A010-0007
The Relative Contribution of Secondary Ice Production Mechanisms in Alpine Mixed-Phase Clouds

Monday, 7 December 2020
Poster
Paraskevi Georgakaki1, Georgia Sotiropoulou1,2, Etienne Vignon3, Gary Lloyd4, Alexis Berne3 and Athanasios Nenes5, (1)EPFL Swiss Federal Institute of Technology Lausanne, LAPI, ENAC, Lausanne, Switzerland, (2)Stockholm University, Department of Meteorology, Stockholm, Sweden, (3)EPFL Swiss Federal Institute of Technology Lausanne, LTE, ENAC, Lausanne, Switzerland, (4)University of Manchester, Manchester, United Kingdom, (5)Swiss Federal Institute of Technology Lausanne, Laboratory of Atmospheric Processes and their Impacts, School of Architecture, Civil & Environmental Engineering, Lausanne, Switzerland
Abstract:
Ice formation in the atmosphere is of major importance affecting cloud microphysical properties, which in turn impact cloud radiative forcing and the hydrological cycle of the Earth. Ice crystal number concentrations (ICNCs) measured in mixed-phase clouds (MPCs) forming over mountain top research sites frequently exceed the available ice nucleating particle concentrations by several orders of magnitude. While blowing snow and hoar frost have often been suggested as possible contributors to the enhanced ICNCs, little is known about the contribution of in-cloud secondary ice production (SIP) processes. Here we investigate the potential role of SIP on orographic MPCs observed during the Cloud and Aerosol Characterization Experiment (CLACE) 2014 campaign at the high-alpine site of Jungfraujoch, using the Weather and Research and Forecasting model (WRF). The Hallett-Mossop mechanism, included in the default Morrison microphysics scheme, is ruled out since the clouds were rarely within the active temperature range for this process. This study investigates if the implementation of two additional SIP parameterizations in WRF, collisional break-up between ice hydrometeors and frozen droplet shattering, can reduce the discrepancies between observed and modeled ICNCs. Given the ubiquitous nature of MPCs and their importance in weather and climate, it is crucial to gain a better understanding of the SIP processes to be able to simulate the correct in-cloud phase partitioning and ultimately represent these clouds more accurately in atmospheric numerical models.