A Coherence-Based Approach for Tracking Waves in the Solar Corona

TL;DR

This paper introduces a coherence-based method for automatically detecting and analyzing wave phenomena in solar corona EUV images, enabling real-time processing of large data volumes from solar observatories.

Contribution

The paper presents a novel coherence and travel-time based approach for robust wave detection in solar EUV images, suitable for near real-time analysis of large datasets.

Findings

Effective detection of transverse and longitudinal waves in TRACE data

Robust measurements of wave propagation speeds

Potential for automated processing of SDO/AIA data flow

Abstract

We consider the problem of automatically (and robustly) isolating and extracting information about waves and oscillations observed in EUV image sequences of the solar corona with a view to near real-time application to data from the Atmospheric Imaging Array (AIA) on the Solar Dynamics Observatory (SDO). We find that a simple coherence / travel-time based approach detects and provides a wealth of information on transverse and longitudinal wave phenomena in the test sequences provided by the Transition Region and Coronal Explorer (TRACE). The results of the search are "pruned" (based on diagnostic errors) to minimize false-detections such that the remainder provides robust measurements of waves in the solar corona, with the calculated propagation speed allowing automated distinction between various wave modes. In this paper we discuss the technique, present results on the TRACE test sequences, and describe how our method can be used to automatically process the enormous flow of data (~1Tb/day) that will be provided by SDO/AIA after launch in late 2008.