Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> We present a novel methodology to estimate cloud condensation nuclei (CCN) concentrations from spaceborne CALIPSO (CloudâAerosol Lidar and Infrared Pathfinder Satellite Observations) lidar measurements. The algorithm utilizes (i)Â the CALIPSO-derived backscatter and extinction coefficient, depolarization ratio, and aerosol subtype information; (ii)Â the normalized volume size distributions and refractive indices from the CALIPSO aerosol model; and (iii)Â 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 0.05â<span class="inline-formula">km<sup>â1</sup></span>. 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
15 Aerosol particles act as cloud condensation nuclei (CCN) and ice nucleating particles (INP) and provide a surface for the condensation of atmospheric water vapour to form cloud droplets
As most of the size distributions used in the CALIPSO aerosol model (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
In order to account for such errors and natural variability, we analyzed the sensitivity of CCN concentrations to the initial 225 normalized size distributions considered in our retrieval algorithm
Summary
15 Aerosol particles act as cloud condensation nuclei (CCN) and ice nucleating particles (INP) 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 (ACI) are not well understood and still remains the largest source of spread in global climate projections This challenge has motivated the scientific community to study ACI by using data from in-situ and satellite measurements as well as by means of modelling and simulations. Satellites provide long term global coverage that enables ACI studies with constrained meteorology and cloud regimes (Oreopoulos et al, 2017; Douglas and L’Ecuyer, 2019; Jia et al, 2021). 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
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.