Menelaos Sarantos
University of Maryland
An automated detection scheme for ICME identification from in situ data
Interplanetary CME identification is a subjective process requiring human expert analysts. Each event exhibits a variety of signatures (e.g., high alpha abundance, low proton temperatures, bidirectional electron flows and others) that are almost never all present at once. A quantitative scheme using statistical clustering has been developed to process multidimensional spacecraft data (e.g. density, velocity etc) with the objective of separating CME events from ambient solar wind measurements. Early results detailing the efficacy of such an automated scheme will be presented.