A New Space Weather Tool for Identifying Eruptive Active Regions

One of the main goals of solar physics is the timely identification of eruptive active regions. Space missions such as Solar Orbiter or future space weather forecasting missions would largely benefit from this achievement. Our aim is to produce a relatively simple technique that can provide real-tim...

Full description

Saved in:
Bibliographic Details
Published in:The Astrophysical journal 2019-12, Vol.886 (2), p.81
Main Authors: Pagano, Paolo, Mackay, Duncan H., Yardley, Stephanie L.
Format: Article
Language:English
Subjects:
Astrophysics
Eruptions
Risk
Signatures
Simulation
Solar active region magnetic fields
Solar active regions
Solar coronal mass ejections
Solar magnetic fields
Solar Orbiter (ESA)
Solar orbits
Solar physics
Space missions
Space weather
Weather forecasting
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:One of the main goals of solar physics is the timely identification of eruptive active regions. Space missions such as Solar Orbiter or future space weather forecasting missions would largely benefit from this achievement. Our aim is to produce a relatively simple technique that can provide real-time indications or predictions that an active region will produce an eruption. We expand on the theoretical work of Pagano et al. that was able to distinguish eruptive from non-eruptive active regions. From this, we introduce a new operational metric that uses a combination of observed line-of-sight magnetograms, 3D data-driven simulations, and the projection of the 3D simulations forward in time. Results show that the new metric correctly distinguishes active regions as eruptive when observable signatures of eruption have been identified and as non-eruptive when there are no observable signatures of eruption. After successfully distinguishing eruptive from non-eruptive active regions we illustrate how this metric may be used in a "real-time" operational sense were three levels of warning are categorized. These categories are: high risk (red), medium risk (amber), and low risk (green) of eruption. Through considering individual cases, we find that the separation into eruptive and non-eruptive active regions is more robust the longer the time series of observed magnetograms used to simulate the build up of magnetic stress and free magnetic energy within the active region. Finally, we conclude that this proof of concept study delivers promising results where the ability to categorize the risk of an eruption is a major achievement.
ISSN:0004-637X
1538-4357
DOI:10.3847/1538-4357/ab4cf1