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A portable polarization lidar system based on the division-of-focal-plane scheme has been proposed for all-day accurate retrieval of the atmospheric depolarization ratio. The polarization lidar system has been designed as a T-shaped architecture consisting of a closed transmitter and a detachable large focal receiver, which is capable of outdoor unmanned measurements. The lidar system features low cost, low maintenance and short blind range (∼100 m) by utilizing a 450 nm multimode laser diode as the light source and a polarization image sensor with four polarized channels as the detector. Validation measurements have been carried out on a near horizontal path in ten consecutive days. The linear volume depolarization ratio (LVDR) as well as its measurement uncertainty has been theoretically and experimentally evaluated without employing additional optical components and sophisticated online calibrations. The offset angle can also be accurately retrieved (i.e., −0.06°) from the four-directional polarized lidar profiles with a standard deviation of ±0.02° during the whole measurement period, which contributes negligible influence on the retrieval of the LVDR. It has been found out that the uncertainty of the LVDR was mainly originated from the random noise, which was below 0.004 at nighttime and may reach up to 0.008 during daytime owing to the increasing sunlight background. The performance of the polarization lidar system has been further examined through atmospheric vertical measurements. The low-cost low-maintenance portable polarization lidar system, capable of detecting four-directional polarized lidar signals simultaneously, opens up many possibilities for all-day field measurements of dust, cloud, urban aerosol, oriented particles, etc.

An incoherent Doppler lidar system based on a fiber Mach-Zehnder interferometer (FMZI) for vertical wind profiling is established. The FMZI Doppler lidar is sensitive to Mie backscattering signals but insensitive to Rayleigh backscattering signals and has a 9.99 cm FMZI arm-length difference. The lidar operates with an injection-seeded Nd:YAG laser at 532 nm and a 406-mm-aperture telescope. Vertical wind profiles up to a height of approximately 550 m were obtained with a 24 m vertical spatial resolution by the FMZI Doppler lidar in Xi'an (China) on April 17, 2018. The reference signal is used for calibrating the laser-frequency jitter. The measured vertical wind velocities are in good agreement with the coherent Doppler lidar vertical wind measurements made simultaneously from the same location. The FMZI Doppler lidar realized the critical step on the road to practice.

Lidar ratios and Angstrom exponents of continental, maritime, and desert aerosols were calculated to evaluate the effects of aerosol composition on these parameters. Their correlation was assessed using correlation analysis and curve fitting. The Pearson correlation coefficient between the lidar ratio and the Angstrom exponent was larger than 0.95 in all cases. We verified the reliability of the Pearson correlation coefficient using the significance test. The relationship between the lidar ratio and the Angstrom exponent of continental aerosol can be described by a cubic polynomial model; thus, the function relation between the change in lidar ratios at different laser wavelengths depends on the fitting coefficients and the Angstrom exponent. The relationship between the lidar ratio and the Angstrom exponent of both maritime and desert aerosols can be described by a linear model. In these aerosols, the linear change in lidar ratios at different laser wavelengths remains unaffected by the Angstrom exponent. The changes in the lidar ratio in maritime aerosol at 355 nm and 532 nm are −0.7 times and −0.18 times that at 1064 nm, respectively. For desert aerosol, the changes in the lidar ratio at 355 nm and 532 nm are 0.37 times and 1.88 times that at 1064 nm, respectively.

From August to October 2010 lidar measurements of aerosols in the troposphere were performed at Otlica observatory, Slovenia, using a vertical scanning elastic lidar. The lidar data sample, which contains 38 nighttime vertical profiles of the mean aerosol extinction, was combined with continuous ozone concentration (O3), particulate matter concentrations (PM) and daily radiosonde data. The obtained radiosonde- and lidar-derived heights of the atmospheric boundary layer (ABL), which varied considerably from day to day, were found to be in good agreement. The mean values of the aerosol optical depth (AOD) at 355 nm, were calculated separately for the ABL and for the free troposphere (FT). A ten-fold increase of the FT AOD was observed during the days with predicted presence of Saharan dust above the lidar site. To correlate AOD values with the type and origin of aerosols, backward trajectories of air-masses above Otlica were modeled using the HYSPLIT model and clustered. High ABL AOD values were found to be correlated with local circulations and slowly approaching air masses from the Balkans and low values with northwestern flows. The highest values correlated with southwestern flows originating in northern Africa.

A solar-blind lidar system is developed by using Nd:YAG laser to produce 266nm wavelength at the frequency of 10Hz as the light source to to detect the height of boundary layer in Xi'an area. The observation experiment and analysis are made.The solar background light has no 266nm wavelength and the influence of it can be ignored in the daytime, and then all day detection can be realized. It can be detected in the daytime and nighttime. The wavelength of 266nm absorbed by ozone is considered only. The absolute minimum of first derivative and second derivative of the range-squared-corrected lidar signal are employed to retrieve height of boundary layer. Based on the observation of atmosphere in daytime and nighttime, the heights of atmospheric boundary layer are 0.44km and 0.47km, and the influences of meteorological factors and human activities on the height of atmospheric boundary layer are analyzed. The results showed that the lidar can satisfied the need for detection of troposphere atmospheric aerosol particles at all time and are beneficial to offer practical and effective data for monitoring atmospheric environment in Xi'an aera.

A high spectral resolution lidar (HSRL) for simultaneously detecting vertical wind, temperature, and the backscattering ratio in the troposphere is developed. The atmospheric temperature and vertical wind are determined by the Rayleigh scattering spectrum width and Mie scattering spectrum Doppler shift, respectively. The influence of temperature and the backscattering ratio on vertical wind measurement accuracy is also analyzed. The temperature and backscattering ratio affect the wind measurement, which produces the vertical wind offset. A correction considering the effects of the method is conducted considering real-time and on-site temperature profiles and the backscattering ratio to correct wind measurement sensitivity. Measurements of HSRL taken under different weather conditions (fine and hazy days) are demonstrated. Good agreement between the HSRL and the radiosonde measurements was obtained considering lapse rates and temperature inversions. The maximum temperature offsets were 1.3 and 4 K at a height of 1.5 km on fine and hazy days, respectively. Then, real-time and on-site temperature profiles and backscattering ratios were applied to correct the real-time and on-site wind. The corrected wind profiles showed satisfactory agreement with the wind profiles acquired from the calibrated wind lidar. The maximum detection offsets of the retrieved wind speed were reduced from 1 m/s to 0.55 m/s and from 1 m/s to 0.21 m/s, respectively, which were decreases of 0.45 and 0.79 m/s in fine and hazy days after correction of sensitivity. It is evident that the corrected wind method can reduce the influence of temperature and the backscattering ratio on the wind measurement and the offset of vertical wind. The reliability of the method is also proven.

Aimed at addressing the disadvantages of restricted retrieval height caused by signal-to-noise ratio (SNR) differences between high-quantum-number and low-quantum-number pure rotational Raman scattering signals (PRRSs) obtained with the traditional retrieval method, an optimized retrieval method is proposed for atmospheric temperature profiling based on rotational Raman lidar. This method allows independent alternating solutions to high- and low-quantum-number PRRSs, where high-quantum-number PRRS lidar returns are used to solve the channel constant, and low-quantum-number PRRS returns with a high SNR are used for retrieving temperature profiles. The system sensitivity, SNR, and statistical error in temperature measurements by the two methods are first simulated and discussed, and the results are then compared to show that a higher SNR and stable sensitivity can be attributed to stable statistical errors with the optimized method. A further assessment is demonstrated by three sets of lidar data from a multifunctional Raman-Mie lidar system at the Xi'an University of Technology (34.233°N, 108.911°E). The retrieved atmospheric temperature profiles under different weather conditions are compared with radiosonde data; then, the temperature deviations are further evaluated, and a correlation analysis is performed to evaluate the reliability and correctness of the temperature data obtained by the optimized retrieval method. The results show that the effective temperature retrieval height can be greatly improved from 17 to 25 km under clear weather conditions, and a high correlation >0.99 and stable relative deviations of less than 5 K can be obtained up to 25 km. Additionally, the retrieval height can be extended from 8 to 16 km in cloudy weather, and the existence of an inversion layer can be successfully captured as well. It is evident that the proposed optimized method will provide a new and reliable retrieval theorem for atmospheric temperature profiles, and the proposed method is propitious for retrieving temperature profiles over a larger height range, even up to the lower stratosphere. It is also deduced that the proposed algorithm can favorably simplify the spectroscopic system for temperature detection in the future when the channel constant is determined in advance.

All fiber Raman temperature lidar for space borne platform has been proposed for profiling of the temperature with high accuracy. Fiber Bragg grating (FBG) is proposed as the spectroscopic system of Raman lidar because of good wavelength selectivity, high spectral resolution and high out-of-band rejection rate. Two sets of FBGs at visible wavelength 532 nm as Raman spectroscopy system are designed for extracting the rotational Raman spectra of atmospheric molecules, which intensities depend on the atmospheric temperature. The optimization design of the tuning method of an all-fiber rotational Raman spectroscopy system is analyzed and tested for estimating the potential temperature inversion error caused by the instability of FBG. The cantilever structure with temperature control device is designed to realize the tuning and stabilization of the central wavelengths of FBGs. According to numerical calculation of FBG and finite element analysis of the cantilever structure, the center wavelength offset of FBG is 11.03 nm/°C with the temperature change in the spectroscopy system. By experimental observation, the center wavelength offset of surface-bonded FBG is 9.80 nm/°C with temperature changing when subjected to certain strain for the high quantum number channel, while 10.01 nm/°C for the low quantum number channel. The tunable wavelength range of FBG is from 528.707 nm to 529.014 nm for the high quantum number channel and from 530.226 nm to 530.547 nm for the low quantum number channel. The temperature control accuracy of the FBG spectroscopy system is up to 0.03 °C, the corresponding potential atmospheric temperature inversion error is 0.04 K based on the numerical analysis of all-fiber Raman temperature lidar. The fine tuning and stabilization of the FBG wavelength realize the elaborate spectroscope of Raman lidar system. The conclusion is of great significance for the application of FBG spectroscopy system for space-borne platform Raman lidar.

Multi-longitudinal-mode (MLM) high-spectral-resolution lidar (HSRL) selects an optical interferometer with the periodic transmittance function as the spectral discriminator to separate aerosol Mie scattering signals and molecular Rayleigh scattering signals excited by the MLM pulsed lasers, such as Mach-Zehnder interferometer, Michelson interferometer, Fabry-Perot etalon and so on. In this paper, we deduce a novel algorithm for retrieving aerosol backscattering coefficient, optical depth, and aerosol extinction coefficient in the application of the MLM HSRL, in which the lidar returns should be considered as a quasi-monochromatic light. Under such a condition, the effective transmittance of Mach-Zehnder interferometer is a function of the complex degree of coherence, which plays an important role in the retrieval algorithms of aerosol optical properties. The retrieval algorithms of aerosol backscattering coefficient, optical depth and aerosol extinction coefficient based on the complex degree of coherence are presented in detail and their correctness is verified by the system simulation using an experimental Mie-Rayleigh lidar returns. Meanwhile, the absolute errors of the measurements of aerosol backscattering coefficient and optical depth are analyzed from the systematic errors and random errors. The simulation results show that the presence of aerosol layers or cloud layer deteriorates considerably the accuracy of the retrieved aerosol backscattering coefficient and optical depth, and the total absolute error of aerosol backscattering coefficient is ignored, as well as the total absolute error of optical depth can be controlled within 0.4 in the majority of the lidar data when the relative error of δ is within 20%. Both measurement examples and continuous observations from the constructed MLM HSRL have proven that the MLM HSRL has the capability in the application of fine detection of aerosol optical properties.

In order to achieve a high signal-to-noise ratio by using small laser energy and telescope aperture, we present a detection method based on Rayleigh-Brillouin scattering (RBS) for the measurement of atmospheric temperature without response functions and calibration procedures by using high spectral resolution lidar (HSRL). Different from the traditional HSRL, a Fabry-Pérot interferometer (FPI) with a continuous tunable cavity and polarization optical scheme are employed in a high spectral resolution filter. In order to continuously change the resonant frequency of the FPI, an electro-optical crystal of potassium dideuterium phosphate (DKDP) with two ring electrodes is used as a continuous tunable cavity in the FPI. At each scanned frequency point corresponded with the resonant frequency of the FPI, the received signals of four discrete points on RBS are obtained. Atmospheric temperature is inverted by using a RBS model. The polarization optical scheme is used to suppress the solar background light, and improve the utilization of return signals. In detection experiment of atmospheric temperature, the detection height is 2 km at night and 1.5 km during the day by using a pulsed energy of 30 mJ and telescope diameter of 250 mm. The results are in good agreement with the data detected by radiosonde.

The objective of this work was to investigate the effects of intrinsic fluorescence on the detection capability for biological aerosols of an UV fluorescence lidar with selected design parameters. Numerical simulations, based on the fluorescence lidar equation, were performed for fluorescence spectra ranging from 300 nm to 800 nm, where the fluorescence was induced by a pulsed laser at 266 nm. Simulation results show that the minimal detectable concentration of biological aerosols increases with detection range at different rates for different solar zenith angles, and that the uncertainties of the minimal detectable concentrations increase sharply with ranges. Lowest concentrations of biological aerosols are expected to be detectable during the night. In the day-time, aerosols emitting intrinsic fluorescence wavelengths are expected to be detectable at larger distances, with a relatively large uncertainty of the minimal detectable concentration.

Pollen is one of the important allergens in allergic diseases. The objective of this research effort is to investigate the use of a fluorescence lidar to measure concentrations of pollens in the atmosphere. The fluorescence lidar was constructed with a pulsed Nd:YAG laser, employing at fourth harmonic and second harmonic. A 250 mm diameter custom telescope was used to receive optical spectra from 260 nm–560 nm excited by 266 nm, and R7506 Photomultiplier tubes for two linear orthogonal polarization applications at 532 nm. Range-resolved fluorescence signals are collected in 32 channels of compound PMT sensor coupled with Czerny–Turner spectrograph. Based on the current configurations, we performed a series of simulations to estimate the measurement range and the concentration resolutions of pollens. With a relative error of less than 10%, theoretical analysis shows that the system is capable of identify a minimum concentration of pollen grains at 19 particles L−1 and 1 particles L−1 at daytime and nighttime within a range of 1.0 km, which is capable of identify a minimum concentration of pollen grains at 903 particles L−1 and 10 particles L−1 at daytime and nighttime within a range of 5.0 km.

Spaceborne Doppler wind lidar is currently one of the hot spots on the lidar technology. The all-fiber Mach-Zehnder interferometer (FMZI) as a frequency discriminator of Doppler wind lidar is proposed for profiling the atmospheric wind velocity. The frequency discriminator system parameters are optimized, and the retrieval method of wind velocity based on FMZI is deduced. The arm length difference of FMZI for the aerosol backscattering signal is optimized to be 74.8 cm at the laser wavelength of 532 nm. The maximum system sensitivity for wind profiling can reach up to 2.62%/(m/s), and the dynamic range of wind velocity is ±18.2 m/s. The system simulation shows that the detection range is up to 6.7 km for 1 m/s wind velocity error at a wind velocity of 15 m/s with laser energy of 250 mJ and telescope diameter of 406 mm. A rotating disc experimental system is designed to simulate the atmospheric wind field for verifying the feasibility of the system, and the results show that there is good agreement between the retrieved wind velocity and simulated wind velocity. The simulation and experimental test results show that FMZI is feasible as a frequency discriminator and can be suitable for direct Mie Doppler lidar, especially for satellite-based platform lidar due to its desirable characteristics, including its small volume, light weight, good stability and compact structure.

The real aerosol size distributions were obtained by aerodynamic particle sizer spectrometer (APS) in China YinChuan. The lidar ratios at wavelengths of 355 nm, 532 nm and 1064 nm were calculated using Mie theory. The effective radius of aerosol particles r eff and volume C / F ratio (coarse/fine) V c/f were retrieved from the real aerosol size distributions. The relationship between multiwavelength lidar ratios and particle r eff and V c/f were investigated. The results indicate that the lidar ratio is positive correlated to the particle r eff and V c/f . The lidar ratio is more sensitive to the coarse particles. The short wavelength lidar ratio is more sensitive to the particle V c/f and the long wavelength lidar ratio is more sensitive to the particle r eff . The wavelength dependency indicated that the lidar ratios decrease with increasing the wavelength. The lidar ratios are almost irrelevant to the shape and total particles of aerosol size distributions.

In this study, a multi-wavelength polarization lidar was developed at the Lidar Center for Atmosphere Remote Sensing, in Xi’an, China to study the vertical distribution of the optical and microphysical properties of smog aerosols. To better understand smog, two events with different haze conditions observed in January 2015 were analyzed in detail. Using these data, we performed a vertical characterization of smog evolution using the lidar range-squared-corrected signal and the aerosol depolarization ratio. Using inversion with regularization, we retrieved the vertical distribution of aerosol microphysical properties, including volume size distribution, volume concentration, number concentration and effective radius. We also used the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model to analyze aerosol sources during the two episodes. Our results show that the most polluted area in the lower troposphere during smog episodes is located below a height of 1 km above the ground level; under more severe smog conditions, it can be below 0.5 km. In the case of severe smog, we found a large number of spherical and fine particles concentrated in the very low troposphere, even below 0.5 km. Surprisingly, a dust layer with a slight depolarization ratio was observed above the smog layer.

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.

Different from the existing methods for estimating averaged slant visibility by lidar and the traditional Koschmieder visibility formula, a measurement method for slant visibility is fundamentally proposed in this paper that considers the correction of slant path scattered radiance. Lidar is adopted to provide aerosol parameters, including optical depth and scattering parameters, and the SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer) model is used to solve the radiative transfer equation to obtain the corresponding radiance distribution; thus, the corrected apparent brightness contrast between the object and background along the slant path is used to achieve accurate slant visibility. Based on the measurement principle of slant visibility, a theoretical simulation and an analysis of the slant path scattered radiance are performed, and the resulting slant visibility is studied in detail in this paper.

It is difficult to independently obtain aerosol optical parameters at the near-infrared wavelength using lidar. A new high-spectral-resolution technology is proposed to obtain the aerosol extinction coefficient profile at 1064 nm. The high-spectral-resolution detection method by extracting Mie scattering and suppressing Cabannes–Brillouin scattering is applied in the lidar at 1064 nm to improve the detection signal-to-noise ratio. The system parameters of near-infrared high-spectral-resolution LiDAR (N HSRL) must be calibrated in this method; then, the optical parameters are accurately deduced. The effect of the system parameters (transmittances of the spectral filter for molecule and aerosol) on the detection results in this method is discussed and analysed. The transmittance of the spectral filter for aerosol scattering is a key parameter in the retrieval of the extinction coefficient, and the sensitivity of the inversion results to the transmittance is analysed and discussed. The method to distinguish the large deviation data of the extinction coefficient is discussed and provided, and the third derivative of the optical thickness profile is adopted to determine the data. According to the characteristics of the inversion signal, the method to correct the extinction coefficient profile is also presented. The correction algorithm can obviously increase the inversion accuracy of the extinction coefficient. The 1064-nm N HSRL Lidar was developed at Xi'an University of Technology. A dual-channel Fabry-Perot Etalon was designed and used to extract the aerosol Mie scattering signal and suppress Cabannes–Brillouin scattering in this N HSRL. The N HSRL lidar observations were performed, and extinction coefficient profiles at 1064 nm were obtained. The results demonstrate that the method can obtain an accurate profile of the extinction coefficients.

Mie lidar is a powerful tool for detecting the optical properties of atmospheric aerosols. However, there are two unknown parameters in the Mie lidar equation: the extinction coefficient and the backscattering coefficient. In the common methods for solving the equation, it is necessary to make assumptions about the relationship between the two unknown parameters. These assumptions will reduce the detection precision of extinction coefficient. In view of this, the back propagation (BP) neural network is used to retrieve extinction coefficient from the Mie scattering signal of lidar. Firstly, the structure and main parameters of the BP network are designed according to the practical application. In order to improve the convergence speed and prevent falling into local minima, the initial weights and thresholds of BP network are optimized by genetic algorithm (GA). Then the GA-BP network is trained with Mie scattering signal and the extinction coefficient retrieved by Raman method. Thus the mathematical relationship between Mie scattering signal and the extinction coefficient is stored in the BP network. The trained GA-BP network is then used to retrieve the extinction coefficient from Mie scattering signal in different conditions and the applicability of the GA-BP network is researched. The research will promote the development of Mie lidar retrieving algorithm.

High-spectral-resolution lidar plays an important role in the measurement of aerosol distributions and variations for understanding the influence on the local environment. The multi-mode high-spectral-resolution lidar is a new type of high-spectral-resolution lidar for fine detection of aerosol optical properties, which uses the multilongitudinal-mode pulsed laser rather than the single longitudinal mode laser. Considering the Mie-Rayleigh scattering signals excited by the multi-longitudinal-mode laser have the periodic characteristics, the tunable MachZehnder interferometer is selected as the optical discriminator in the construction of multi-mode high-spectralresolution lidar. In order to minimize the effect of divergence angle on the transmittance function, a filedcompensated Mach-Zehnder interferometer is designed, which has the complementary outputs to realize the transmission and suppression of Mie scattering signals respectively. The optimal optical path difference of the MachZehnder interferometer should be twice of the cavity length of the Nd:YAG pulsed laser. The capability of the multimode high-spectral-resolution-lidar has been verified using the standard atmospheric model, the simulation results show that the proposed system can achieve the accurate measurement of aerosol optical properties up to 10km.

All-day atmospheric water vapor content measurements determined by Raman lidar and a sunphotometer were combined to investigate the all-day variation characteristics in the water vapor distribution in Xi&rsquo, an, China (34.233&deg, N, 108.911&deg, E). To enhance the daytime lidar performance, the wavelet threshold de-noising method is used to filter out the strong solar background light, and effective denoised results are demonstrated with the following optimization: wavelet sym6, the improved threshold function, and the improved threshold selection. The denoised system signal-to-noise ratio (SNR) for the water vapor daytime measurement is validated, with an enhancement of ~3.4 times up to a height of 3 km compared to that of the original signal. The time series of the atmospheric water vapor mixing ratio profiles and the obtained precipitable water vapor (PWV) measured by Raman lidar are used to reveal the temporal and spatial variations in water vapor, and the comparisons with the total column water vapor content (TCWV) measured by a sunphotometer validate the daytime variation trend of the water vapor. All-day continuous observations clearly present a consistent variation trend in the water vapor between the sunphotometer and Raman lidar measurements. The correlation analysis between TCWV and PWV at the layers below 850 hPa and below 700 hPa yields a good positive correlation coefficient (&gt, 0.75), indicating that PWV determination in the bottom layer by Raman lidar can directly reflect the variations in the total water vapor content. Moreover, different diurnal variation trends in water vapor are also observed, that is, a downward trend from the afternoon to the night, or a tendency of being high in the morning and afternoon and low at noon, demonstrating the high temporal-spatial variation characteristics of water vapor and close correlation with weather changes. The results reflected and validated that the diurnal variation in water vapor is complicated and can be an indicator of the weather to a certain extent.

The absolute measurement technique for atmospheric temperature can avoid the calibration process and improve the measurement accuracy. To achieve the rotational Raman temperature lidar of absolute measurement, the two-stage parallel multi-channel spectroscopic filter combined a first-order blazed grating with a fiber Bragg grating is designed and its performance is tested. The parameters and the optical path structure of the core cascaded-device (micron-level fiber array) are optimized, the optical path of the primary spectroscope is simulated and the maximum centrifugal distortion of the rotational Raman spectrum is approximately 0.0031 nm, the centrifugal ratio of 0.69p. The experimental results show that the channel coefficients of the primary spectroscope are 0.67, 0.91, 0.67, 0.75, 0.82, 0.63, 0.87, 0.97, 0.89, 0.87 and 1 by using the twelfth channel as a reference and the average FWHM is about 0.44 nm. The maximum deviation between the experimental wavelength and the theoretical value is approximately 0.0398 nm, with the deviation degree of 8.86p. The effective suppression to elastic scattering signal are 30.6, 35.2, 37.1, 38.4, 36.8, 38.2, 41.0, 44.3, 44.0, 46.7 dB. That means, combined with the second spectroscope, the suppression at least is up to 65 dB. Therefore we can fine extract single rotational Raman line to achieve the absolute measurement technique.

Atmospheric temperature is one of the important parameters for the description of the atmospheric state. Most of the detection approaches to atmospheric temperature monitoring are based on rotational Raman scattering for better understanding atmospheric dynamics, thermodynamics, atmospheric transmission, and radiation. In this paper, we present a fine-filter method based on wavelength division multiplexing, incorporating a fiber Bragg grating in the visible spectrum for the rotational Raman scattering spectrum. To achieve high-precision remote sensing, the strong background noise is filtered out by using the secondary cascaded light paths. Detection intensity and the signal-to-noise ratio are improved by increasing the utilization rate of return signal form atmosphere. Passive temperature compensation is employed to reduce the temperature sensitivity of fiber Bragg grating. In addition, the proposed method provides a feasible solution for the filter system with the merits of miniaturization, high anti-interference, and high stability in the space-based platform.

A combination of more than two years of water vapor lidar data with back trajectory analysis using the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model was used to study the long-range transport of air masses and the water vapor distribution characteristics and variations over Xi’an, China (34.233° N, 108.911° E), which is a typical city in Northwest China. High-quality profiles of the water vapor density were derived from a multifunction Raman lidar system built in Xi’an, and more than 2000 sets of profiles with >400 nighttime observations from October 2013 to July 2016 were collected and used for statistical and quantitative analyses. The vertical variations in the water vapor content were discussed. A mutation height of the water vapor exists at 2–4 km with a high occurrence rate of ∼60% during the autumn and winter seasons. This height reflects a distinct stratification in the water vapor content. Additionally, the atmospheric water vapor content was mainly concentrated in the lower troposphere, and the proportion of the water vapor content at 0.5–5 km accounted for 80%–90% of the total water vapor below 10 km. Obvious seasonal variations were observed, including large water vapor content during the spring and summer and small content during the autumn and winter. Combined with back trajectory analysis, the results showed that markedly different water vapor transport pathways contribute to seasonal variations in the water vapor content. South and southeast airflows dominated during the summer, with 30% of the 84 trajectories originating from these areas; however, the air masses during the winter originated from the north and local regions (64.3%) and from the northwest (27%). In addition, we discussed variations in the water vapor during fog and haze weather conditions during the winter. A considerable enhancement in the mean water vapor density at 0.5–3 km exhibited a clear positive correlation (correlation coefficient >0.8) with the PM2.5 and PM10 concentrations. The results indicate that local airflow trajectories mainly affect water vapor transport below the boundary layer, and that these flows are closely related to the formation of fog and haze events in the Xi’an area.

For sharing the Mie scattering lidar profile data comes different lidar system, one of key challenge is tacking the heterogeneous format. In this paper, we analyses the temporal and spatial characteristics and two-dimensional structure of the scanning Mie lidar profile data. Based on the principle of scanning Mie lidar, and the meteorological of atmospheric parameters, we proposed a general data standardization and fill method for missing space. Experimental results shows that the method can accurately fill the space position of missing data, and can make scanning Mie lidar profile data standardized. It has realistic significance for sharing and analyzing of atmospheric monitoring lidar data.

In order to investigate the aerosol variability over the southwest region of Slovenia, an ultraviolet scanning elastic backscatter LiDAR was utilized to make the vertical scan for atmospheric probing. With the assumption of horizontal atmospheric homogeneity, aerosol optical variables were retrieved from the horizontal pixel data points of two-dimensional range-height-indicator (RHI) diagrams by using a multiangle retrieval method, in which optical depth is defined as the slope of the resulting linear function when height is kept constant. To make the data retrieval feasible and precise, a series of key procedures complemented the data processing, including construction of the RHI diagram, correction of Rayleigh scattering, assessment of horizontal atmospheric homogeneity and retrieval of aerosol optical variables. The measurement example demonstrated the feasibility of the ultraviolet scanning elastic backscatter LiDAR in the applications of the retrieval of aerosol extinction and determination of the atmospheric boundary layer height. Three months’ data combined with the modeling of air flow trajectories using Hybrid Single Particle Lagrangian Integrated Trajectory Model were analyzed to investigate aerosol variability. The average value of aerosol extinction with the presence of land-based air masses from the European continent was found to be two-times larger than that influenced by marine aerosols from the Mediterranean or Adriatic Sea.

Fringe-imaging Fabry–Perot interferometer (FIFPI) and fringe-imaging Mach–Zehnder interferometer (FIMZI) used as frequency discriminator for incoherent molecular Doppler lidar were analyzed, respectively. For a pure molecular backscattered signal, performances (wind measurement sensitivity and signal-to-noise ratio) of both FIFPI and FIMZI systems were simulated based on the U.S. standard atmospheric model. Comparisons of two systems were made under the same emitting and receiving parameters with certain wind speed dynamic range. Simulated results show that, though relatively lower sensitivity to Doppler shift, the single-channel FIMZI system provides a factor of 1.3 times smaller error in the horizontal wind velocity than that of FIFPI at a range of 20 km. We expect that the FIMZI frequency discriminator would provide an effective technique to improve the measurement accuracy for incoherent molecular Doppler lidar.

Accurate aerosol optical properties could be obtained via the high spectral resolution lidar (HSRL) technique, which employs a narrow spectral filter to suppress the Rayleigh or Mie scattering in lidar return signals. The ability of the filter to suppress Rayleigh or Mie scattering is critical for HSRL. Meanwhile, it is impossible to increase the rejection of the filter without limitation. How to optimize the spectral discriminator and select the appropriate suppression rate of the signal is important to us. The HSRL technology was thoroughly studied based on error propagation. Error analyses and sensitivity studies were carried out on the transmittance characteristics of the spectral discriminator. Moreover, ratwo different spectroscopic methods for HSRL were described and compared: one is to suppress the Mie scattering; the other is to suppress the Rayleigh scattering. The corresponding HSRLs were simulated and analyzed. The results show that excessive suppression of Rayleigh scattering or Mie scattering in a high-spectral channel is not necessary if the transmittance of the spectral filter for molecular and aerosol scattering signals can be well characterized. When the ratio of transmittance of the spectral filter for aerosol scattering and molecular scattering is less than 0.1 or greater than 10, the detection error does not change much with its value. This conclusion implies that we have more choices for the high-spectral discriminator in HSRL. Moreover, the detection errors of HSRL regarding the two spectroscopic methods vary greatly with the atmospheric backscattering ratio. To reduce the detection error, it is necessary to choose a reasonable spectroscopic method. The detection method of suppressing the Rayleigh signal and extracting the Mie signal can achieve less error in a clear atmosphere, while the method of suppressing the Mie signal and extracting the Rayleigh signal can achieve less error in a polluted atmosphere.

Ontology is an effective method to solve the problem of heterogeneous data in lidar measurements. Due to complexity and diversity of data structure, traditional method of ontology storage cannot be directly applied to lidar data. In this work, we proposed a novel ontology storage model based on the object-oriented data model, in which the mapping mechanism was established from ontology of lidar data to the object-oriented data model. A new storage model of lidar data is then obtained by a combination of the characteristics of lidar data and the syntax of OWL DL. Compared to the traditional method of ontology storage, we believe that the new storage model can better serve the sharing of lidar data.

A complex optical system used in polarization lidars often modifies the input polarization of the return signal so that it may significantly impact depolarization estimates and introduce errors to polarization lidar measurements. In most cases, retardation, depolarization, and misalignment of the system exist at the same time and interact with each other. Polarization effects of the system cannot be represented by a simple correction coefficient, so they cannot be removed using a traditional calibration method. Detailed analysis and correction technologies were provided to remove systematic biases in estimating depolarization values from a polarization lidar owing to multiple optical components. The Mueller matrices from an emitter to a receiver were calculated, and the expression for an aerosol depolarization parameter including system polarization effects was derived and obtained. In addition, the correction algorithm based on the Mueller matrix was introduced and provided. A polarization lidar was established, and the polarization characteristics of its optical components were measured with a laboratory ellipsometer; then, the Mueller matrix of the receiver was calculated and obtained. Lidar observations were performed, and our correction algorithm was applied to lidar field data. The results show that the correction method can significantly remove systematic polarization effects.

Aiming at the detection of water vapor mixing ratio, particle linear depolarization ratio, extinction coefficient and cloud information, the Water vapor, Cloud and Aerosol Lidar (WVCAL) was developed by the lidar group at Ocean University of China. The Lidar consists of transmitting subsystem, receiving subsystem, data acquisition and controlling subsystem and auxiliary subsystem. These parts were presented and described in this paper. For the measurement of various physical properties, three channels including Raman channel, polarization channel and infrared channel are integrated in this Lidar system. In this paper, the integration and working principle of these channels is introduced in details. Finally, a measurement example which was operated in coastal area-Qingdao, Shandong province, during 2014 is provided.

Aim to the current situation that the haze distribution detection is limited by network of point-type instruments, a three dimension scanning micro pulse lidar is researched on the basis of the Mie scattering theory of atmospheric particles. In order to strengthen detective ability of fine particles having a significant effect on human respiratory system, we choose a diode-pumped Nd:YAG solid laser with 532-nm wavelength and wind cooled technique as excited optical source to actualize lidar miniaturization. The pulse energy of 50 μJ and pulse repetitive frequency of 1 kHz are configured to ensure the eye-safety and high temporal-spatial resolution, while the lidar operates in the horizontal scanning mode. A Cassegrain telescope with clear aperture of 254 mm is utilized to collect the backscattering signal for portable multi-location observation. The lidar echo signal is filtered through an interference filter with passed bandwidth of 0.2 nm to implement all-time efficient detection. The experimental observation of atmospheric particle distribution is carried out in horizontal scanning mode. Each plane- position-indication of atmospheric particle distribution contains approximately 300 profiles in the horizontal plane within 6-min interval. Experimental results show that this lidar prototype can probe the space distribution of atmospheric particle with the range of 6 km, and that the influence of industrial production on the atmospheric particle density is 2-3 times as much as that of human activity.

To evaluate the potential of Raman lidar observations for measuring precipitable water vapor (PWV), PWV variations and distribution characteristics were investigated in Xi’an (34.233°N, 108.911°E), and its comparisons with meteorological parameters were also analysed. Comparisons of lidar PWV with radiosonde PWV verified the ability and accuracy of using Raman lidars for PWV measurements. The diurnal and monthly variation trends in PWV in different layers are first discussed via the statistical analysis of lidar data from November 2013 to July 2016; different proportions of PWV were found in different layers, and the PWV in each layer presented a slight diurnal change trend and consistent seasonal variation, which was relatively rich in summer, less so in spring and autumn, and relatively deficient in winter. Furthermore, correlation analyses between lidar PWV and meteorological parameters are explored. Water vapor pressure and surface temperature revealed the same inter-seasonal oscillation of PWV, with a correlation coefficient of ~0.90. However, incomplete synchronization was found between PWV and relative humidity and precipitation parameters. Higher humidity appeared in the late summer and the beginning of autumn of each year, which was also the case for precipitation and precipitation efficiency. In addition, atmospheric water vapor density profiles and the obtained PWV by Raman lidar are discussed employing a rainfall case, and a comprehensive analysis with meteorological parameters is undertaken. The intensifying characteristics of vertical change in water vapor and the accumulation of PWV in the lower troposphere can be captured by lidar before the onset of rainfall. In contrast to the obvious diurnal change trend, such meteorological parameters as relative humidity, water vapor pressure, and dew-point temperature difference are accompanied with stable trends with a change rate of close to 0 in the rainfall processes; they also show high correlated variations with lidar PWV. Thus, with the advantage of lidar detection, investigation of water vapor profiles and PWV by Raman lidar, and the comprehensive correlation analyses with synchronic meteorological parameters can prove to be good indications of rainfall.

In order to improve accuracy of aerosol measurements, a novel method using twin scanning lidars is presented; this method is able to overcome the incomplete overlap range of vertical lidar as well as provide 2D spatial distributions. The scanning lidar setups in the opposite directions are employed as remote sensing tools. Aerosol measurements are performed with cross scanning from the ground to the height of interest. Aerosol optical properties are retrieved using numerical approximation, in which differences between the measured values and the constructed values of the logarithmic range-square-corrected lidar data in the cross-scanning region are minimized. In the data retrieval, we utilize a matrix formulation, in which a Cartesian 2D range-height-indicator diagram is constructed. To verify this method, scanning measurements by ultraviolet Mie scanning lidar performed at different time intervals were taken as the cross-scanning measurements from the twin scanning lidars. With the retrieved spatial distributions of aerosol optical properties, such as aerosol backscatter, aerosol extinction, and lidar ratio, the regional aerosol studies showed that aerosol loading was relatively small and in the presence of multiple layers, which may be influenced by airflow from long-range transportation and cause a large impact on the local environment. To conclude, the presented method using twin scanning lidars is feasible for aerosol measurement in the application of horizontally atmospheric inhomogeneity.

Aiming at the detection of atmospheric water vapor mixing ratio, depolarization ratio, backscatter coefficient, extinction coefficient and cloud information, the Water vapor, Cloud and Aerosol Lidar (WACAL) is developed by the lidar group at Ocean University of China. The lidar consists of transmitter, receiver, data acquisition and auxiliary system. For the measurement of various atmospheric physical properties, three channels including Raman channel, polarization channel and infrared channel are integrated in WACAL. The integration and working principle of these channels are introduced in details. The optical setup, the housekeeping of the system and the data retrieval routines are also presented. After the completion of the construction of the lidar, the WACAL system was installed in Ocean University of China (36.165°N, 120.5°E), Qingdao for the measurement of atmosphere during 2013 and 2014. The measurement principles and some case studies corresponding to various atmospheric physical properties are provided. Finally, the result of one continuous measurement example operated on 13 June 2014 is presented. The WACAL can measure the aerosol and cloud optical properties as well as the water vapor mixing ratio. It is useful for studying the direct and indirect effects of the aerosol on the climate change.

Telescopes in polarization lidar often modify the input polarization of the return signal, such that the telescope may significantly impact the depolarization estimates of aerosol and introduce error to the polarization lidar measurements. The error cannot be corrected by a traditional calibration constant. We present a method to correct the polarization effect of the telescope. We analyze the polarization effect of a telescope on the basis of the Mueller formalism, and introduce an algorithm for correcting the depolarization parameter of aerosol. A Newton telescope and a Cassegrain telescope are often chosen as the receiver in lidar. Their polarization models are established, and the Mueller matrices are calculated. The components of these matrices are dependent on wavelength, incident angle of the incoming light, and surface properties. The polarization impact of the telescope in lidar can be calibrated by a parameter, and the effects of different telescopes are discussed. The polarization crosstalk induced by the Newton telescope is obvious. The depolarization parameters change greatly with coating and wavelength, and they are calculated and presented. Whereas the crosstalk of a Cassegrain telescope is much smaller, the error can reach the level of 10−3 and can be negligible. The method presented in this paper could also be upgraded by taking into account all of the optical devices instead of only the telescope.