The Impact of CCN Concentrations on the Thermodynamic and Turbulent State of Arctic Mixed-Phase Clouds
Abstract. Impacts of aerosol on mixed-phase cloud evolution play a potentially important role in Arctic climate, but remain poorly understood. The way in which aerosol, clouds and turbulence interact, is speculated to significantly modify the cloud evolution. There has been an increasing number of field observations of the ice clouds in Arctic, however it has proven hard to gain insight into these complex interactions using measurements alone. This model study aims to help filling this gap in the current understanding of low-level Arctic clouds, by combining high resolution simulations with new field campaign data. The main focus is on the impact of the cloud condensation nuclei concentration (CCN) on the properties of cloud and mixed-layer turbulence in an~evolving boundary layer. We configure semi-idealised model scenarios based on the weather situation observed over open ocean during two research flights of the ACLOUD campaign, which took place over Fram Strait northwest of Svalbard. A demi-Lagrangian frame of reference is adopted, with the model domain following low level air masses and the large-scale forcings derived from weather model analyses and short-range forecasts. Adjustments in the initial state are made based on comparison to dropsonde data. The simulations reproduce the observed general structure of the cloud-bearing Arctic mixed layer. Results further show that while the ice phase forms just a fraction of the mass of cloud water, it is responsible for most of the precipitation, in line with previous observational and LES studies. A lower initial CCN concentration generally results into a faster glaciation of the cloud, leading to a faster removal of the cloud water, and also affects the vertical structure of turbulence. Implications for radiative studies of clouds for the purpose of Arctic Amplification are discussed.
This preprint has been withdrawn.
semi-idelalised LES of RF05 and RF20 https://doi.org/10.5281/zenodo.3271773
Model code and software
semi-idelalised LES of RF05 and RF20 - DALES model extension https://doi.org/10.5281/zenodo.3271773
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