SH21A-4090:
Automated Wave Analysis and Reduction in EUV (AWARE): a tool for the detection and characterization of EUV waves.
Tuesday, 16 December 2014
Andrew R Inglis1, Jack Ireland2, Albert Shih3, Steven Christe3 and Laura Hayes4, (1)Catholic University of America, Washington, DC, United States, (2)ADNET Systems Inc. Greenbelt, Greenbelt, MD, United States, (3)NASA GSFC, Greenbelt, MD, United States, (4)Trinity College Dublin, Dublin, Ireland
Abstract:
Extreme ultraviolet (EUV) waves are large-scale and faint propagating disturbances observed in the solar corona, frequently associated with coronal mass ejections and flares. Since their discovery over two hundred papers discussing their properties, causes and physics have been published. However, their fundamental nature and the physics of their interactions with other solar phenomena are still not understood. To further the understanding of EUV waves, and their relation to other solar phenomena, we are developing AWARE - the Automated Wave Analysis and REduction algorithm for the detection of EUV waves over the full Sun. AWARE is a Python-based, open-source algorithm that utilizes the SunPy data analysis package and general purpose signal processing libraries. The core detection algorithm is based on a novel image processing approach to isolating the bright wavefront of the EUV as it propagates across the confounding background emission of the complex structured solar corona. The location, speed and acceleration of the wavefront as a function of direction from the source events are calculated. We describe the core image processing steps of the AWARE algorithm, and demonstrate its application to observational data from SDO/AIA and STEREO/EUVI.
