Climatology of morphology and cloud-radiative properties of marine low-level mixed-phase clouds
Authors:   , Danker Jessica 
Published: December 2023

Marine stratocumuli cover about 40 - 60% of the ocean surface. They self-organize into different morphological regimes. The two organized cellular regimes are called open and closed mesoscale-cellular convective (MCC) clouds. In mid-to-high latitudes, open and closed cells are the two most frequent types of MCC clouds. In particular, many MCC clouds consist of a mixture of vapor, liquid droplets, and ice particles, referred to as mixed-phase clouds (MPCs). Even for the same cloud fraction, the albedo of open cells is, on average, lower than that of closed MCC clouds. Cloud phase and morphology individually influence the cloud radiative effect. Thus, this thesis investigates the relationships between the cloud phase, MCC organization, cell size, and differences regarding the cloud-radiative effect. This thesis focuses on space-borne retrievals to achieve extensive temporal and spatial coverage. The liDAR-raDAR (DARDAR) version 2 product collocates two active and one passive satellite: CloudSat, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Moderate Resolution Imaging Spectroradiometer (MODIS). The cloud phase of DARDAR is vertically integrated to establish a single cloud phase at each data point. The MCC classification data set based on the liquid water path (LWP) of MODIS scenes is collocated with the DARDAR product to determine the MCC organization. Cell-size statistics of both MCC clouds are obtained using a marker-based image segmentation method on MODIS reflectance scenes. In addition, based on MODIS reflectance scenes, a convolutional neural network (CNN) is developed to classify open and closed MCC scenes to avoid missing mature MPCs with a low LWP. The first part of this thesis explores the relationships between cloud phase, morphology, and cloud albedo in the Southern Ocean (SO). At a given cloud-top temperature (CTT), seasonal changes in the mixed-phase fraction, defined as the number of MPCs divided by the sum of MPC and supercooled liquid cloud (SLC) pixels, are stronger than the morphological changes. Therefore, external factors seem to influence these changes instead of morphology. The dependence of cloud phase on cloud-top height (CTH) is more substantial than on CTT in clouds with CTHs below 2.5 km. The previously observed acceleration of closed-to-open transition in MPCs, known as preconditioning, is not the primary driver of climatological cloud morphology statistics in the SO. The morphological differences in cloud albedo are more pronounced in SLCs than in MPCs. This change in albedo alters the cloud radiative effect in the SO by 21Wm−2 to 39Wm−2 depending onseason and cloud phase. Open and closed MCC clouds exhibit larger equivalent cell diameters in the MPCs than in SLCs in austral summer, whereas, in austral winter, the SLCs are larger. The cell’s aspect ratio accounts for varying CTHs. Closed cells have smaller aspect ratios than open cells, so their cell diameter is smaller, independent of CTH. While the seasonal differences in closed cells are due to changes in CTH, the seasonal aspect ratio differences in open cells are mainly caused by MPCs. With increasing aspect ratios, the cloud albedo decreases in both open and closed MCC clouds, with the most substantial decrease in open MPCs clouds. This leads to cloud-radiative changes of 60 - 75Wm−2 in the SO, depending on cloud phase and aspect ratio. The established CNN exhibits a good accuracy of 80.6%, with even higher accuracies in the Open (85.5%) and Closed (87.3%) categories. The global MCC climatology based on the CNN generally agrees well with previous MCC distributions. The most notable difference occurs in the Northern Hemisphere (NH) in boreal winter, with a higher occurrence frequency of closed and open MCC clouds. This might indicate missing MPCs in previous studies based on the LWP and some restricted to warm cloud scenes. Thus, the developed CNN seems to better represent the different morphologies in MPCs than in previous classifications. In conclusion, this thesis shows that understanding the dependencies of cloud phase, cloud morphology, and cell size is important to enhance predictions of the cloud-radiative effect and thus, it is important to evaluate how cloud phase, cloud morphology, and cellsize change in a warming climate.