Hailing Xie
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Hailing Xie has a total of 17 co-authors. Here are the top co-authors by number of shared publications:
- Damao Zhang
Pacific Northwest National Laboratory, Richland, Washington, USA
2 shared publications - Jennifer M. Comstock
Pacific Northwest National Laboratory, Richland, Washington, USA
1 shared publication - Jianping Huang
Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou 730000, China
1 shared publication - Jianrong Bi
Key Laboratory for Semi‐Arid Climate Change of the Ministry of Education College of Atmospheric Sciences Lanzhou University Lanzhou China
1 shared publication - Jingyi Tang
Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
1 shared publication Kang Yang
University of Colorado
1 shared publication
Latest Publications
- Open Access
- 16 September 2022
- Published by MDPI AG in Remote Sensing
- Vol. 14 (18) , 4638
Polar Aerosol Vertical Structures and Characteristics Observed with a High Spectral Resolution Lidar at the ARM NSA Observatory
Aerosol vertical distributions impact both the direct and indirect radiative effects of aerosols. High Spectra Resolution Lidar (HSRL) separates between atmospheric molecular signals and aerosol particle signals and therefore can provide reliable measurements of aerosol properties. Six years of HSRL measurements between 2014 and 2019 from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) atmospheric observatory at Utqiaġvik are used to statistically analyze Arctic aerosol vertical distributions. The annual cycle of aerosol vertical distributions in terms of aerosol particulate backscatter coefficient (), lidar scattering ratio (SR), and aerosol particulate depolarization ratio () profiles at the wavelength of 532 nm shows that Arctic Haze events are prevalent in later winter and spring at the NSA site. Mineral dust is frequently presented in strong aerosol layers in the spring, fall, and winter seasons. Over the summer season, the NSA site has large aerosol loadings that are dominated by small spherical aerosol particles.- 16 September 2022
- Published by MDPI AG in Remote Sensing
- Vol. 14 (18) , 4638
Open AccessPolar Aerosol Vertical Structures and Characteristics Observed with a High Spectral Resolution Lidar at the ARM NSA Observatory
Aerosol vertical distributions impact both the direct and indirect radiative effects of aerosols. High Spectra Resolution Lidar (HSRL) separates between atmospheric molecular signals and aerosol particle signals and therefore can provide reliable measurements of aerosol properties. Six years of HSRL measurements between 2014 and 2019 from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) atmospheric observatory at Utqiaġvik are used to statistically analyze Arctic aerosol vertical distributions. The annual cycle of aerosol vertical distributions in terms of aerosol particulate backscatter coefficient (), lidar scattering ratio (SR), and aerosol particulate depolarization ratio () profiles at the wavelength of 532 nm shows that Arctic Haze events are prevalent in later winter and spring at the NSA site. Mineral dust is frequently presented in strong aerosol layers in the spring, fall, and winter seasons. Over the summer season, the NSA site has large aerosol loadings that are dominated by small spherical aerosol particles. - 13 December 2021
- Published by Optica Publishing Group in Optics Express
- Vol. 29 (26) , 43502-43515
Afterpulse correction for micro-pulse lidar to improve middle and upper tropospheric aerosol measurements
Micro-pulse lidar (MPL) measurements have been widely used in atmospheric research over the past few decades. However, the MPL afterpulse noise has a large impact on the MPL aerosol measurement in the middle and upper troposphere, and an effective correction method is still lacking. Here, a new afterpulse correction approach is presented by using measurements with low-level optically thick clouds to act as the lids blocking atmospheric signals beyond the clouds completely. Examples are provided to illustrate the effectiveness of this correction method. Using one-year 2014 MPL measurements at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site, the impact of the correction on the aerosol measurements is quantified. The relative error (RE, %) of attenuated backscattering ratio (ABR) without the afterpulse correction is 30% and 190% at the height of 1.00 km and 9.00 km (AGL), and the RE is larger for weaker aerosol signals (ABR<2). The RE of linear depolarization ratio (LDR), which is significantly higher than that of ABR for a given aerosol layer, is highly non-linear above 3.00 km, with a value of 300%-900% for weak aerosols (ABR<2) above 3.00 km. Therefore, the afterpulse correction is critical for the middle and upper tropospheric aerosol observations. We demonstrated that our afterpulse correction can provide reasonable particle depolarization ratio (PDR) to properly identify dust aerosols. The newly developed method can be applied to long-term MPL measurements to support aerosol and mixed-phase/ice cloud interaction study at the NSA site.
- 13 December 2021
- Published by Optica Publishing Group in Optics Express
- Vol. 29 (26) , 43502-43515
Afterpulse correction for micro-pulse lidar to improve middle and upper tropospheric aerosol measurements
Micro-pulse lidar (MPL) measurements have been widely used in atmospheric research over the past few decades. However, the MPL afterpulse noise has a large impact on the MPL aerosol measurement in the middle and upper troposphere, and an effective correction method is still lacking. Here, a new afterpulse correction approach is presented by using measurements with low-level optically thick clouds to act as the lids blocking atmospheric signals beyond the clouds completely. Examples are provided to illustrate the effectiveness of this correction method. Using one-year 2014 MPL measurements at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site, the impact of the correction on the aerosol measurements is quantified. The relative error (RE, %) of attenuated backscattering ratio (ABR) without the afterpulse correction is 30% and 190% at the height of 1.00 km and 9.00 km (AGL), and the RE is larger for weaker aerosol signals (ABR<2). The RE of linear depolarization ratio (LDR), which is significantly higher than that of ABR for a given aerosol layer, is highly non-linear above 3.00 km, with a value of 300%-900% for weak aerosols (ABR<2) above 3.00 km. Therefore, the afterpulse correction is critical for the middle and upper tropospheric aerosol observations. We demonstrated that our afterpulse correction can provide reasonable particle depolarization ratio (PDR) to properly identify dust aerosols. The newly developed method can be applied to long-term MPL measurements to support aerosol and mixed-phase/ice cloud interaction study at the NSA site.
- Open Access
- 13 March 2021
- Published by MDPI AG in Remote Sensing
- Vol. 13 (6) , 1099
Profiling Dust Mass Concentration in Northwest China Using a Joint Lidar and Sun-Photometer Setting
The satellite-based estimation of the dust mass concentration (DMC) is essential for accurately evaluating the global biogeochemical cycle of the dust aerosols. As for the uncertainties in estimating DMC caused by mixing dust and pollutants and assuming a fixed value for the mass extinction efficiency (MEE), a classic lidar-photometer method is employed to identify and separate the dust from pollutants, obtain the dust MEE, and evaluate the effect of the above uncertainties, during five dust field experiments in Northwest China. Our results show that this method is effective for continental aerosol mixtures consisting of dust and pollutants. It is also seen that the dust loading mainly occurred in the free troposphere (−2 trapped in the planetary boundary layer. The dust MEE ranges from 0.30 to 0.60 m2 g−1 and has a significantly negative relationship with the size of dust particles. With the assumption of the dust MEE of 0.37 (0.60) m2 g−1, the DMC is shown to be overestimated (underestimated) by 20–40% (15–30%). In other words, our results suggest that the change of MEE with the size of dust particles should be considered in the estimation of DMC.
- 13 March 2021
- Published by MDPI AG in Remote Sensing
- Vol. 13 (6) , 1099
Open AccessProfiling Dust Mass Concentration in Northwest China Using a Joint Lidar and Sun-Photometer Setting
The satellite-based estimation of the dust mass concentration (DMC) is essential for accurately evaluating the global biogeochemical cycle of the dust aerosols. As for the uncertainties in estimating DMC caused by mixing dust and pollutants and assuming a fixed value for the mass extinction efficiency (MEE), a classic lidar-photometer method is employed to identify and separate the dust from pollutants, obtain the dust MEE, and evaluate the effect of the above uncertainties, during five dust field experiments in Northwest China. Our results show that this method is effective for continental aerosol mixtures consisting of dust and pollutants. It is also seen that the dust loading mainly occurred in the free troposphere (−2 trapped in the planetary boundary layer. The dust MEE ranges from 0.30 to 0.60 m2 g−1 and has a significantly negative relationship with the size of dust particles. With the assumption of the dust MEE of 0.37 (0.60) m2 g−1, the DMC is shown to be overestimated (underestimated) by 20–40% (15–30%). In other words, our results suggest that the change of MEE with the size of dust particles should be considered in the estimation of DMC.