First SDO AIA Observations of a Global Coronal EUV "Wave": Multiple Components and "Ripples"

TL;DR

This paper reports the first detailed observations of a global coronal EUV disturbance with multiple components and ripples, revealing complex wave and non-wave behaviors driven by a CME, thanks to high-cadence AIA data.

Contribution

It provides the first detailed observation of a multi-component EUV wave with ripples, demonstrating the coexistence of wave and non-wave features in coronal disturbances.

Findings

The disturbance has a diffuse pulse and multiple sharp fronts.

Fast sharp fronts overtake slow fronts, creating ripples.

The diffuse pulse maintains coherence over 30 minutes.

Abstract

We present the first SDO AIA observations of a global coronal EUV disturbance (so-called "EIT wave") revealed in unprecedented detail. The disturbance observed on 2010 April 8 exhibits two components: one diffuse pulse superimposed on which are multiple sharp fronts that have slow and fast components. The disturbance originates in front of erupting coronal loops and some sharp fronts undergo accelerations, both effects implying that the disturbance is driven by a CME. The diffuse pulse, propagating at a uniform velocity of 204-238 km/s with very little angular dependence within its extent in the south, maintains its coherence and stable profile for ~30 minutes. Its arrival at increasing distances coincides with the onsets of loop expansions and the slow sharp front. The fast sharp front overtakes the slow front, producing multiple "ripples" and steepening the local pulse, and both fronts propagate independently afterwards. This behavior resembles the nature of real waves. Unexpectedly, the amplitude and FWHM of the diffuse pulse decrease linearly with distance. A hybrid model, combining both wave and non-wave components, can explain many, but not all, of the observations. Discoveries of the two-component fronts and multiple ripples were made possible for the first time thanks to AIA's high cadences (10-20 s) and high signal-to-noise ratio.