Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters

• Published in: Atmospheric Chemistry and Physics
• Main Authors: Mamouri, Rodanthi-Elisavet, Ansmann, Albert
• Format: Text
• Language: English
• Published: 2018
• Subjects: Aerosol Robotic Network
• Online Access: https://doi.org/10.5194/acp-16-5905-2016; https://www.atmos-chem-phys.net/16/5905/2016/

We investigate the potential of polarization lidar to provide vertical profiles of aerosol parameters from which cloud condensation nucleus (CCN) and ice nucleating particle (INP) number concentrations can be estimated. We show that height profiles of particle number concentrations n 50, dry considering dry aerosol particles with radius > 50 nm (reservoir of CCN in the case of marine and continental non-desert aerosols), n 100, dry (particles with dry radius > 100 nm, reservoir of desert dust CCN), and of n 250, dry (particles with dry radius > 250 nm, reservoir of favorable INP), as well as profiles of the particle surface area concentration s dry (used in INP parameterizations) can be retrieved from lidar-derived aerosol extinction coefficients σ with relative uncertainties of a factor of 1.5–2 in the case of n 50, dry and n 100, dry and of about 25–50 % in the case of n 250, dry and s dry . Of key importance is the potential of polarization lidar to distinguish and separate the optical properties of desert aerosols from non-desert aerosol such as continental and marine particles. We investigate the relationship between σ , measured at ambient atmospheric conditions, and n 50, dry for marine and continental aerosols, n 100, dry for desert dust particles, and n 250, dry and s dry for three aerosol types (desert, non-desert continental, marine) and for the main lidar wavelengths of 355, 532, and 1064 nm. Our study is based on multiyear Aerosol Robotic Network (AERONET) photometer observations of aerosol optical thickness and column-integrated particle size distribution at Leipzig, Germany, and Limassol, Cyprus, which cover all realistic aerosol mixtures. We further include AERONET data from field campaigns in Morocco, Cabo Verde, and Barbados, which provide pure dust and pure marine aerosol scenarios. By means of a simple CCN parameterization (with n 50, dry or n 100, dry as input) and available INP parameterization schemes (with n 250, dry and s dry as input) we finally compute profiles of the CCN-relevant particle number concentration n CCN and the INP number concentration n INP . We apply the method to a lidar observation of a heavy dust outbreak crossing Cyprus and a case dominated by continental aerosol pollution.