| Description |
Understanding the connection between large-scale meteorology, cloud macrophysical variables, and cloud microphysical variables is needed in order to improve the parameterization of marine boundary layer (MBL) clouds in weather and climate models. For this study, multiple aspects of MBL clouds over the Atmospheric Radiation Measurement Program (ARM) mobile site at Graciosa Island, Azores are examined. Hourly averaged raw variables of cloud fraction, column summed dBZ, liquid water path, first cloud base height, boundary layer static stability, and midtropospheric static stability are clustered together using a K-means clustering algorithm. The cluster output infers seven characteristic cloud regimes that describe the spectrum of warm boundary layer clouds that occurred over Graciosa Island during the deployment. These cloud regimes range from precipitating stratocumulus to nonprecipitating fair weather cumulus to deep clouds associated with broad synoptic scale frontal systems. Using the cluster results and NCEP/NCAR reanalysis, the typical macrophysical and meteorological environments for the MBL cloud regimes are summarized along with their average radar profiles. MBL cloud microphysical properties are then derived using a new retrieval algorithm that assumes the presence of both cloud and precipitation particle modes within a radar resolution volume. Compared to a traditional single mode particle size distribution (PSD), a bimodal PSD is closer to in-situ observations and is expected to provide improved statistics and understanding of the cloud microphysical parameters such as number concentration, precipitation rate, and effective droplet sizes. The bimodal retrieval algorithm can use either ARM ground-based or A-Train satellite-based data as an input. This study finds that ARM and A-Train versions of the bimodal algorithm retrieve plausible microphysics and the reasons for their differences are explored. Case studies are completed using the bimodal retrieval for three shallow cloud regimes with varying precipitation, macrophysical, and synoptic environments. Results show that microphysical quantities do change as the cloud regime varies and validate the connection between the large and small-scale environment of MBL clouds. The specifics of the unique regime-based microphysics are also useful in order to better parameterize these clouds in models. |
