ALBERT

Description: Dust aerosols have been regarded as effective ice nuclei (IN), but large uncertainties regarding their efficiencies remain. Here, four years of collocated CALIPSO and CloudSat measurements are used to quantify the impact of dust on heterogeneous ice generation in midlevel supercooled stratiform clouds (MSSCs) over the ‘dust belt’. The results show that the dusty MSSCs have an up to 20% higher mixed-phase cloud occurrence, up to 8 dBZ higher mean maximum Ze (Ze_max), and up to 11.5 g/m2 higher ice water path (IWP) than similar MSSCs under background aerosol conditions. Assuming similar ice growth and fallout history in similar MSSCs, the significant differences in Ze_max between dusty and non-dusty MSSCs reflect ice particle number concentration differences. Therefore, observed Ze_max differences indicate that dust could enhance ice particle concentration in MSSCs by a factor of 2 to 6 at temperatures colder than −12°C. The enhancements are strongly dependent on the cloud top temperature, large dust particle concentration and chemical compositions. These results imply an important role of dust particles in modifying mixed-phase cloud properties globally.

Description: Ice particle formation in slightly supercooled stratiform clouds is not well documented or understood. In this study four years of combined lidar depolarization and radar reflectivity (Z e ) measurements are analyzed to distinguish between cold drizzle and ice crystal formations in slightly supercooled Arctic stratiform clouds over the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) North Slope of Alaska (NSA) Utqiaġvik (“Barrow”) site. Ice particles are detected and statistically shown to be responsible for the strong precipitation in slightly supercooled Arctic stratiform clouds at cloud top temperatures as high as -4 °C. For ice precipitating Arctic stratiform clouds, the lidar particulate linear depolarization ratio (δ par_lin ) correlates well with radar Z e at each temperature range, but the δ par_lin -Z e relationship varies with temperature ranges. In addition, lidar depolarization and radar Z e observations of ice generation characteristics in Arctic stratiform clouds are consistent with laboratory-measured temperature-dependent ice growth habits.

Description: Abstract In this study, we conduct sensitivity experiments with the Community Atmosphere Model version 5 (CAM5) to understand the impact of representing heterogeneous distribution between cloud liquid and ice on the phase partitioning in mixed‐phase clouds through different perturbations on the Wegener‐Bergeron‐Findeisen (WBF) process. In two experiments, perturbation factors that are based on assumptions of pocket structure and the partial homogeneous cloud volume derived from the High‐performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole‐to‐Pole Observation (HIPPO) campaign are utilized. Alternately, a mass‐weighted assumption is used in the calculation of WBF process to mimic the appearance of unsaturated area in mixed‐phase clouds as the result of heterogeneous distribution. Model experiments are tested in both single‐column and weather forecast modes and evaluated against data from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program's Mixed‐Phase Arctic Cloud Experiment (M‐PACE) field campaign and long‐term ground‐based multi‐sensor measurements. Model results indicate that perturbations on the WBF process can significantly modify simulated microphysical properties of Arctic mixed‐phase clouds. The improvement of simulated cloud water phase partitioning tends to be linearly proportional to the perturbation magnitude that is applied in the three different sensitivity experiments. Cloud macrophysical properties such as cloud fraction and frequency of occurrence of low‐level mixed‐phase clouds are less sensitive to the perturbation magnitude than cloud microphysical properties. Moreover, this study indicates that heterogeneous distribution between cloud hydrometeors should be treated consistently for all cloud microphysical processes. The model vertical resolution is also important for liquid water maintenance in mixed‐phase clouds.