Abstract. Clouds and aerosol–cloud interactions remain major sources of uncertainty in climate projections. Here, we improve the representation of mixed-phase clouds (MPCs) in the EC-Earth3-AerChem Earth System Model by replacing the default temperature-dependent nucleation scheme with a physically based aerosol-sensitive heterogeneous ice nucleation parameterization. This scheme accounts for immersion freezing by K-feldspar, quartz, and marine organic aerosols, and is combined with a machine-learning-based parameterization of secondary ice production (SIP) to represent ice crystal multiplication processes. The new configuration improves agreement with global in situ ice nucleating particle (INP) observations and reveals realistic spatial patterns of ice crystal number concentrations (ICNC) across diverse environments. While these improvements do not eliminate the persistent structural cloud biases in EC-Earth3-AerChem, the aerosol-sensitive primary ice production scheme increases supercooled liquid water and cloud cover, particularly in the extratropics. Critically, the addition of SIP rebalances the cloud phase by enhancing ICNC in regions with low primary ice formation. Compared to the default scheme, the aerosol-sensitive primary ice production configuration with SIP reduces cloud radiative effect biases at mid- and high latitudes, while increasing them in the lower latitudes, leading to comparable global biases across configurations. Our results highlight the importance of explicitly representing both aerosol-sensitive nucleation and SIP for realistic simulations of MPCs and their radiative impacts. Unlike previous schemes, in which ice concentrations depend directly on INPs, the presence of effective SIP enhances ice formation in all MPCs and reduces the sensitivity of ICNC to aerosols, especially at low INP levels.
Costa-Surós et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: