Description
The NASA Atmosphere SIPS, located at the University of Wisconsin, is responsible for producing operational cloud and aerosol scientific products from satellite observations. With decades of satellite observations, new scientific algorithms are employing Machine Learning (ML) methods to improve processing efficiencies and scientific analyses. In preparation for future developments, we are working with NASA Atmospheric Science Teams to understand ML requirements and assist in developing new tools that will benefit both the Science Teams and the broader Open-Source Science community. This talk will step through a ML methodology being used to identify cloud types and severe aerosols.