Articles | Volume 11, issue 10
https://doi.org/10.5194/gmd-11-4021-2018
https://doi.org/10.5194/gmd-11-4021-2018
Development and technical paper
 | 
05 Oct 2018
Development and technical paper |  | 05 Oct 2018

Implementation of a comprehensive ice crystal formation parameterization for cirrus and mixed-phase clouds in the EMAC model (based on MESSy 2.53)

Sara Bacer, Sylvia C. Sullivan, Vlassis A. Karydis, Donifan Barahona, Martina Krämer, Athanasios Nenes, Holger Tost, Alexandra P. Tsimpidi, Jos Lelieveld, and Andrea Pozzer

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Cited articles

Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation: 2. Multiple aerosol types, J. Geophys. Res.-Atmos., 105, 6837–6844, https://doi.org/10.1029/1999JD901161, 2000. a
Ackermann, I. J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F. S., and Shankar, U.: Modal aerosol dynamics model for Europe: development and first applications, Atmos. Environ., 32, 2981–2999, https://doi.org/10.1016/S1352-2310(98)00006-5, 1998. a
Aquila, V., Hendricks, J., Lauer, A., Riemer, N., Vogel, H., Baumgardner, D., Minikin, A., Petzold, A., Schwarz, J. P., Spackman, J. R., Weinzierl, B., Righi, M., and Dall'Amico, M.: MADE-in: a new aerosol microphysics submodel for global simulation of insoluble particles and their mixing state, Geosci. Model Dev., 4, 325–355, https://doi.org/10.5194/gmd-4-325-2011, 2011. a
Barahona, D. and Nenes, A.: Parameterization of cirrus cloud formation in large-scale models: Homogeneous nucleation, J. Geophys. Res.-Atmos., 113, d11211, https://doi.org/10.1029/2007JD009355, 2008. a, b, c
Barahona, D. and Nenes, A.: Parameterizing the competition between homogeneous and heterogeneous freezing in ice cloud formation – polydisperse ice nuclei, Atmos. Chem. Phys., 9, 5933–5948, https://doi.org/10.5194/acp-9-5933-2009, 2009. a, b, c, d, e, f, g
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Short summary
The complexity of ice nucleation mechanisms and aerosol--ice interactions makes their representation still challenging in atmospheric models. We have implemented a comprehensive ice crystal formation parameterization in the global chemistry-climate model EMAC to improve the representation of ice crystal number concentrations. The newly implemented parameterization takes into account processes which were previously neglected by the standard version of the model.
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