What Controls the Macrophysical and Microphysical Properties of Arctic Clouds during Cold Air Outbreaks: Results from CAESAR

There is a strong need to determine how boundary cloud properties vary with surface, environmental and aerosol conditions in high latitudes during cold air outbreaks (CAOs) to determine processes controlling the evolution of these clouds. In-situ cloud microphysical, thermodynamic, and remote sensing measurements made on a C130 aircraft during the 2024 CAO Experiment in the Sub-Arctic Region (CAESAR) field campaign over the Norwegian and Greenland Sea are used to quantify how vertical cloud and thermodynamic profiles vary with environmental conditions, and how they transform downstream from the ice edge to warmer oceans. The majority of clouds sampled were either liquid- or mixed-phase, with few entirely ice-phase clouds. Ramped ascents and descents through cloud are used to determine how vertical profiles of total number concentration, liquid water content, ice crystal concentration, ice mass content, liquid and ice effective radius, and median volume diameter as functions of normalized altitude (zn, where zn=0 at cloud base and zn=1 at cloud top) vary with environmental conditions. Results show considerable variability, but profiles exhibit clear dependence on estimated inversion strength (EIS), with higher cloud droplet number concentrations, lower effective radii for liquid and ice particles, and lower large ice crystal number concentration and water content for higher EIS. Dependence on other environmental conditions will also be shown. Data from the 16 March 2024 flight when 36 dropsondes were released, are then used to determine how cloud and environmental properties vary across five distinct zones: the sea ice zone, zone near the edge of the sea ice with shallow cumulus clouds, zone characterized by well-organized cloud streets, zone featuring disorganized cloud streets on northern side of a polar low, and the polar low zone. Environmental parameters, including the M index, LTS (lower tropospheric stability), EIS, boundary layer (BL) height, and the vertical distribution of temperature and humidity within the BL, vary across these five zones. Additionally, cloud macrophysical properties such as cloud top and base heights and temperature, cloud cell width, number within a 50-km observation window, and cloud albedo, along with microphysical properties including liquid water content and liquid water fraction (LWF), also change across zones. These variations highlight the spatial, macro- and micro-physical, and thermodynamic gradients as CAO air moves downstream. To uncover mechanisms driving differences in zone properties, simulations conducted with the Weather Research and Forecasting (WRF) model shown to reproduce observed cloud patterns and vertical structures, are utilized. WRF simulations reveal that mixed-phase shallow cumulus located near the sea ice edge contained a supercooled liquid layer near their tops. These clouds had higher LWF near cloud top compared to both well-organized and disorganized cloud streets. Additionally, polar low clouds primarily consisted of ice. A Random Forest model, utilizing WRF output, shows LTS was the most important factor in predicting the number of cloud cells. In contrast, relative humidity (RH) between 0 and 2 km had the greatest influence on cloud cell width and cloud base height, while RH between 2 and 4 km was most critical for predicting cloud base heights.