Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4755-2021
https://doi.org/10.5194/amt-14-4755-2021
Research article
 | 
01 Jul 2021
Research article |  | 01 Jul 2021

Retrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaign

William G. K. McLean, Guangliang Fu, Sharon P. Burton, and Otto P. Hasekamp

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Cited articles

Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. a
Andreae, M. O., Jones, C. D., and Cox, P. M.: Strong present-day aerosol cooling implies a hot future, Nature, 435, 1187–1190, https://doi.org/10.1038/nature03671, 2005. a
Böckmann, C.: Hybrid regularization method for the ill-posed inversion of multiwavelength lidar data in the retrieval of aerosol size distributions, Appl. Optics, 40, 1329–1342, https://doi.org/10.1364/AO.40.001329, 2001. a
Böckmann, C., Mironova, I., Müller, D., Schneidenbach, L., and Nessler, R.: Microphysical aerosol parameters from multiwavelength lidar, J. Opt. Soc. Am. A, 22, 518–528, https://doi.org/10.1364/JOSAA.22.000518, 2005. a
Burton, S. P., Ferrare, R. A., Hostetler, C. A., Hair, J. W., Rogers, R. R., Obland, M. D., Butler, C. F., Cook, A. L., Harper, D. B., and Froyd, K. D.: Aerosol classification using airborne High Spectral Resolution Lidar measurements – methodology and examples, Atmos. Meas. Tech., 5, 73–98, https://doi.org/10.5194/amt-5-73-2012, 2012. a, b, c
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Short summary
In this study, we present results from aerosol retrievals using both synthetic and real lidar datasets, including measurements from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined initiative between NASA and SRON (the Netherlands Institute for Space Research). Aerosol microphysical retrievals were performed using the High Spectral Resolution Lidar-2 (HSRL-2) setup, alongside several others, with the ACEPOL retrievals also compared to polarimeter retrievals. 
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