our findings provide new evidence that the reflectivity spectrum of CDWL has potential for assessing cloud seeding effects.

Estimating the Parameters of Wind Turbulence from Spectra of Radial Velocity Measured by a Pulsed Doppler Lidar

The strategy providing an estimation of both the mean velocity and the temporal and spatial spectra of radial velocity from data of the same pulse coherent Doppler lidar is proposed. Theoretical relations taking into account the averaging over the probing volume while estimating the spectra of fluctuations of the radial velocity measured by lidar are presented. The method of estimation of the turbulent energy dissipation rate and the variance of the vertical component of wind velocity vector from the spectra of radial velocity is carried out. The results of the comparative experiments are discussed and used in further studies of wind turbulence in the atmospheric boundary layer during the formation of low-level jets and propagation of internal gravity waves.

Remote sensing of raindrop size distribution using the coherent Doppler lidar

The coherent Doppler wind lidar (CDL) shows capability in precipitation detection. Retrieval of the raindrop size distribution (DSD) using CDL is still challenging work, as both accurate backscattering cross section at the working wavelength and reflectivity spectrum of raindrop are required. Firstly, the Mie theory and the vectorial complex ray model (VCRM) are applied to calculate backscattering cross section for small spheric raindrops and large oblate raindrops, respectively. Secondly, an iterative deconvolution method is proposed to separate the reflectivity spectrum of raindrop from the lidar power spectrum, which is a superposition of rain and aerosol components. An accompanying aerosol signal model considering the effect of temporal window, from the same height and time, is used to improve the accuracy and robustness of the iteration. In experiment, a co-located micro rain radar (MRR) is used for comparison. Good agreements are obtained despite tremendous differences in wavelength and scattering characteristics. As an example, at 600 m height, the R² of linear fitting to the mean rain velocity and mean raindrop diameter between CDL and MRR are 0.96 and 0.93, respectively.