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Author: Mamouri, Rodanthi-Elisavet × Subject: cloud condensation nucleus ×

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    Tropospheric and stratospheric wildfire smoke profiling with lidar: mass, surface area, CCN, and INP retrieval
    (Katlenburg-Lindau : European Geosciences Union, 2021) Ansmann, Albert; Ohneiser, Kevin; Mamouri, Rodanthi-Elisavet; Knopf, Daniel A.; Veselovskii, Igor; Baars, Holger; Engelmann, Ronny; Foth, Andreas; Jimenez, Cristofer; Seifert, Patric; Barja, Boris
    We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area, and number concentrations in the case of wildfire smoke layers as well as estimates of smoke-related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations from backscatter lidar measurements on the ground and in space. Conversion factors used to convert the optical measurements into microphysical properties play a central role in the data analysis, in addition to estimates of the smoke extinction-to-backscatter ratios required to obtain smoke extinction coefficients. The set of needed conversion parameters for wildfire smoke is derived from AERONET observations of major smoke events, e.g., in western Canada in August 2017, California in September 2020, and southeastern Australia in January-February 2020 as well as from AERONET long-term observations of smoke in the Amazon region, southern Africa, and Southeast Asia. The new smoke analysis scheme is applied to CALIPSO observations of tropospheric smoke plumes over the United States in September 2020 and to ground-based lidar observation in Punta Arenas, in southern Chile, in aged Australian smoke layers in the stratosphere in January 2020. These case studies show the potential of spaceborne and ground-based lidars to document large-scale and long-lasting wildfire smoke events in detail and thus to provide valuable information for climate, cloud, and air chemistry modeling efforts performed to investigate the role of wildfire smoke in the atmospheric system. © 2021 Albert Ansmann et al.
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    Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters
    (München : European Geopyhsical Union, 2016) Mamouri, Rodanthi-Elisavet; Ansmann, Albert
    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 n50, dry considering dry aerosol particles with radius  > 50 nm (reservoir of CCN in the case of marine and continental non-desert aerosols), n100, dry (particles with dry radius  >  100 nm, reservoir of desert dust CCN), and of n250, dry (particles with dry radius  >  250 nm, reservoir of favorable INP), as well as profiles of the particle surface area concentration sdry (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 n50, dry and n100, dry and of about 25–50 % in the case of n250, dry and sdry. 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 n50, dry for marine and continental aerosols, n100, dry for desert dust particles, and n250, dry and sdry 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 n50, dry or n100, dry as input) and available INP parameterization schemes (with n250, dry and sdry as input) we finally compute profiles of the CCN-relevant particle number concentration nCCN and the INP number concentration nINP. We apply the method to a lidar observation of a heavy dust outbreak crossing Cyprus and a case dominated by continental aerosol pollution.