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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 04 Feb 2019

Research article | 04 Feb 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Method to retrieve cloud condensation nuclei number concentrations using lidar measurements

Wangshu Tan1, Gang Zhao1, Yingli Yu1, Chengcai Li1, Jian Li2, Ling Kang3, Tong Zhu3, and Chunsheng Zhao1 Wangshu Tan et al.
  • 1Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
  • 2State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • 3State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Science & Engineering, Peking University, Beijing 100871, China

Abstract. Determination of cloud condensation nuclei (CCN) number concentrations at cloud base is important to constrain aerosol-cloud interactions. A new method to retrieve CCN number concentrations using backscatter and extinction profiles from multiwavelength Raman lidars is proposed. The method implements hygroscopic enhancements of backscatter/extinction with relative humidity to derive dry backscatter/extinction and humidogram parameters. Humidogram parameters, Ångström exponents, and lidar extinction-to-backscatter ratios are then linked to the ratio of CCN number concentration to dry backscatter/extinction coefficient (ARξ). This linkage is established based on the datasets simulated by Mie theory and κ-Köhler theory with in situ measured particle size distributions and chemical compositions. CCN number concentration can thus be calculated with ARξ and dry backscatter/extinction. An independent theoretical simulated datasets is used to validate this new method and results show that the retrieved CCN number concentrations at supersaturations of 0.07 %, 0.10 %, and 0.20 % are in good agreement with theoretical calculated values. Sensitivity tests indicate that retrieval error in CCN arise mostly from uncertainties in extinction coefficients and RH profiles. The proposed method improves CCN retrieval from lidar measurements and has great potential in deriving scarce long-term CCN data at cloud base which benefits aerosol-cloud interaction studies.

Wangshu Tan et al.
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Wangshu Tan et al.
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