Automated Microphysical Cloud Properties from ARM Cimel Sunphotometer Cloud Mode Datasets

Abstract:

The representation of cloud processes and associated cloud feedbacks is a primary source of uncertainty in global climate model predictions. However, several fundamental cloud properties are poorly constrained by current models, including cloud droplet size and cloud optical depth, which are key quantities for cloud formation, dissipation and aerosol-drizzle interaction process studies. Recently, the DOE Atmospheric Radiation Measurement (ARM) User Facility has automated a Sunphotometer Cloud Mode Value-Added-Product (SPHOT VAP) that provides cloud optical depth, cloud droplet effective radius, and liquid water path, including associated uncertainties, from ground-based sunphotometer cloud mode zenith radiance data. These products use a three-channel (440, 870, and 1640 nm) retrieval algorithm, capable of enhancing the current and operational Aerosol Robotic Network (AERONET) two-channel algorithm, which is applicable only over vegetated surfaces. This new three-channel method was initially demonstrated for the 2013 Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign over the ocean. The automatic implementation of these retrievals streamlines the availability of cloud microphysical data for all DOE ARM cloud mode CIMEL sunphotometer deployments over vegetated land, ocean, and ice. Summary results are provided for the ARM Southern Great Plains (SGP) site, and the recent Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARUCS) and ARM West Antarctic Radiation Experiment (AWARE) field campaigns.