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Sensitivity of Arctic clouds to ice microphysical processes in the NorESM2 climate model
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  • Georgia Sotiropoulou,
  • Anna Lewinschal,
  • Paraskevi Georgakaki,
  • Vaughan Phillips,
  • Sachine Patade,
  • Annica M. L. Ekman,
  • Athanasios Nenes
Georgia Sotiropoulou
ICE-HT, Foundation for Research and Technology Hellas (FORTH), Patras, Greece

Corresponding Author:georgia.sotiropoulou@epfl.ch

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Anna Lewinschal
Department of Meteorology, Stockholm University & Bolin Center for Climate Research, 9 Sweden
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Paraskevi Georgakaki
Laboratory of Atmospheric Processes and their Impacts (LAPI), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Vaughan Phillips
Department of Physical Geography
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Sachine Patade
Department of Physical Geography, University of Lund, Lund, Sweden
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Annica M. L. Ekman
Department of Meteorology, Stockholm University
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Athanasios Nenes
Laboratory of Atmospheric Processes and their Impacts (LAPI), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Ice formation remains one of the most poorly represented microphysical processes in climate models. While primary ice production (PIP) parameterizations are known to have a large influence on the modeled cloud properties, the representation of secondary ice production (SIP) is incomplete and its corresponding impact is therefore largely unquantified. Furthermore, ice aggregation is another important process for the total cloud ice budget, which also remains largely unconstrained. In this study we examine the impact of PIP, SIP and ice aggregation on Arctic clouds, using the Norwegian Earth System model version 2 (NorESM2). Simulations with both prognostic and diagnostic PIP show that heterogeneous freezing alone cannot reproduce the observed cloud ice and liquid content. The implementation of missing SIP mechanisms (collisional break-up, drop-shattering and sublimation break-up) in NorESM2 improves the modeled ice properties, however results are sensitive to the implementation method. Using an emulated-bin framework, instead of a bulk approach, increases the efficiency of the collisional break-up and drop-shattering processes. Moreover, collisional break-up, which is the dominant SIP mechanism in the examined conditions, is very sensitive to the treatment of the sublimation correction factor, a poorly-constrained parameter that is included in the utilized parameterization. Finally, ice aggregation is also found to be a critical process; reducing its efficiency (in line with radar observations of shallow Arctic clouds) substantially enhances SIP and further improves the agreement with remote-sensing cloud retrievals. The simulations with enhanced SIP and reduced ice aggregation result in decreased surface downward longwave biases compared to satellite measurements during the cold months.