Exploring links between cloud and aerosol microphysical processes, marine boundary layer dynamics, and cloud morphology in marine cold-air outbreaks over the Norwegian Sea

Marine cold-air outbreaks (MCAOs) over the Norwegian Sea exhibit a wide range of cloud morphologies within large-scale cloud regime transitions, which include closed-to-open-cell transitions that appear as a relatively sudden decreases in regional albedo and roll-to-cell transitions that show more gradual albedo changes with fetch, both seemingly linked to large-scale meteorological conditions. Intense mixed-phase cloud microphysical processes within marine boundary layer (MBL) clouds have the potential to leave strong cloud macrophysical signatures, including impacts to cloud morphology, via precipitation formation and subsequent dynamical modulations from sub-cloud precipitation evaporation. Here, we explore possible links between microphysical process rates, MBL dynamics, and the resulting cloud morphology.

This study builds on the ongoing model-observation intercomparison effort that focuses on one of the strongest MCAO events during the recent COMBLE (Cold-air Outbreak in the Marine Boundary Layer Experiment) campaign that showed a roll-to-cell transition and provides a platform for an international group of participants to test and develop their large-eddy simulation (LES) and single column models against various observational targets.

We analyze Lagrangian LES output spanning domains of (128 km)2, for a range of configurations that (1) dictate the permitted cloud phase (i.e., liquid-only versus mixed-phase clouds), and (2) switch between a diagnostic versus prognostic treatment for both cloud droplet and frozen hydrometeor number concentrations, Nd and Ni. We apply a watershed algorithm to hourly two-dimensional pseudo-albedo fields to identify cloud cells and determine their size and orientation, and extract cell-specific profiles from concomitant three-dimensional output, such as vertical and horizontal wind components and hydrometeor mixing ratios. Where sensible, we corroborate leading hypotheses with additional simulations, for example, by disallowing strong spatial gradients of sub-cloud moisture shown to drive cloud morphology in sub-tropical Sc (Zhou et al., 2018). Lastly, we test whether active remote sensing would detect finer differences that matter to cloud morphology and do so by forward-simulating signals from LES output using EMC2 (Silber et al., 2022)

References

Zhou, X., Ackerman, A. S., Fridlind, A. M., & Kollias, P. (2018). Simulation of Mesoscale Cellular Convection in Marine Stratocumulus. Part I: Drizzling Conditions. Journal of the Atmospheric Sciences, 75(1), 257-274.

Silber, I., Jackson, R. C., Fridlind, A. M., Ackerman, A. S., Collis, S., Verlinde, J., and Ding, J. (2022): The Earth Model Column Collaboratory (EMC2) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models, Geosci. Model Dev., 15, 901–927