Search

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. [ABSTRACT FROM AUTHOR]

Over the past three decades, China has seen aerosol levels substantially surpass the global average, significantly impacting regional climate. This study investigates the long-term and seasonal variations of aerosols in the Huai River Basin (HRB) using MODIS, CALIOP observations from 2007 to 2021, and ground-based measurements. A notable finding is a significant decline in the annual mean Aerosol Optical Depth (AOD) across the HRB, with MODIS showing a decrease of approximately 0.023 to 0.027 per year, while CALIOP, which misses thin aerosol layers, recorded a decrease of about 0.016 per year. This downward trend is corroborated by improvements in air quality, as evidenced by PM2.5 measurements and visibility-based aerosol extinction coefficients. Aerosol decreases occurred at all heights, but for aerosols below 800 m, with an annual AOD decrease of 0.011. The study also quantifies the long-term trends of five major aerosol types, identifying Polluted Dust (PD) as the predominant frequency type (46%), which has significantly decreased, contributing to about 68% of the total AOD reduction observed by CALIOP (0.011 per year). Despite this, Dust and Polluted Continental (PC) aerosols persist, with PC showing no clear trend of decrease. Seasonal analysis reveals aerosol peaks in summer, contrary to surface measurements, attributed to variations in the Boundary Layer (BL) depth, affecting aerosol distribution and extinction. Furthermore, the study explores the influence of seasonal wind patterns on aerosol type variation, noting that shifts in wind direction contribute to the observed changes in aerosol types, particularly affecting Dust and PD occurrences. The integration of satellite and ground measurements provides a comprehensive view of regional aerosol properties, highlighting the effectiveness of China's environmental policies in aerosol reduction. Nonetheless, the persistence of high PD and PC levels underscores the need for continued efforts to reduce both primary and secondary aerosol production to further enhance regional air quality. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Fabry–Perot interferometer (FPI) plays a crucial role as the frequency discriminator in the incoherent Doppler wind lidar. However, in the practical receiver system, reflections occurring between optical elements introduce non-normal incident components in the light beams passing through the FPI. This phenomenon results in the deformation of the FPI transmission spectral lines. Based on that, a theoretical model has been developed to describe the transmission spectrum of the FPI when subjected to obliquely incident light beams with a divergence angle. By appropriately adjusting the model parameters, the simulated transmission spectrum of the FPI edge channels can coincide with the experimentally measured FPI spectral line. Subsequently, the impact of deformations in the transmission spectrum of the two edge channels on wind measurements is evaluated. The first implication is a systematic shift of 30.7 m/s in line-of-sight (LOS) wind velocities. This shift is based on the assumption that the lidar echo is solely backscattered from atmospheric molecules. The second consequence is the inconsistency in the response sensitivities of Doppler frequency shift between Rayleigh signals and Mie signals. As a result, the lidar system fails to fully achieve its initial design objectives, particularly in effectively suppressing interference from Mie signals. The presence of aerosols can introduce a significant error of several meters per second in the measurement of LOS wind velocity. [ABSTRACT FROM AUTHOR]

This paper presents a method for instantaneous measurement of Fabry-Parot(F-P) transmittance curve. Compared with the previous method, this method has many advantages, such as scanning-free, simple in structure and accuracy.

The side-scattering lidar based on the CCD camera is a powerful tool to measure the near- ground aerosol, which is most interesting for the environmental and meteorological departments. The inversion method for the side-scattering lidar is different from the conventional Fernald method due to the differences in two lidar equations. A new inversion method for the side-scattering lidar to retrieve the aerosol backscattering coefficient is proposed for the first time, which is based on the aerosol backscattering coefficient at the ground as a restriction condition. Numerical simulation is used to analyze the convergence of this new method. Case studies indicate that this new method is reasonable and feasible.REFERENCES

The Polarization Lidar has been developed for cirrus cloud optical properties measurement. The Nd-YAG laser is employed as emitting linear source and two channels are used for detecting back-scattering signals from cirrus cloud including two 532 nm Orthogonal Polarization channels. Measurements were carried out from December 2010, to February 2013. In this work, we consider the only linear depolarization ratio measured at a wavelength of 532 nm. The dependences of depolarization ratios on both the size of ice crystals and the distribution of their distortion angles were also calculated. These results were compared with each other and used for retrieving the microphysical parameters of cirrus clouds observed in Hefei.

Lidar technologies are widely used for retrieving microphysics of cirrus clouds, i.e. sizes, shapes and spatial orientation of ice crystals constituting the clouds. Interpretation of the lidar signals are based on the backscattered light. However, properties of the light backscattered by the ice crystals have not been well known and understood yet. The reason of this is that the problem of light scattering by the ice crystals much larger that incident wavelengths has not been solved satisfactorily yet because of great demands to computer resources. In this contribution we review the physical optics approximation as a prospective method to solve the light scattering problem on large nonspherical particles in lidar application.

The light scattering matrix is calculated for large dust particles with irregular shape and refractive index of 1.3116+i0.0. The scattering matrix in the backward direction needed for lidar studies is separately discussed. In this case, the obtained results for the lidar and depolarization ratios are in good agreement with experimental data. It is shown that for randomly oriented particles the number of particle orientations needed for numerical calculations by exact methods like DDA becomes a crucial parameter. In particular, for particles with size parameters larger than 40 the number of orientations should be more than 1000.

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. [ABSTRACT FROM AUTHOR]

High repetition rate lidar is typically equipped with a low-energy, high repetition rate laser, and small aperture telescopes. Therefore, it is small, compact, low-cost, and can be networked for observation. However, its data acquisition and control functions are generally not specially designed, and the data acquisition, storage, and control programs need to be implemented on an IPC (Industrial Personal Computer), which increases the complexity and instability of the lidar system. Therefore, this paper designs an integrated off-line echo signal acquisition system (IOESAS) for lidar developed based on SoC FPGA (System-On-Chip Field Programmable Gate Array). Using a hardware–software co-design approach, the system is implemented in a heterogeneous multi-core chip ZYNQ-7020 (integrated FPGA and ARM). The FPGA implements dual-channel echo data acquisition (gated counting and hardware accumulation). At the same time, the ARM performs laser control and monitoring, laser pointing control, pulse energy monitoring, data storage, and wireless transmission. Offline data acquisition and control software was developed based on LabVIEW, which can remotely control the status of the lidar and download the echo data stored in IOESAS. To verify the performance of the data acquisition system, IOESAS was compared with the photon counting card P7882 and MCS-PCI, respectively. The test results show that they are in good agreement; the linear correlation coefficients were 0.99967 and 0.99884, respectively. IOESAS was installed on lidar outdoors for continuous detection, and the system was able to work independently and stably in different weather conditions, and control functions were tested normally. The gating delay and gating width time jitter error are ±5 ns and ±2 ns, respectively. The IOESAS is now used in several small lidars for networked observations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

For ground-based lidars in atmospheric observation, their data acquisition unit and control unit usually work independently. They usually require the cooperation of large-volume, high-power-consumption Industrial Personal Computer (IPC). However, the space-borne lidar has high requirements on the stability and integration of the acquisition control system. In this paper, a new data acquisition and lidar control system (DALCS) was developed based on System-on-Chip Field-Programmable Gate Array (SoC FPGA) technology. It can be used in lidar systems with high repetition rate and photon-counting mode and has functions such as data storage, laser control, automatic collimation, wireless communication, and fault self-test. DALCS has two working modes: in online mode, the echo data collected by DALCS are transmitted to the computer for display in real-time and then stored with the current time as the file name; in offline mode, the data are stored in local non-volatile memory, which can be read remotely and can work autonomously when there is no IPC. The test results showed that in the frequency range of 0–70 M, the counting linearity of DALCS reached 0.9999, and the maximum relative error between the DALCS card and the standard signal source was 0.211%. The comparison results showed that the correlation coefficient between DALCS and MCS-PCI was as high as 0.99768. The DALCS was placed in a self-developed lidar sensor system for continuous observation, and the system worked stably under different weather conditions. The range-squared-corrected signal profiles obtained from the observations reflect the spatial and temporal distribution characteristics of aerosols and clouds well. This provides scheme verification and experimental support for the development of space-borne lidar data acquisition and control system. [ABSTRACT FROM AUTHOR]

In this article, a non-through metal–insulator–metal (MIM) waveguide that can excite fivefold Fano resonances is reported. The Fano resonances are obtained by the interaction between the modes excited by the square split-ring resonator (SSRC) and the bus waveguide. After a detailed analysis of the transmission characteristics and magnetic field strength of the structure using the finite element method (FEM), it was found that the independent tuning of Fano resonance wavelength and transmittance can be achieved by adjusting the geometric parameters of SSRC. In addition, after optimizing the geometric parameters, the refractive index sensing sensitivity (S) and figure of merit (FOM) of the structure can be optimal, which are 1290.2 nm/RIU and 3.6 × 104, respectively. Additionally, the annular cavity of the MIM waveguide structure can also be filled with biomass solution to act as a biosensor. On this basis, the structure can be produced for optical refractive index sensing in the biological, micro and nano fields. [ABSTRACT FROM AUTHOR]

Aerosol optical properties were continuously measured with the National Institute for Environmental Studies (NIES) compact Raman lidar over Beijing, China, from 15 to 31 December 2007. The results indicated that in a moderate pollution episode, the averaged aerosol extinction below 1 km height was 0.39 [+ or -] 0.15 [km.sup.-1] and the lidar ratio was 60.8 [+ or -] 13.5 sr; in heavy pollution episode, they were 1.97 [+ or -] 0.91 [km.sup.-1] and 43.7 [+ or -] 8.3 sr; in an Asian dust episode, they were 0.33 [+ or -] 0.11 [km.sup.-1] and 38.3 [+ or -] 9.8 sr. The total depolarization ratio was mostly below 10% in the pollution episode, whereas it was larger than 20% in the Asian dust episode. The distinct characteristics of aerosol optical properties in moderate and heavy pollution episodes were attributed to the difference in air mass trajectory and the ambient atmospheric conditions such as relative humidity. OCIS codes: 010.0010, 010.3640, 120.0280, 280.0280, 280.1120, 280.3640.

A movable multi-wavelength Raman lidar (TMPRL) was built in Hefei, China. Emitting with three wavelengths at 1064, 532, and 355nm, receiving three above Mie scattering signals and two nitrogen Raman signals at 386 and 607nm, and depolarization signal at 532nm, TMPRL has the capacity to investigate the height resolved optical and microphysical properties of aerosol and cloud. The retrieval algorithms of optical parameters base on Mie-Raman technique and the microphysical parameters based on Bayesian optimization method were also developed and applied to observed lidar data. Designing to make unattended operation and 24/7 continuous working, TMPRL has joined several field campaigns to study on the aerosol, cloud and their interaction researches. Some observed results of aerosol and cloud optical properties and the first attempt to validate the vertical aerosol size distribution retrieved by TMPRL and in-situ measurement by airplane are presented and discussed.

The interaction relationship between cloud and aerosol is studied via their optical depth and cloud effective radius based on ground-based remote sensors. By attenuated backscatter obtained by lidar the optical depth of cloud and aerosol is retrieved. Combing with liquid water path observed by microwave radiometer, the cloud number concentration and cloud effective radius is also retrieved based on the adiabatic hypothesis Cases studies shows that during the stable stratocumulus with interval precipitation period and aerosol with vertical motion, the cloud effective radius shows both negative and positive relationship with aerosol optical depth. It may be due to the difference of liquid water path of the cloud properties and shows complex interaction with aerosol.

In theory, lidar overlap factor can be derived from the difference between the particle backscatter coefficient retrieved from lidar elastic signal without overlap correction and the actual particle backscatter coefficient, which can be obtained by other measured techniques. The side-scatter signal using a CCD camera is testified to be a powerful tool to detect the particle backscatter coefficient in near ground layer during night time. In experiment, by combining side-scatter and backscatter signals the geometric form factor for vertically-pointing Mie lidar in 532 nm channel is determined successfully, which is corrected by an iteration algorithm combining the retrieved particle backscatter coefficient using CCD sidescatter method and Fernald method. In this study, the method will be expanded to 1064 nm channel in dual-wavelength Mie lidar during routine campaigns. The experimental results in different atmosphere conditions demonstrated that the method present in this study is available in practice.

A new method for independent calibration of water vapor Raman lidar by using additional measurements of elastic signals at water vapor Raman wavelength was introduced. The water vapor mixing ratio calibration constant was derived from nitrogen mixing ratio calibration constant and Rayleigh to water vapor Raman backscattering cross section ratio. The nitrogen mixing ratio calibration constant with uncertainties of 1~2% can be determined from the nitrogen mixing ratio measurement in an aerosolfree zone in the upper troposphere with the additional elastic measurement and nitrogen Raman measurement, the Rayleigh to water vapor Raman backscattering cross section ratio can be calculated with uncertainties of about 8%, or can be determined experimentally with uncertainties of less than 5%. Using the experimental cross section ratio, a total uncertainty of the water vapor calibration less than 6% is possible to achieve. Because this calibration method utilizes actual lidar signals in nitrogen and water vapor detection channels, the calibration can fully capture lidar state changes.

A method to calibrate the overlap factor of Lidar is proposed, named unmanned aerial vehicle correction (UAVC), which uses unmanned aerial vehicles (UAVs) to detect the vertical distribution of particle concentrations. The conversion relationship between the particulate matter concentration and the aerosol extinction coefficient is inverted by the high-altitude coincidence of the vertical detection profiles of the UAV and Lidar. Using this conversion relationship, the Lidar signal without the influence of the overlap factor can be inverted. Then, the overlap factor profile is obtained by comparing the signal with the original Lidar signal. A 355 nm Raman-Mie Lidar and UAV were used to measure overlap factors under different weather conditions. After comparison with the Raman method, it is found that the overlap factors calculated by the two methods are in good agreement. The changing trend of the extinction coefficient at each height is relatively consistent, after comparing the inversion result of the corrected Lidar signal with the ground data. The results show that after the continuously measured Lidar signal is corrected by the overlap factor measured by this method, low-altitude aerosol information can be effectively obtained. [ABSTRACT FROM AUTHOR]

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. Key Points: The magnitudes of local PM10 pollutions depend on various transport trajectories of dust aerosols as well as local meteorological conditionsDifferent dust transported heights are revealed by integrated observations of satellite remote sensing and ground‐based lidarThe spherical characteristics of dust‐related aerosols are identified by depolarization ratio of aerosols from lidar observation [ABSTRACT FROM AUTHOR]