A Multi-Instrument Cloud Condensation Nuclei Spectrum Product

Principal Investigator(s):
Sonia Kreidenweis, Colorado State University

A wealth of observational data exist on the characteristics of atmospheric particulate matter, over multiple years, at the DOE ARM Southern Great Plains (SGP) site. This site is located in a region of the country that frequently experiences weather extremes, and that is removed from many local sources of pollution but is affected by transported smoke, dust, and urban emissions. The relationships between particulate matter, cloud formation and evolution, and precipitation are therefore of strong interest, and are being explored via modeling on a variety of scales. These models require as input detailed information on the characteristics of particles capable of serving as the nuclei for cloud formation. Sufficient data exist to be able to put together a picture of the nature of these cloud condensation nuclei (CCN) and their variability, but such a combined data product does not yet exist. In this project we will exploit the multiple measurement types at SGP to develop such estimates. The product that is to be produced in this 2-year effort will create a best-estimate CCN spectrum over a range of supersaturations, of less than 0.1% to ~10%. Further, the resulting data can be classified into representative categories that can be associated with specific impacts at the SGP site, e.g., clean background, polluted background, smoke intrusions, and the like, thereby gaining insights into the particle sources affecting the atmosphere in this region. The goal is to create an automated and flexible software package for this purpose that will be transitioned to ARM translators at the end of the project.