Estimation of CCN concentrations from Spaceborne Lidar measurements

Aerosol and cloud-mediated change in climate forcing is the most uncertain one among all forcing agencies in the climate system, representing the largest challenge in climate predictions. Quantifying this at a global scale needs space-borne retrieval of cloud condensation nuclei (CCN) number concentration. Our inability to do so introduce a highest uncertainty regarding aerosol-cloud interactions and their climate forcing. This can be addressed by the emerging capability of estimating CCN concentrations using space-borne lidar measurements. The present study offers a novel approach to estimate vertically-resolved CCN concentration at five various supersaturations from multi-wavelength measurements from space-born lidar instruments. The algorithm uses backscatter and extinction coefficients from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) along with inverse-Mie technique to determine the aerosols size parameters for predefined aerosol types. Followingly, the critical radius of CCN activation at various supersaturation determines using the maximum of -Kohler theory. Finally, the CCN concentrations are calculated by integrating the aerosol size distribution over a range of critical radius at various supersaturation. Furthermore, the present retrieval approach will provide the 3D high-resolution benchmark datasets of CCN concentrations at various supersaturations at global scale which will be decisive for improved quantitative estimate of climate forcing due to anthropogenic impacts.