Modeling aerosol-cloud interactions in the Arctic

Licentiate thesis, 2022

Clouds have a large impact on Earth’s energy balance, especially in the Arctic. Through their warming or cooling effect on the surface, clouds can play a critical role in the onset of melting and freezing of Arctic sea ice, which itself has a large effect on energy and moisture fluxes between the ocean and the atmosphere. One of the factors that determine whether a cloud has a net warming or cooling effect is its microphysical structure determined by the phase of the hydrometeors that the cloud consists of. Mixed-phase stratiform clouds, consisting of both water droplets and ice crystals, often occur in the Arctic between mid-spring and mid-fall. To be able to simulate the Arctic climate, it is crucial that models capture Arctic mixed-phase stratiform clouds (AMPS) and the apportionment between liquid and frozen hydrometeors in these clouds. A good representation of ice nucleation is the necessary first step for accurate modeling of cloud ice. Ice nucleation in mixed-phase clouds occurs heterogeneously with the requirement of ice nucleating particles (INP). This work presents a new heterogeneous freezing parameterization that was tested in a large-eddy simulation of AMPS. Different to other parameterization schemes, this parameterization does not require knowledge about the aerosol concentration and characteristics (type, size, etc.). Instead the parameterization is based on the observation that the frequency of INP concentrations at a specific temperature follows a log-normal distribution and randomly draws INP concentrations from this distribution at the present temperature. It is shown that the new parameterization results in reasonable amounts of cloud ice and that the random drawing of INP concentrations is an important aspect to be investigated when it comes to cloud ice formation.