Preprints
https://doi.org/10.5194/egusphere-2025-4659
https://doi.org/10.5194/egusphere-2025-4659
06 Oct 2025
 | 06 Oct 2025
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Implementation of Primary and Secondary Ice Production in EC-Earth3-AerChem: Global Impacts and Insights

Montserrat Costa-Surós, María Gonçalves Ageitos, Marios Chatziparaschos, Paraskevi Georgakaki, Manu Anna Thomas, Gilbert Montané Pinto, Stelios Myriokefalitakis, Twan van Noije, Philippe Le Sager, Maria Kanakidou, Athanasios Nenes, and Carlos Pérez García-Pando

Abstract. Clouds and aerosol–cloud interactions remain major sources of uncertainty in climate projections. 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.

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). While biases in liquid water path persist, with overestimations in the tropics and underestimations at high latitudes, 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.

Competing interests: I declare that neither I nor my co-authors have any competing interests, except that Maria Kanakidou currently serves as an editor for Atmospheric Chemistry and Physics. This has been disclosed for transparency, and we have no other financial, personal, or professional interests that could influence the review of this manuscript.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Montserrat Costa-Surós, María Gonçalves Ageitos, Marios Chatziparaschos, Paraskevi Georgakaki, Manu Anna Thomas, Gilbert Montané Pinto, Stelios Myriokefalitakis, Twan van Noije, Philippe Le Sager, Maria Kanakidou, Athanasios Nenes, and Carlos Pérez García-Pando

Status: open (until 17 Nov 2025)

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Montserrat Costa-Surós, María Gonçalves Ageitos, Marios Chatziparaschos, Paraskevi Georgakaki, Manu Anna Thomas, Gilbert Montané Pinto, Stelios Myriokefalitakis, Twan van Noije, Philippe Le Sager, Maria Kanakidou, Athanasios Nenes, and Carlos Pérez García-Pando

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Reproducible figure generation for Costa-Suros et al. (2025, ACP) Montserrat Costa-Surós and Marios Chatziparaschos https://doi.org/10.5281/zenodo.17175726

Montserrat Costa-Surós, María Gonçalves Ageitos, Marios Chatziparaschos, Paraskevi Georgakaki, Manu Anna Thomas, Gilbert Montané Pinto, Stelios Myriokefalitakis, Twan van Noije, Philippe Le Sager, Maria Kanakidou, Athanasios Nenes, and Carlos Pérez García-Pando
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Short summary
Mixed-phase clouds play a key role in Earth’s climate but remain poorly represented in climate models. We improved their representation in the EC-Earth model by introducing an aerosol-sensitive scheme for ice formation and a machine-learning approach for secondary ice production. These advances produce more realistic cloud properties and radiative effects, highlighting that both processes are essential for reliable climate projections.
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