| Description |
Marine boundary layer clouds are an important component of Earth's climate system due to their vast spatial and temporal coverage. Representation of these clouds in climate models remains challenging and continues to result in the largest feedback uncertainties. It is essential to increase understanding of cloud physical processes in order to improve climate models. In this study, we investigate possible conditions influencing albedo and precipitation susceptibility of marine boundary layer clouds, which gauge the clouds' sensitivity to perturbations in aerosol concentration. To do so, we employ a recently developed retrieval algorithm that uses A-Train satellite data to infer cloud properties. This unique algorithm assumes a bimodal particle size distribution, and then uses information from CloudSat and MODIS to simultaneously retrieve cloud mode and precipitation mode properties. Additionally, a new parameterization for the single scattering properties of clouds is developed to account for the bimodal size distribution, and is used to help provide constraints for the cloud retrieval. An equivalent retrieval has been developed to use ground-based ARM data. To study marine boundary layer cloud susceptibility, we focus our attention on the region spanning the stratocumulus cloud regime near California and the trade cumulus cloud regime near Hawaii. We compare albedo and precipitation susceptibility between winter and summer months and also between high and low surface wind conditions. It is found that cloud droplet number concentrations vary between seasons and surface wind conditions. Albedo susceptibility tends to increase monotonically with liquid water path (LWP). Precipitation susceptibility, on the other hand, shows non-monotonic behavior characterized by an autoconversion regime at low LWP and a transition to an accretion regime at higher LWP. |
