The temperature of the middle atmosphere is of great significance in the coupled study of the upper and lower layers. A pure rotational Raman–Rayleigh scattering LiDAR system was developed for profiling the middle atmospheric temperature at daytime and nighttime continuously by employing an ultra-narrow band interferometer. The comparisons between LiDAR detections and radiosonde data show that the LiDAR system has temperature detection capabilities of 80 km and 60 km at night and during the day, respectively. The results demonstrate that our method can reliably detect the atmospheric temperature in the middle atmosphere. The significant non-uniformity in the horizontal distribution of temperature in the middle atmosphere and the vertical gradient of atmospheric temperature could be observed by using the developed LiDAR.

Integrated systems are facing complex and changing environments with the wide application of atmospheric LiDAR in civil, aerospace, and military fields. Traditional analysis methods employ optical software to evaluate the optical performance of integrated systems, and cannot comprehensively consider the influence of optical and mechanical coupling on the optical performance of the integrated system, resulting in the unsatisfactory accuracy of the analysis results. Optical–mechanical integration technology provides a promising solution to this problem. A small-field-of-view LiDAR system with high repetition frequency, low energy, and single-photon detection technology was taken as an example in this study, and the Zernike polynomial fitting algorithm was programmed to enable transmission between optical and mechanical data. Optical–mechanical integration technology was employed to obtain the optical parameters of the integrated system under a gravity load in the process of designing the optical–mechanical structure of the integrated system. The experimental validation results revealed that the optical–mechanical integration analysis of the divergence angle of the transmission unit resulted in an error of 2.586%. The focal length of the telescope increased by 89 μm, its field of view was 244 μrad, and the error of the detector target surface spot was 4.196%. The continuous day/night detection results showed that the system could accurately detect the temporal and spatial variations in clouds and aerosols. The inverted optical depths were experimentally compared with those obtained using a solar photometer. The average optical depth was 0.314, as detected using LiDAR, and 0.329, as detected by the sun photometer, with an average detection error of 4.559%. Therefore, optical–mechanical integration analysis can effectively improve the stability of the structure of highly integrated and complex optical systems.

Through theoretical calculations and field experiments, the setting of gate width in distance gating technology has been optimized in DIM LiDAR. The mathematical relationship between gate width and detection distance has been derived. The relationship curves between gate width and image signal-to-noise ratio(SNR), as well as gate width and atmospheric refractive index structure constant \(C_n^2\) were obtained. The results indicate that at a constant detection distance, there is a gradual increase in the SNR of the image with increasing gate width, followed by a saturation point. The higher the SNR, the closer the inverted $C_n^2$ is to the ultrasonic anemometer. Meanwhile, if the SNR is similar, the inverted $C_n^2$ is similar. Finally, the appropriate gate width for this system is given.

A denoising method applied to atmospheric coherent length lidar is proposed. Wavelet decomposition (WD) and the adaptive median filter (ADMF) are combined in this method. In this research, the effectiveness of the WD-ADMF has been verified through simulation and measurement. The results show that this filter algorithm, when applied to lidar data, improves the average peak signal-to-noise ratio (PSNR) and centroid error while maintaining data integrity such that the measurement of coherence length or the inference of C n 2 from coherence length more closely matches simulated truth and measured data.

In the study of atmospheric wind fields from the upper troposphere to the stratosphere (10 km to 50 km), direct detection wind LiDAR is considered a promising method that offers high-precision atmospheric wind field data. In 2020, Xie et al. of the Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, developed an innovative rotating Rayleigh Doppler wind LiDAR (RRDWL). The system aims to achieve single-LiDAR detection of atmospheric wind fields by rotating the entire device cabin. In 2022, the feasibility of the system was successfully validated in laboratory conditions, and field deployment was completed. Due to the structural differences between this system and traditional direct-detection wind LiDAR, performance tests were conducted to evaluate its continuous detection capability in outdoor environments. Subsequently, based on the test results and error analysis, further analysis was carried out to identify the main factors affecting the system’s detection performance. Finally, the error analysis and traceability of the detection results were conducted, and corresponding measures were discussed to provide a theoretical foundation for optimizing the performance of RRDWL.

An integrated LiDAR system has been reported, which can be used for simultaneous detection of atmospheric transmittance, turbulence, and wind along the same path. Through the integrated design of optics and mechanics, the size and weight of the system were effectively reduced. The comprehensive detection distance of atmospheric transmittance, atmospheric coherence length, and radial wind had also been achieved at least 4 kilometers. Comparative experiments have demonstrated that the detection results of the integrated LiDAR system and the near-surface meteorological observation system have standard deviations of less than 0.03 km-1 for extinction coefficient, 0.2 m/s for wind velocity, and 7.15 x 10-14 m-2/3 for C 2 n (atmospheric refractive index structure parameter), thus verifying the accuracy of the system detection. The reliability of the integrated LiDAR system was validated through six consecutive nights of continuous detection experiments, measuring three parameters simultaneously. Through analysis, the influence laws among atmospheric transmittance, coherence length, and wind were preliminarily explored. Significant variations in wind velocity can induce substantial fluctuations in atmospheric coherence length, and it is positively correlated with atmospheric transmittance. The integrated LiDAR system can provide a variety of reliable real-time detection data for further research on the laser transmission process in the atmosphere.

Through theoretical calculations and field experiments, the setting of gate width in distance gating technology has been optimized in DIM LiDAR. The mathematical relationship between gate width and detection distance has been derived. The relationship curves between gate width and image signal-to-noise ratio(SNR), as well as gate width and atmospheric refractive index structure constant C_n^2 were obtained. The results indicate that at a constant detection distance, there is a gradual increase in the SNR of the image with increasing gate width, followed by a saturation point. The higher the SNR, the closer the inverted C_n^2 is to the ultrasonic anemometer. Meanwhile, if the SNR is similar, the inverted C_n^2 is similar. Finally, the appropriate gate width for this system is given.

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 alpha (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 alpha 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 the wind measurement of CDL.

Due to the complex and variable nature of the atmospheric conditions, traditional multi-wavelength differential absorption lidar (DIAL) methods often suffer from significant errors when inverting ozone concentrations. As the detection range increases, there is a higher demand for Signal to Noise Ratio (SNR) in lidar signals. Based on this, the paper discusses the impact of different atmospheric factors on the accuracy of ozone concentration inversion. It also compares the advantages and disadvantages of the two-wavelength differential method and the three-wavelength dual-differential method under both noisy and noise-free conditions. Firstly, the errors caused by air molecular extinction, aerosol extinction, and backscatter terms in the inversion using the two-wavelength differential method were simulated. Secondly, the corrected inversion errors were obtained through direct correction and the introduction of a three-wavelength dual differential correction. Finally, addressing the issue of insufficient SNR in practical inversions, the inversion errors of the two correction methods were simulated by constructing lidar parameters and incorporating appropriate noise. The results indicate that the traditional two-wavelength differential algorithm is significantly affected by aerosols, making it more sensitive to aerosol concentration and structural changes. On the other hand, the three-wavelength dual differential algorithm requires a higher SNR in lidar signals. Therefore, we propose a novel strategy for inverting atmospheric ozone concentration, which prioritizes the use of the three-wavelength dual-differential method in regions with high SNR and high aerosol concentration. Conversely, the direct correction method utilizing the two-wavelength differential approach is used. This approach holds the potential for high-precision ozone concentration profile inversion under different atmospheric conditions.

This study investigates the macroscopic and optical properties of cirrus clouds in the 32N region from July 2016 to May 2017, leveraging data from ground-based lidar observations and CALIOP to overcome the inconsistencies in detected cirrus cloud samples. Through extensive data analysis, statistical characteristics of cirrus clouds were discerned, revealing lidar ratio values of 28.5 ± 10.8 from ground-based lidar and 27.4 ± 11.2 from CALIOP. Validation with a decade of CALIOP data (2008-2018) confirmed these findings, presenting a consistent lidar ratio of 27.4 ± 12.0. A significant outcome of the analysis was the identification of a positive correlation between the lidar ratio and cloud centroid temperature, indicating a gradual decrease in the lidar ratio as temperatures dropped. The study established a fundamental consistency in their macroscopic properties, including cloud base height, cloud top height, cloud thickness, cloud centroid height, and cloud centroid temperature. The results for ground-based lidar (CALIOP) are: 10.0 ± 2.1 km (10.0 ± 2.2 km), 11.8 ± 2.1 km (11.5 ± 2.3 km), 1.87 ± 0.83 km (1.52 ± 0.71 km), and 10.5 ± 2.2 km, -46.9 ± 9.7°C (-47.1 ± 10.0°C).These properties exhibited seasonal variations, with cirrus clouds reaching higher altitudes in summer and lower in winter, influenced by the height of the tropopause. The optical properties of cirrus clouds were also analyzed, showing an annual average optical depth of 0.31 ± 0.35 for ground-based lidar and 0.32 ± 0.44 for CALIOP. The study highlighted the distribution of subvisible, thin, and thick cirrus clouds, with a notable prevalence of subvisible clouds during summer, suggesting their frequent formation above 14 km. Furthermore, the study observed linear growth in geometric thickness and optical depth up to 2.5 km from CALIOP and 2.9 km from ground-based lidar. Maximum optical depth was observed at cloud centroid temperatures of -35°C for CALIOP and -40°C for ground-based lidar, with optical depth decreasing as temperatures fell. This suggests that fully glaciated cirrus clouds exhibit the highest optical depth at warmer temperatures, within the complete glaciation temperature range of -35°C to -40°C.

为了实现高精度连续探测对流层和平流层大气风场，搭建了一台直接测风激光雷达系统对对流层和平流层大气风场进行探测。该系统基于双边缘法布里-珀罗标准具的瑞利散射多普勒测风原理，使用转台式探测结构，通过频率跟踪的手段对频率漂移进行跟踪，确保测风的精度。实验结果表明，该系统对对流层和平流层大气风场探测效果良好，频率跟踪的范围为±50 MHz，可以大大减小频率漂移带来的风速误差。经过系统的稳定运行和长时间的观测，在40 km处测得的径向风速随机误差为8 m/s。径向风速合成为水平风速后，随机误差在38 km处最大为10 m/s左右。该系统白天探测高度为25 km，夜晚探测高度为38 km。与探空数据对比，风速误差均小于10 m/s，其中风速误差在±5 m/s的范围内的数据量约占75.8%，探测的风向误差与探空气球的趋势基本一致，误差范围在10°～20°之间，在15°范围内的数据量约占58.6%。将实测数据与探空数据进行统计分析，结果具有良好的一致性。该系统可以为对流层和平流层大气风场的探测提供数据支撑。

To provide references for the design of the lab’s upcoming prototype of the compact spaceborne lidar with a high-repetition-rate laser (CSLHRL), in this paper, the detection signal of spaceborne lidar was simulated by the measured signal of ground-based lidar, and then, the detection capability of spaceborne lidar under different atmospheric conditions was evaluated by means of the signal-to-noise ratio (SNR), volume depolarization ratio (VDR) and attenuated color ratio (ACR). Firstly, the Fernald method was used to invert the optical parameters of cloud and aerosol with the measured signal of ground-based lidar. Secondly, the effective signal of the spaceborne lidar was simulated according to the known atmospheric optical parameters and the parameters of the spaceborne lidar system. Finally, by changing the cumulative laser pulse number and atmospheric conditions, a simulation was carried out to further evaluate the detection performance of the spaceborne lidar, and some suggestions for the development of the system are given. The experimental results showed that the cloud layer and aerosol layer with an extinction coefficient above 0.3 km−1 could be easily obtained when the laser cumulative pulse number was 1000 and the vertical resolution was 15 m at night; the identification of moderate pollution aerosols and thick clouds could be easily identified in the daytime when the laser cumulative pulse number was 10,000 and the vertical resolution was 120 m.

This paper investigates the transmitter and receiver performance of an active rotating tropospheric stratospheric Doppler wind Lidar. A 532 nm laser was determined as the detection wavelength based on transmission and scattering aspects. A ten-fold Galileo beam expander consisting of spherical and aspherical mirrors was designed and produced to compress the outgoing laser’s divergence angle using ZEMAX simulation optimization and optical-mechanical mounting means. The structure and support of the 800 mm Cassegrain telescope was redesigned. Additionally, the structure of the receiver was optimized, and the size was reduced. Meanwhile, the detectors and fiber mountings were changed to improve the stability of the received optical path. A single-channel atmospheric echo signal test was used to select the best-performing photomultiplier tube (PMT). Finally, the atmospheric wind field detection results of the original and upgraded systems were compared. The results show that after optimizing the transmitter and receiver, the detection altitude of the system is increased to about 47 km, and the wind speed and wind direction profiles match better with radiosonde measurements.

激光雷达作为大气探测的有效手段之一,逐渐向小型化、轻量化的趋势发展.针对激光雷达的功能专用性,基于现场可编程门阵列(FPGA)对探测、采集系统进行了集成优化设计.逻辑中各模块之间通过握手协议和同步有限状态机有序配合完成数据链路的构建和传递.系统以FIFO作为ADC的数据存储器,通过AXI总线协议配合Xilinx MIG IP有序将FIFO的数据突发缓存到DDR中,并且通过千兆以太网完成对采集数据的传输.该激光雷达数据采集卡集成光电倍增管增益控制和回波信号采集功能,并采用兼容性硬件和逻辑设计,具有集成度高、增益调节便捷且精度高、采集快速方便以及快速适配等诸多优点.

This paper explores the effects of different factors on the results and accuracy of aerosol optical property measurements made in overlap factor regions using scanning lidar, simulation calculations and aerosol detection experiments. First, the measurement principle was analysed using the atmospheric layered structure model. The slope inversion of the simulated backscattering coefficient of the aerosols was performed using the Fernald method. Second, the measurement errors caused by the inhomogeneity of the horizontal atmospheric layers and scanning angle errors were analysed for different weather conditions. Finally, the aerosol detection accuracies of the scanning lidar under different weather conditions were explored by employing comparative experiments. The experimental results showed that the aerosol extinction characteristics in the overlap factor region can be effectively obtained using the proposed method and that the measurement results were affected by the systematic errors in the scanning angle. The proposed method would effectively solve the problems caused by the unavailability of optical properties of aerosols in the overlap factor region of lidar. Moreover, the signal inversion of slant detection also provides an accurate theoretical basis for field experiments and has a good aerosol detection capability and potential application prospects.

为满足星载激光雷达接收系统光机结构轻量化﹑高稳定性要求,基于超轻量化主镜结构模型,从材料选择﹑轻量化﹑结构形式及固定方式对望远镜主镜组件进行结构设计,获得其总重仅为9.07 kg,进行力学特性分析可知:在重力作用下,主镜面型RMS优于λ/40(λ@632.8nm),且一阶基频为659.24Hz,满足设计要求,为同类型星载激光雷达望远镜主镜组件设计提供了思路和参考.

Taking the continuous haze pollution process that occurred on January 11-17, 2015 in Beijing as an example, the vertical distribution characteristics of aerosols were obtained by inversion using joint observations of ground based and space borne lidar. The pollution sources and transport paths were derived from MODIS satellite remote sensing data and HYSPLIT backward trajectory model analysis, after which the causes of this pollution were revealed by combining ground-based air quality and meteorological observation data. The results show that the near-surface aerosol extinction coefficients inferred from lidar data are generally consistent with the variation of PM2.5 concentrations on the ground, while the planetary boundary layer height shows an opposite trend to PM2.5 concentrations, and the lowest boundary layer height is 500 m. During the pollution period, it is light wind and high humidity, and the average wind speed and relative humidity are 1.35 m/s and 66%, respectively. The presence of the inversion layer for several days inhibited the diffusion and transport of pollutants in the vertical space, and the intensity of the inversion was as high as 5 degrees C. These two factors led to the continuous accumulation of pollutants, and finally, the PM2.5 concentration reached 448 mu g/m(3) in the early morning of the January 16th, and the pollution was finally disappeared because of the southerly wind on the January 16th, and the PM2.5 concentration decreased at a rate of 82 mu g/(m(3) . h). During the observation period, the correlation coefficients of PM2.5 with NO2 and CO were 0.766 and 0.901, respectively, showing a significant positive correlation, which shows that secondary aerosols from the transformation of gaseous precursor pollutants such as NO2 are an important source of haze. Comprehensive analysis shows that this pollution is dominated by haze, which is caused by the superposition and accumulation of aerosols from regional transmission and local emissions. Pollutants from southern Hebei, Henan and Shanxi are transmitted to Beijing with high-altitude air masses and mixed with locally emitted pollution aerosols, leading to increased pollution.

A Doppler lidar mounted on a rotary platform has been developed for measuring wind fields in the upper troposphere and stratosphere. The rotating platform was used to support a large system for the detection of wind velocities of sight (VOS) in four directions. The principle, structure, and parameters of the lidar system are introduced. The Fabry-Perot interferometer (FPI), the core component of the wind measurement system, was designed after comprehensively considering the measurement uncertainty and the influence of Mie scattering. Its dual-edge channel bandwidth is 1.05 GHz with 3.48 GHz spacing. In operation, the FPI channels are locked to the laser frequency with a stability of 14.8 MHz. Compared with the local radiosonde, it was found that the deviation in wind speed below 28 km was generally less than 10 m/s, and the deviation in wind direction below 19 km was less than 10 degrees. The 42-day profile comparison between lidar in Hefei and radiosondes in Anqing and Fuyang was analyzed. The statistical results show that the wind speed and wind direction deviations between lidar and radiosondes below 20 km were approximately 10 m/s and 20 degrees, respectively, which are comparable to the regional differences in the wind field. However, as altitudes exceed 20 km, the deviations increased rapidly with height. The experiments indicate that the Doppler lidar could measure wind fields from 7 km to 30 km, with better detection accuracy below 20 km.

Dust storms pose a serious threat to air quality and public health through large‐scale, long‐distance transport. In early April 2018, two severe dust storm events occurred in the Taklimakan and Gobi Deserts in northwestern China. The advected air‐masses containing dust traveled eastward over long distances reaching the western Yangtze River Delta region (WYRDR) with local PM10 peak concentrations of 190 and 410 μg/m3 on April 6 and April 11, 2018, respectively. Satellite remote sensing and ground‐based lidar observations showed that the first dust event was transported to WYRDR at an altitude of <5 km, while the second transport height was at an altitude of <3 km. The first one was accompanied with the dry‐cold air mass in the northwest moving eastward and southward. By comparison, in the second event, the dust aerosols were mixed with anthropogenic aerosols from southwestern China. Meanwhile, as southerly warm‐humid air flows prevailed at near‐surface layer over the WYRDR in the second event, the associated higher relative humidity potentially induced hygroscopic growth of polluted dust aerosols, resulting in explosive growth of PM10. In addition, the average depolarization ratio of aerosols over WYRDR on April 6 was 0.3, while on April 11 it was 0.2, indicating that the previous pollution event featured more obvious nonspherical characteristics of aerosols. Our findings provide scientific evidence that transboundary dust events and resultant local PM10 pollution are closely related to various transport trajectories of dust aerosols as well as the local vertical wind profiles and surface humidity conditions.

From August 4th to 30th, 2020 and from November 27th to December 25th, 2020, 11 a self-developed radiosonde balloon system was used to observe high-altitude atmospheric 12 optical turbulence at three sites in northwestern China, and an improved model based on the 13 observational data was established. Through comparative analysis of the observational data 14 and the improved model, the distribution characteristics of atmospheric optical turbulence 15 under the combined action of different meteorological parameters and different landform 16 features in different seasons were obtained. The improved model can show the variation of the 17 detailed characteristics of turbulence with the height distribution, and the degree of 18 correlation with the measured values is above 0.82. The improved model can provide a 19 theoretical basis and supporting data for turbulence estimation and forecasting in 20 northwestern China. 21