Lucas Sterzinger

Abstract. Mixed-phase clouds are ubiquitous in the Arctic. These clouds can persist for days and dissipate in a matter of hours. It is sometimes unknown what causes this sudden dissipation, but aerosol–cloud interactions may be involved. Arctic aerosol concentrations can be low enough to affect cloud formation and structure, and it has been hypothesized that, in some instances, concentrations can drop below some critical value needed to maintain a cloud.

We use observations from a Department of Energy ARM site on the northern slope of Alaska at Oliktok Point (OLI), the Arctic Summer Cloud Ocean Study (ASCOS) field campaign in the high Arctic Ocean, and the Integrated Characterisation of Energy, Clouds, Atmospheric state, and Precipitation at Summit – Aerosol Cloud Experiment (ICECAPS-ACE) project at the NSF (National Science Foundation) Summit Station in Greenland (SMT) to identify one case per site where Arctic boundary layer clouds dissipated coincidentally with a decrease in surface aerosol concentrations. These cases are used to initialize idealized large eddy simulations (LESs) in which aerosol concentrations are held constant until, at a specified time, all aerosols are removed instantaneously – effectively creating an extreme case of aerosol-limited dissipation which represents the fastest a cloud could possibly dissipate via this process. These LESs are compared against the observed data to determine whether cases could, potentially, be dissipating due to insufficient aerosol. The OLI case’s observed liquid water path (LWP) dissipated faster than its simulation, indicating that other processes are likely the primary drivers of the dissipation. The ASCOS and SMT observed LWP dissipated at similar rates to their respective simulations, suggesting that aerosol-limited dissipation may be occurring in these instances.

We also find that the microphysical response to this extreme aerosol forcing depends greatly on the specific case being simulated. Cases with drizzling liquid layers are simulated to dissipate by accelerating precipitation when aerosol is removed while the case with a non-drizzling liquid layer dissipates quickly, possibly glaciating via the Wegener–Bergeron–Findeisen (WBF) process. The non-drizzling case is also more sensitive to ice-nucleating particle (INP) concentrations than the drizzling cases. Overall, the simulations suggest that aerosol-limited cloud dissipation in the Arctic is plausible and that there are at least two microphysical pathways by which aerosol-limited dissipation can occur.

Many factors are at play in determining the amount and distribution of mountain snowfall predicted by weather models; among them is the influence of assumed ice habit. Ice habit is necessarily greatly simplified in microphysics schemes and uncertainty remains in how best to model ice processes. In this study we simulate a Sierra Nevada snowfall event driven by an extratropical cyclone in February 2014. We have simulated the storm with four fixed-habit types as well as with an ice habit scheme that is variable in time and space. In contrast to some previous studies, we found substantially smaller sensitivity of total accumulated precipitation amount and negligible changes in spatial distribution to the ice habit specification. The reason for smaller sensitivity seems to be linked to strong aggregation of ice crystals in the model. Nonetheless, while changes in total accumulated precipitation were small, changes in accumulated ice hydrometeors were larger. The variable-habit simulation produced up to 37% more ice precipitation than any of the fixed-habit simulations with an average increase of 14%. The variable-habit simulation led to a maximization of ice growth in the atmosphere and, subsequently, ice accumulation at the surface. This result points to the potential importance of accounting for the time and space variation of ice crystal properties in simulations of orographic precipitation.