AMF Deployment, Graciosa Island, Azores
Location: 39° 5' 28" N, 28° 1' 45" W
Altitude: 15.24 meters
From May 2009 through December 2010, the ARM Mobile Facility is obtaining data from a location near the airport on Graciosa Island to support the Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) field campaign. Led by principal investigator Robert Wood, scientists involved in the campaign will use data from the AMF to study processes controlling the radiative properties and microphysics of marine boundary layer clouds, a high priority science question. Collaborators from the Regional Directorate of Science and Technology of the Government of Azores, the University of the Azores, and the Portuguese Meteorological Institute are providing key logistical and operations support.
Marine boundary layer clouds are particularly important in the global climate system, not only as passive modulators of solar energy, but as interactive systems that influence and modulate sea surface temperature and the strength of the trade winds on seasonal-interannual timescales. Their microphysical properties are important, strongly sensitive to manmade aerosol, and poorly understood, especially over remote oceans.
![Surrounded by the Atlantic Ocean, Graciosa Island is ideal for sampling the transition from an overcast stratocumulus regime in the spring to the broken trade cumulus regime in the summer.](https://webarchive.library.unt.edu/web/20121007164327im_/http://www.arm.gov/images/cms/azores-edited2.jpg)
Data from the prolonged AMF deployment will result in the first climatology of detailed vertical structure of cloud and precipitation properties of low clouds at a remote subtropical marine site. These data will provide particularly important new information about the structure and variability of the remote marine boundary layer system and the factors that influence it. These and other data sets created within the proposed work will be extremely important in the validation and testing of cloud parameterizations for the large-scale computer models and improved climate predictions.