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The use of Raman and high-spectral lidars enables measurements of a stratospheric aerosol extinction profile independent of backscatter, and a multi-wavelength (MW) lidar can obtain additional information that can aid in retrieving the microphysical characteristics of the sampled aerosol. The inversion method for retrieving aerosol particle size distributions and microphysical particle parameters from MW lidar data was studied. An inversion algorithm for retrieving aerosol particle size distributions based on the regularization method was established. Based on the inversion of regularization, the inversion method was optimized by choosing the base function closest to the aerosol distribution. The logarithmic normal distribution function was selected over the triangle function as the base function for the inversion. The averaging procedure was carried out for three main types of aerosol. The 1% averaging result near the minimum of the discrepancy gave the best estimate of the particle parameters. The accuracy and stabilization of the optimized algorithm for microphysical parameters were tested by scores of aerosol size distributions. The systematic effects and random errors impacting the inversion were also considered, and the algorithm was tested by the data, showing 10% systematic error and 15% random error. At the same time, the reliability of the proposed algorithm was also verified by using the aerosol particle size distribution data of the aircraft. The inversion results showed that the algorithm was reliable in retrieving the aerosol particle size distributions at vertical heights using lidar data.

Lidar and Ka-band Millimeter-Wave Cloud Radar (MMCR) are powerful equipment to detect the height distribution of cloud boundaries, which can monitor the whole life cycle of cloud layers. In this paper, we employ lidar and MMCR to jointly detect cloud boundaries under different conditions (e.g., single-layer clouds, multilayer clouds, and precipitating clouds). By enhancing the echo signal of lidar @1064nm and combining its SNR, he cloud signal can be accurately extracted from the aerosol signals and background noise. The interference signal is eliminated from the power spectrum of the MMCR by using SNRmin and the spectral point continuous threshold, and the quality control of the meteorological signal (echo reflectivity factor) obtained by the inversion is carried out, which improves the detection accuracy of the cloud signal. Based on the advantages and disadvantages of the two devices in detecting cloud boundaries under different conditions, cloud boundary statistical rules are established to analyze the characteristics of cloud boundary changes in Xi'an in 2021. The seasonal variation characteristics of clouds show that the frequency distribution of cloud boundaries in vertical height in spring and summer has a similar variation trend. The normalized cloud amount is the lowest in spring (0.65) and the highest in summer 2.46). The frequency distribution of high-level clouds (at 11~12 km) is the highest in autumn, and the clouds in winter are mainly distributed below 8 km. Furthermore, the cloud boundary frequency distribution results for the whole year of 2021 show that the cloud bottom boundary below 1.5 km is more than 10%, the frequency within the height range of 3.06 km~3.6 km is approximately 3.24%, and the frequency above 8 km is less than 2%. The cloud top boundary frequency distribution has the characteristics of a bimodal distribution. The first narrow peak lies at approximately 1.5~3.1 km, and the second peak appears at 7.5~10.5 km. [ABSTRACT FROM AUTHOR]

Lidar is an active remote sensing instrument, and it has been widely used in the detection of atmospheric environmental parameters and meteorological parameters. In recent years, climate change has been widely concerned by the public, and the corresponding atmospheric detection technology has also been developed rapidly. Atmospheric Lidar has been developed rapidly in China, and has achieved good research achievements. The research progress and development status of Lidar for atmospheric detection in recent years are introduced and summarized in this invited paper. The advantages and disadvantages of all kinds of atmospheric detection Lidars and their applications in different detection objects are comprehensively introduced in this article. Finally, the bottlenecks of Lidar technology are summarized, and the development trend of Lidar is also prospected. [ABSTRACT FROM AUTHOR]

To monitor the variability and the correlation of multiple atmospheric parameters in the whole troposphere and the lower stratosphere, a ground-based ultraviolet multifunctional Raman lidar system was established to simultaneously measure the atmospheric parameters in Xi'an (34.233°N, 108.911°E). A set of dichroic mirrors (DMs) and narrow-band interference filters (IFs) with narrow angles of incidence were utilized to construct a high-efficiency 5-channel polychromator. A series of high-quality data obtained from October 2013 to December 2015 under different weather conditions were used to investigate the functionality of the Raman lidar system and to study the variability of multiple atmospheric parameters in the whole stratosphere. Their conveying characteristics are also investigated using back trajectories with a hybrid single-particle Lagrangian integrated trajectory model (HYSPLIT). The lidar system can be operated efficiently under weather conditions with a cloud backscattering ratio of less than 18 and an atmospheric visibility of 3 km. We observed an obvious temperature inversion phenomenon at the tropopause height of 17–18 km and occasional temperature inversion layers below the boundary layer. The rapidly changing atmospheric water vapor is mostly concentrated at the lower troposphere, below ∼4–5 km, accounting for ∼90% of the total water vapor content at 0.5–10 km. The back trajectory analysis shows that the air flow from the northwest and the west mainly contributes to the transport of aerosols and water vapor over Xi'an. The simultaneous continuous observational results demonstrate the variability and correlation among the multiple atmospheric parameters, and the accumulated water vapor density in the bottom layer causes an increase in the aerosol extinction coefficient and enhances the relative humidity in the early morning. The long-term observations provide a large amount of reliable atmospheric data below the lower stratosphere, and can be used to study their correlation and to improve local climate change research. [ABSTRACT FROM AUTHOR]

• Be different from the existing Mie-scattering slant visibility lidar, a two-wavelength Raman-Mie scanning lidar is proposed slant visibility measurements. • The four-channel spectroscopic system is designed to provide enough aerosol parameter profiles and to obtain 33-layer actual atmospheric scattered radiance. • Vertical lidar and slant lidar are combined to contribute to calculate the slant visibility at any slant directions. • Slant visibility distances are realized with consideration of the interaction of the actual atmospheric scattered radiance and atmospheric transparency. • Lidar experiments under different weather conditions demonstrated the feasibility of the lidar system. Considering the necessity of lidar for atmospheric scattered radiance measurement, and the application scenario in civil aviation airports, an eye-safe two-wavelength Raman-Mie lidar is proposed for slant visibility measurements, which differs from the existing Mie-scattering slant visibility lidar. Lidar system is to provide atmospheric aerosol parameters for SBDART model, so as to solve the calculation of actual atmospheric scattered radiance. The obtained information including the total irradiance, the scattered radiance, and the atmospheric transparency are combined to calculate the contrast ratio between the object and the background.Lidar experiments were carried out over Xi'an University of Technology, China (34.233°N, 108.911°E), and two cases conducted under overcast and haze conditions are investigated. Using the 33-layer atmospheric aerosol list by vertical lidar detection, the 33-layer actual atmospheric scattered radiance and the total solar irradiance are obtained by SBDART model. The atmospheric transparency is further obtained by slant scanning detection. Taking the playground runway and the grassland as the object and the background, the contrast ratio curves can be calculated with consideration of actual atmospheric scattered radiance and atmospheric transparency, and the slant visibility distances can be thus obtained at any slant directions under the contrast ratio of 0.05. The results under overcast condition showed that, the obtained slant visibility is at the distance of 9 km and 11.2 km at a zenith angle of 50° and 70°, with the statistical measurement error of 12.5% and 6.54%. The results under haze weather condition also differs at slant directions, the slant visibility distances varied ranging from 4.4 km to 6.51 km, and the statistical measurement errors are approximately of 10.21% and 8.89%. The results demonstrated the developed two-wavelength Raman-Mie lidar provides a new solution to actual atmospheric scattered radiance measurements, and also validated its feasibility and reliability for accurate slant visibility measurements. [ABSTRACT FROM AUTHOR]