Articles | Volume 12, issue 7
Research article
12 Jul 2019
Research article |  | 12 Jul 2019

Method to retrieve cloud condensation nuclei number concentrations using lidar measurements

Wangshu Tan, Gang Zhao, Yingli Yu, Chengcai Li, Jian Li, Ling Kang, Tong Zhu, and Chunsheng Zhao

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Cited articles

Bedoya-Velásquez, A. E., Navas-Guzmán, F., Granados-Muñoz, M. J., Titos, G., Román, R., Casquero-Vera, J. A., Ortiz-Amezcua, P., Benavent-Oltra, J. A., de Arruda Moreira, G., Montilla-Rosero, E., Hoyos, C. D., Artiñano, B., Coz, E., Olmo-Reyes, F. J., Alados-Arboledas, L., and Guerrero-Rascado, J. L.: Hygroscopic growth study in the framework of EARLINET during the SLOPE I campaign: synergy of remote sensing and in situ instrumentation, Atmos. Chem. Phys., 18, 7001–7017,, 2018. 
Bian, Y., Zhao, C., Xu, W., Kuang, Y., Tao, J., Wei, W., Ma, N., Zhao, G., Lian, S., Tan, W., and Barnes, J. E.: A novel method to retrieve the nocturnal boundary layer structure based on CCD laser aerosol detection system measurements, Remote Sens. Environ., 211, 38–47,, 2018. 
Bohren, C. F. and Huffman, D. R.: Absorption and Scattering by an Arbitrary Particle, in: Absorption and Scattering of Light by Small Particles, Wiley-VCH Verlag GmbH, Weinheim, 57–81, 2007. 
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and Aerosols, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 571–658, 2013. 
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32,, 2001. 
Short summary
A new method to retrieve CCN number concentrations using multiwavelength Raman lidars is proposed. The method implements hygroscopic enhancements of backscatter and extinction with relative humidity to represent particle hygroscopicity. The retrieved CCN number concentrations are in good agreement with theoretical calculated values. Sensitivity tests indicate that retrieval error in CCN arises mostly from uncertainties in extinction coefficients and RH profiles.