PhD Defense: Hannah Seppala
ADVISOR: Dr. Zhibo Zhang
TITLE: Characterizing Arctic Marine Cold Air Outbreaks: A Lagrangian Method Applied to 21 Years of Data
ABSTRACT: Arctic Marine Cold Air Outbreaks (AMCAO) are unique weather events which occur when a cold polar air mass moves over the relatively warm ocean. These events feature intense heat and moisture fluxes and form mixed phase clouds which evolve, both macro and microphysically, over the course of approximately 15 hours. At the event onset, clouds are generally stratocumulus, forming convective rolls parallel to the wind direction. During the aging process, the clouds break up into cumuliform structures. This transition, the Stratocumulus-to-Cumulus Transition (SCT), is difficult to represent in models due to its strong dependence on subgrid processes and air-sea interactions. This dissertation utilizes MODIS data in order to better characterize clouds in these AMCAO events and the SCT they undergo. A novel Lagrangian framework is developed, which maps MODIS pixels along wind trajectories to determine cloud properties as a function of cloud age.
This method was first applied to eight case studies in 2020, mostly over the Fram Strait, using MODIS Level-2 retrievals. The transition in cloud properties was characterized, showing general decreases in cloud droplet number concentration and liquid water fraction, and increases in cloud water path and cloud top height, regardless of changes in cloud top temperature and air-sea potential temperature difference. Crucially, the events showed two distinct behaviors, termed ``Fast Freezing" (FF) and ``Phase Stable" (PS). FF events underwent cloud top glaciation, defined as the cloud top liquid water fraction dropping below 0.6, within 10 hours. In contrast, PS events maintained predominantly liquid cloud tops through the event.
The method was then applied to 21 years of Level-3 MODIS data, covering 2000-2020, over the Fram Strait. 414 unique AMCAO events were identified. Of those, 55 (13%) were FF, and the remaining 359 (87%) were PS, indicating a preference in the region for PS events. Comparing strong FF events to all strong events, which underwent similar air-sea temperature evolutions, FF events had higher and colder cloud tops, larger liquid water paths and optical thicknesses, and significantly higher cloud droplet number concentrations. MERRA-2 reanalysis data showed no statistically robust difference in aerosol loading between the two cases, with the caveat that local Arctic aerosol sources, likely significant in the region and season, were not included in the dataset. HYSPLIT back trajectories of 15 randomly sampled events, 5 each of strong FF, strong PS, and weak PS, showed that the air masses in PS events had spent more time over sea ice, an aerosol sink, than the air masses in FF events. These results support the hypothesis that higher aerosol loading is likely favorable for FF event formation, likely through the mechanism of ice nucleating particles initiating cloud top glaciation, although enhanced convection is also a possible contributing factor. Importantly, the resulting dataset provides an observational benchmark for evaluating simulated cloud phase and morphology transitions in CAO events.
Virtual Attendance
Meeting link: umbc.webex.com/meet/hseppal1