Application of the Ultraviolet Scanning Elastic Backscatter LiDAR for the Investigation of Aerosol Variability

Gao, Fei; Stanič, S.; Bergant, Klemen; Liu, Ying; Li, Songhui; Hua, Dengxin; Wang, Longlong

doi:10.3390/rs70506320

Cited by 7 publications

(3 citation statements)

References 33 publications

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“…As for the derivation of the nocturnal boundary layer in Warsaw, the lower detection limit at 195 m could have led to a slight overestimation of the derived values. However, even for scanning lidars, where the overlap is claimed to play a negligible role due to the measurement geometry, heights of the boundary layer between 0.5 and 2.4 km were reported for August to October over Slovenia [86], considered a continental climate of the Dfb type, such as Warsaw [80].…”

Section: Variability Of Yearly Mean Well-mixed Nocturnal and Residumentioning

confidence: 99%

Variability of the Boundary Layer Over an Urban Continental Site Based on 10 Years of Active Remote Sensing Observations in Warsaw

et al. 2020

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Atmospheric boundary layer height (ABLH) was observed by the CHM15k ceilometer (January 2008 to October 2013) and the PollyXT lidar (July 2013 to December 2018) over the European Aerosol Research LIdar NETwork to Establish an Aerosol Climatology (EARLINET) site at the Remote Sensing Laboratory (RS-Lab) in Warsaw, Poland. Out of a maximum number of 4017 observational days within this period, a subset of quasi-continuous measurements conducted with these instruments at the same wavelength (1064 nm) was carefully chosen. This provided a data sample of 1841 diurnal cycle ABLH observations. The ABLHs were derived from ceilometer and lidar signals using the wavelet covariance transform method (WCT), gradient method (GDT), and standard deviation method (STD). For comparisons, the rawinsondes of the World Meteorological Organization (WMO 12374 site in Legionowo, 25 km distance to the RS-Lab) were used. The ABLHs derived from rawinsondes by the skew-T-log-p method and the bulk Richardson (bulk-Ri) method had a linear correlation coefficient (R2) of 0.9 and standard deviation (SD) of 0.32 km. A comparison of the ABLHs obtained for different methods and instruments indicated a relatively good agreement. The ABLHs estimated from the rawinsondes with the bulk-Ri method had the highest correlations, R2 of 0.80 and 0.70 with the ABLHs determined using the WCT method on ceilometer and lidar signals, respectively. The three methods applied to the simultaneous, collocated lidar, and ceilometer observations (July to October 2013) showed good agreement, especially for the WCT method (R2 of 0.94, SD of 0.19 km). A scaling threshold-based algorithm was proposed to homogenize ceilometer and lidar datasets, which were applied on the lidar data, and significantly improved the coherence of the results (R2 of 0.98, SD of 0.11 km). The difference of ABLH between clear-sky and cloudy conditions was on average below 230 m for the ceilometer and below 70 m for the lidar retrievals. The statistical analysis of the long-term observations indicated that the monthly mean ABLHs varied throughout the year between 0.6 and 1.8 km. The seasonal mean ABLH was of 1.16 ± 0.16 km in spring, 1.34 ± 0.15 km in summer, 0.99 ± 0.11 km in autumn, and 0.73 ± 0.08 km in winter. In spring and summer, the daytime and nighttime ABLHs appeared mainly in a frequency distribution range of 0.6 to 1.0 km. In winter, the distribution was common between 0.2 and 0.6 km. In autumn, it was relatively balanced between 0.2 and 1.2 km. The annual mean ABLHs maintained between 0.77 and 1.16 km, whereby the mean heights of the well-mixed, residual, and nocturnal layer were 1.14 ± 0.11, 1.27 ± 0.09, and 0.71 ± 0.06 km, respectively (for clear-sky conditions). For the whole observation period, the ABLHs below 1 km constituted more than 60% of the retrievals. A strong seasonal change of the monthly mean ABLH diurnal cycle was evident; a mild weakly defined autumn diurnal cycle, followed by a somewhat flat winter diurnal cycle, then a sharp transition to a spring diurnal cycle, and a high bell-like summer diurnal cycle. A prolonged summertime was manifested by the September cycle being more similar to the summer than autumn cycles.

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Section: Variability Of Yearly Mean Well-mixed Nocturnal and Residumentioning

confidence: 99%

Variability of the Boundary Layer Over an Urban Continental Site Based on 10 Years of Active Remote Sensing Observations in Warsaw

et al. 2020

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“…at La Palma (Lombardi et al 2008), and the free troposphere can be considered free of aerosols most of the time, except for the possible occurrence of clouds, and stratospheric volcanic debris (García-Gil et al 2010). The Vertical Aerosol Optical Depth (VAOD) up to ht can be retrieved entirely from the LIDAR data, only if an absolute calibration of the system constant (Gao et al 2015):…”

Section: Parametermentioning

confidence: 99%

Characterizing the aerosol atmosphere above the Observatorio del Roque de los Muchachos by analyzing seven years of data taken with an GaAsP HPD-readout, absolutely calibrated elastic LIDAR

Fruck,

Gaug,

Hahn

et al. 2022

Preprint

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We present a new elastic LIDAR concept, based on a bi-axially mounted Nd:YAG laser and a telescope with HPD readout, combined with fast FADC signal digitization and offline pulse analysis. The LIDAR return signals have been extensively quality checked and absolutely calibrated. We analyze seven years of quasi-continuous LIDAR data taken during those nights when the MAGIC telescopes were operating. Characterization of the nocturnal ground layer yields zenith and azimuth angle dependent aerosol extinction scale heights for clear nights. We derive aerosol transmission statistics for light emitted from various altitudes throughout the year and separated by seasons. We find further seasonal dependencies of cloud base and top altitudes, but none for the LIDAR ratios of clouds. Finally, the night sky background light is characterized using the LIDAR photon backgrounds.

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“…In principle, the variance calculation models for evaluating the data distribution characteristics of lidar probing traces can be applied to any atmospheric lidar system. In this paper, the ultraviolet elastic scanning lidar was taken as the research object [23,24], and a probing profile with a summed result of 20 laser shots or the lidar scanning profiles with a fixed elevation angle was analyzed to calculate the spatial and temporal variance. Based on the variance calculation results, the techniques for evaluating and improving the lidar performance were studied and implemented.…”

Section: Data Distribution Characteristics Of the Lidar Probing Tracesmentioning

confidence: 99%

Evaluation and Improvement of Lidar Performance Based on Temporal and Spatial Variance Calculation

Gao

Zhu

et al. 2019

Applied Sciences

Self Cite

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Poisson distributions have the characteristic of equality between their variance and mean values. By constructing a calculation model of the temporal variance and spatial variance, the relationship between the variance and mean values of lidar analog data and photon-counting data can be analyzed. The calculation results show that the photon-counting data from far field have the distribution property of equality between the variances and the corresponding mean values, while the analog data for the whole probing traces do not. In this paper, by analyzing the distribution properties of the spatial variance and temporal variance of lidar data, the dead time of photon-counting data was estimated, and the threshold voltage of the photon-counting system and the linear working range of photomultiplier tube were evaluated. The results show that the linear working range of the high voltage for the photomultiplier tube in the ultraviolet elastic scanning lidar is between −500 V and −1000 V, and the dead time and threshold voltage of the photon-counting system in the Licel transient recorder are 3.488 ns and 1.20 mV, respectively. Meanwhile, a novel gluing method between analog data and photon-counting data is presented, based on the calculation results of the variance distribution of lidar data. The linear transfer coefficients were determined by minimizing the differences between the variance and mean of the transformed photon-counting data in the near filed with high signal to noise ratio. The glued data were distributed to express the atmospheric conditions uniformly.

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Application of the Ultraviolet Scanning Elastic Backscatter LiDAR for the Investigation of Aerosol Variability

Cited by 7 publications

References 33 publications

Variability of the Boundary Layer Over an Urban Continental Site Based on 10 Years of Active Remote Sensing Observations in Warsaw

Variability of the Boundary Layer Over an Urban Continental Site Based on 10 Years of Active Remote Sensing Observations in Warsaw

Characterizing the aerosol atmosphere above the Observatorio del Roque de los Muchachos by analyzing seven years of data taken with an GaAsP HPD-readout, absolutely calibrated elastic LIDAR

Evaluation and Improvement of Lidar Performance Based on Temporal and Spatial Variance Calculation

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