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Complexly distributed aerosol particles have significant impacts on climate and environmental changes. As one of the vital atmospheric power sources, the wind field deeply affects the distribution and transport of aerosol particles. For a more comprehensive investigation of the aerosols flux and transport mechanism, two retrieval methods of aerosol optical properties (backscatter coefficient and extinction coefficient at 1550 nm) from coherent Doppler lidar (CDL) observation are proposed in this paper. The first method utilizes the calculated aerosol backscatter coefficient (532 nm) from Mie-scattering lidar datasets and the iterative Fernald method to retrieve aerosol optical property profiles during joint measurements with CDL and Mie-scattering lidar. After verifying the correctness of the first method compared with AERONET datasets, we proposed the second retrieval method. Using the forward integral Fernald method with near-ground reference aerosol extinction coefficient calculated by atmospheric visibility, aerosol optical properties at 1550 nm could be obtained. Thirty-six-day joint measurements with two lidars were specially designed and conducted to verify the correctness of these retrieval methods. The validation results of these two methods indicate great performances, where the mean relative errors are 0.0272 and 0.1656, and the correlation coefficients are 0.9306 and 0.9197, respectively. In conclusion, the feasibility of these two retrieval methods extends the capability of CDL to detect aerosol optical properties and also provides a possibility to observe the aerosol distribution and transport process comprehensively, which is a great promotion of aerosol transport studies development. [ABSTRACT FROM AUTHOR]

The observation of the nocturnal boundary layer height (NBLH) plays an important role in air pollution and monitoring. Through 39 d of heavy pollution observation experiments in Beijing (China), as well as an exhaustive evaluation of the gradient, wavelet covariance transform, and cubic root gradient methods, a novel algorithm based on the cluster analysis of the gradient method (CA-GM) of lidar signals is developed to capture the multilayer structure and achieve night-time stability. The CA-GM highlights its performance compared with radiosonde data, and the best correlation (0.85), weakest root-mean-square error (203 m), and an improved 25 % correlation coefficient are achieved via the GM. Compared with the 39 d experiments using other algorithms, reasonable parameter selection can help in distinguishing between layers with different properties, such as the cloud layer, elevated aerosol layers, and random noise. Consequently, the CA-GM can automatically address the uncertainty with multiple structures and obtain a stable NBLH with a high temporal resolution, which is expected to contribute to air pollution monitoring and climatology, as well as model verification. [ABSTRACT FROM AUTHOR]

An iterative method, based on a derived inverse relationship between atmospheric backscatter coefficient and aerosol lidar ratio, is proposed to invert the lidar ratio profile and aerosol extinction coefficient. The feasibility of this method is investigated theoretically and experimentally. Simulation results show the inversion accuracy of aerosol optical properties for iterative method can be improved in the near-surface aerosol layer and the optical thick layer. Experimentally, as a result of the reduced insufficiency error and incoherence error, the aerosol optical properties with higher accuracy can be obtained in the near-surface region and the region of numerical derivative distortion. In addition, the particle component can be distinguished roughly based on this improved lidar ratio profile. [ABSTRACT FROM AUTHOR]

The remote sensing of water clouds is useful for studying their spatial and temporal variations and constraining physical processes in climate and weather prediction models. However, radar-only detection provides inadequate information for the cloud droplet size distribution. Here, we propose a novel lookup-table method, which combines lidar (1064, 532 nm) and radar (8.6 mm) to retrieve profiles of cloud optical (backscatter coefficient and extinction coefficient) and microphysical properties (effective diameter and liquid water content). Through the iteration of the extinction-to-backscatter ratio, more continuous cloud optical characteristics can be obtained. Sensitivity analysis shows that a 10% error of the lidar constant will lead to a retrieval error of up to 30%. The algorithm performed precise capture of the ideal cloud signal at a specific height and at full height and the maximum relative error of the backscatter coefficients at 1064 nm and 532 nm were 6% and 4%, respectively. With the application of the algorithm in the two observation cases on single or multiple cloud layers, the results indicate that the microphysical properties mostly agree with the empirical radar measurements but are slightly different when larger particles cause signal changes of different extents. Consequently, the synergetic algorithm is capable of computing the cloud droplet size distribution. It provides continuous profiles of cloud optical properties and captures cloud microphysical properties well for water cloud studies. [ABSTRACT FROM AUTHOR]

The types of aerosols are essential for estimating radiative forcing effects, improving the lidar retrieval algorithms, and identifying aerosol sources. However, it is difficult to categorize the aerosols with similar optical properties based on lidar techniques. In this study, an approach was proposed to distinguish desert dust (DD), mineral dust (MD), air pollution aerosols (APA), and their mixtures (DD&MD, DD&APA, MD&APA, DD&MD&APA). We established the fluorescence–Mie​ polarization lidar (FMPL) system to categorize three types of main aerosols using the customized fluorescence-to-Mie ratio (FMR) and volume depolarization ratio (VDR) in the experiments from September 2017 to December 2018. Then, the mixture of the aerosols was classified by combining backward trajectory analysis. The feasibility of this method was verified through five typical cases in the paper, and it is proved that the method could be employed to study air pollution issues based on FMPL, which could provide references for the meteorological investigation. • We established a fluorescence–Mie polarization lidar system. • We defined Fluorescence-to-Mie ratio (FMR). • Aerosols were divided into seven types according to their FMR and VDR. [ABSTRACT FROM AUTHOR]

• A simple de-noising operation is implemented to increase the signal-to-noise ratio. • The operation avoids the subjectivity of the iterative number of iteration method. • The more accurate aerosol backscatter coefficient could be obtained in the near ground (< 2 km). • A higher effective detection altitude is obtained with the simple de-noising operation. The de-noising of lidar signal, especially for the range-dependent systematic noise, always affects the signal-to-noise ratio of lidar signal and the inversion accuracy of aerosol backscatter coefficient. To avoid this issue, a simple de-noising operation is implemented to increase the signal-to-noise ratio and obtain a more accurate aerosol backscatter coefficient. Theoretically, the subjectivity of the iterative number of iteration method can be avoided by the simple de-noising operation. And the feasibility of the simple de-noising operation is investigated by simulation and the routine lidar experimental data. In the near ground, the aerosol backscatter coefficient with higher accuracy of about 4–10 times could be obtained with the simple de-noising operation, compared with the traditional de-noising operation. Moreover, the long-term stability of the range-dependent systematic noise can be found by the experimental results, which avoids the frequent measurement of the systematic noise. In addition, a higher effective detection altitude is obtained with the simple de-noising operation. [ABSTRACT FROM AUTHOR]

Conventional double-grating monochromators used in pure rotational Raman (PRR) temperature LIDAR usually adopt the Littrow configuration to separate backscattered PRR lines. A mirror is added to this configuration, thereby producing the Littman configuration. The dispersion of the modified configuration is greater than thrice that of the Littrow configuration for incident angles larger than 60 deg. A spectroscopy system with a linear dispersion better than 0.9 mm / nm is designed for the 532-nm excitation laser wavelength, and the selected N2 PRR lines are effectively separated. The overall system is simulated using only off-the-shelf optical components, and the results show that the volume is smaller than 240 × 200 × 80 mm3. [ABSTRACT FROM AUTHOR]

We propose a new calibration method for pure rotational Raman (PRR) lidar temperature profiling based on the different temperature sensitivities of Stocks and anti‐Stocks PRR lines. This method reconstructs the expression of the differential backscatter cross section according to the temperature dependencies of each component and forms a temperature factor and a calibration factor in the intensity ratio. With these factors, the temperature is retrievable from the lidar return. The effectiveness and accuracy of the proposed method have been verified through simulations and experiments. The inversion error can be reduced by ~50% compared with the commonly used calibration methods in weak signal‐to‐noise situations. Plain Language Summary: A new calibration method for temperature detecting by a pure rotational Raman lidar is proposed. Based on the properties of the pure rotational Raman spectrum, a calibration factor is formed in the return signals and is used to retrieve the temperature in combination with local radiosonde. Both simulations and experiments validate the effectiveness of our proposed method. The inversion errors are reduced by ~50% compared with the traditional fitting methods in weak signal‐to‐noise environments. Key Points: A novel robust calibration method for pure rotational Raman lidar temperature profiling is proposed in this workThe method focuses on the difference in temperature sensitivity between the two branches of the Raman spectrumThe proposed method provides higher accuracy compared with the traditional fitting methods under weak signal‐to‐noise ratio conditions [ABSTRACT FROM AUTHOR]

For pure rotational Raman temperature-measurement lidar, the suppression of elastic signals has always been a core technical issue. In practice, however, the surge of aerosol concentration, such as mist, haze, and short-time air pollution, tends to cause the intensity of the elastic scattering light to exceed the generally applicable suppression ratio of the lidar system, and the leaked elastic signal will result in some distortions of the Raman signals, especially in the near-field region. To solve this problem, here we propose to correct the signal distortion by forming a correction coefficient from the expression of the signal intensity ratio of the two Raman channels, which has been proven to be highly correlated with the intensity of the elastic signals. Simulated and experimental verification have been performed on the proposed method. The results demonstrated that using this coefficient to correct the Raman data will significantly improve the signal quality and the corresponding temperature inversion accuracy. Meanwhile, the correction coefficient can also be applied to modify the lidar returns in a similar atmospheric environment so as to enhance the detecting performance of the pure rotational Raman lidar in polluted air condition. [ABSTRACT FROM AUTHOR]

Highlights • A fluorescence-Mie lidar for observing fluorescent aerosols was developed in Beijing. • The spatio-temporal variability of fluorescent aerosols in the lower atmosphere was investigated. • The LIF results was validated by backward trajectories and local pollutants emission data. • The mean ratio of LIF-to-Mie is good correlated with PM2.5 concentration. Abstract An integrated fluorescence-Mie lidar was built to observe fluorescent aerosol at the altitude below 1.5 km. It was constructed with the third harmonic of Nd:YAG laser (355 nm), a Newtonian telescope and two single-channel photomultiplier tubes. Based on the Mie scattering theory and laser-induced fluorescence (LIF) theory, the vertical distribution of fluorescent aerosol was retrieved by the LIF-to-Mie signal ratio. As a common factor, the geometric form factor of the system was cancelled out when dividing LIF signal by Mie signal, therefore the high-precision of the LIF-to-Mie signal ratio was obtained in the lower atmosphere. After continuous observations under different air quality conditions, the time-height indications of fluorescent aerosol were obtained. The fluorescence efficiency was preliminary estimated. By combining the backward trajectories analysis and the local emission data of SO 2 and NO 2 , the time-height indications were analyzed for investigating the sources of fluorescent aerosol. The correlation between PM2.5 concentration and the mean value of LIF-to-Mie signal ratio was also studied. The good agreement between the results indicate that the above mentioned method can be employed to analyze the spatio-temporal distribution of fluorescent aerosol and has a great potential in meteorological application. [ABSTRACT FROM AUTHOR]

A straightforward method is presented for the determination of the geometric form factor in Raman–Mie lidar by using elastic backscatter signal from different altitudes and derived particle backscatter coefficients. The theory is briefly described. The error of this method is discussed and a comparison with the method proposed by Wandinger and Ansmann indicates the improved accuracy of the new method. The effect of the determined geometric form factor error on aerosol extinction coefficient retrieval is further discussed. The results of the experiment show that the derived aerosol extinction coefficient profile is less affected by the geometric form factor error when the atmospheric aerosol concentration is higher. [ABSTRACT FROM AUTHOR]

Simulation of the coherent Doppler LiDAR signal requires accurate computation of homogeneous random wind fields. Based on complex random processes with specified spatial statistics given by the covariance function, an improved real correlation random wind field algorithm is proposed for real random processes, the simulation results are compared with the given covariance function and the real correlation algorithm conforms to the given covariance function quite well. Moreover, to validate the accuracy of the real correlation algorithm, the estimation of the turbulence energy dissipation rate (TEDR) from the Doppler spectrum width is described. Using the generated real random wind field, the estimation relative bias of the TEDR is retrieved. The accuracy of the simulation is in accordance with the experimental results. [ABSTRACT FROM AUTHOR]

Abstract: The telescope is a key optical component which largely affects the signal intensity in coherent Doppler Lidar. In the paper the normalized signal to noise ratio(SNR) as a function of range z and diameter D of the telescope is investigated for pulsed coherent wind lidar, then the telescope aperture requirement for 300km orbit is calculated and presented. After that the initial structure parameters for space-based (40×) off-axis telescope are obtained with the PW method, furthermore, the initial structure has been optimized by the Zemax software. The telescope's RMS wavefront error is optimized to be less than 1/10λ (2μm), and the tolerance requirement is discussed. The designed structure of the telescope is simple and compact, can be easily applied to other similar fields due to its high portability. [Copyright &y& Elsevier]