Biological and dust aerosol as sources of ice nucleating particles in the Eastern Mediterranean: source apportionment, atmospheric processing and parameterization

• DOI: 10.5194/egusphere-2024-511
• Publication Date: 2024-02-27T12:31:00Z
• Authors: Kunfeng Gao; Franziska Vogel; Romanos Foskinis; Stergios Vratolis; Maria I. Gini; Konstantinos Gran...; Anne-Claire Billa...; Paraskevi Georgakaki; Olga Zografou; Prodromos Fetfatzis; Alexis Berne; Alexandros Papagi...; Konstantinos Elef...; Ottmar Möhler; Athanasios Nenes
• Keywords: Earth sciences; Chemistry; info:eu-repo/classification/ddc/550; 550; ddc:550; Physics; QC1-999; QD1-999

Abstract. Aerosol-cloud interactions in mixed-phase clouds (MPCs) are one of the most uncertain drivers of the hydrological cycle and climate change. A synergy of in-situ, remote sensing and modelling experiments was used to determine the source of ice nucleating particles (INPs) for MPCs at Mount Helmos in the Eastern Mediterranean. The influences of boundary layer turbulence, vertical aerosol distributions and meteorological conditions were also examined. When the observation site is in the Free Troposphere (FT), approximately 1 in 106 aerosol particles serve as INPs. The INP abundance spans three orders of magnitude and increases following the order of marine aerosols, continental aerosols, and finally, dust plumes. Biological particles are important INPs observed in continental and marine aerosols, whereas they play a secondary yet important role even during Saharan dust events. Air masses in the planetary boundary layer (PBL) show both enriched INP concentrations and higher proportion of INPs in comparison to total aerosol particles, different from cases in the FT. The presence of precipitations/clouds enriches INPs in the FT but decreases INPs in the PBL. Additionally, new INP parameterizations, incorporating the ratio of fluorescent-to-nonfluorescent or coarse-to-fine particles and predicting >90 % of the observed INPs within an uncertainty range of a factor of 10, exhibit better performance than current widely-used parameterizations, and allow ice formation in models to respond to variations in dust and biological particles. The improved parameterizations can help MPC formation simulations in regions with various INP sources or different regions with prevailing INP sources.