Abstract

Abstract. We present a novel methodology to estimate cloud condensation nuclei (CCN) concentrations from spaceborne CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations) lidar measurements. The algorithm utilizes (i) the CALIPSO-derived backscatter and extinction coefficient, depolarization ratio, and aerosol subtype information; (ii) the normalized volume size distributions and refractive indices from the CALIPSO aerosol model; and (iii) the MOPSMAP (modelled optical properties of ensembles of aerosol particles) optical modelling package. For each CALIPSO height bin, we first select the aerosol-type specific size distribution and then adjust it to reproduce the extinction coefficient derived from the CALIPSO retrieval. The scaled size distribution is integrated to estimate the aerosol number concentration, which is then used in the CCN parameterizations to calculate CCN concentrations at different supersaturations. To account for the hygroscopicity of continental and marine aerosols, we use the kappa parameterization and correct the size distributions before the scaling step. The sensitivity of the derived CCN concentrations to variations in the initial size distributions is also examined. It is found that the uncertainty associated with the algorithm can range between a factor of 2 and 3. Our results are comparable to results obtained using the POLIPHON (Polarization Lidar Photometer Networking) method for extinction coefficients larger than 0.05 km−1. An initial application to a case with coincident airborne in situ measurements for independent validation shows promising results and illustrates the potential of CALIPSO for constructing a global height-resolved CCN climatology.

Highlights

  • Aerosol particles act as cloud condensation nuclei (CCN) and ice-nucleating particles (INPs) and provide a surface for the condensation of atmospheric water vapour to form cloud droplets

  • The performance of OMCAM in retrieving CCN concentrations primarily relies on the initial normalized volume size distributions (NVSDs) given in CALIPSO aerosol model (CAMel)

  • Tions used in CAMel are derived from cluster analysis of the long-term Aerosol Robotic Network (AERONET) measurements, they incorporate the errors associated with the AERONET inversion algorithm

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Summary

Introduction

Aerosol particles act as cloud condensation nuclei (CCN) and ice-nucleating particles (INPs) and provide a surface for the condensation of atmospheric water vapour to form cloud droplets. The rapid adjustments in clouds resulting from aerosol–cloud interactions (ACIs) are not well understood and still remain the largest source of spread in global climate projections (IPCC, 2021). This challenge has motivated the scientific community to study ACIs by using data from in situ and satellite measurements as well as by means of modelling and simulations. Satellite-based ACI studies relate cloud parameters (cloud reflectivity or albedo, cloud optical depth, cloud fraction, cloud drop effective radius, liquid water path), aerosol properties (aerosol optical depth (AOD), Ångström exponent (AE), aerosol index (AI)), and the precipitation pattern to understand the underlying mechanisms (Quaas et al, 2008, 2020; Gryspeerdt and Stier, 2012; McCoy et al, 2017; Kant et al, 2019; Liu et al, 2020; Choudhury et al, 2020).

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