Solar Magnetic Feature Detection and Tracking for Space Weather Monitoring

TL;DR

This paper introduces SMART, an automated system for detecting, tracking, and analyzing solar active regions using magnetogram data, providing detailed magnetic properties and tracking their evolution over time.

Contribution

The paper presents a novel automated algorithm, SMART, that improves detection and tracking of solar active regions and their magnetic properties from magnetogram data.

Findings

Number and area of magnetic regions vary with the solar cycle.

SMART provides direct magnetic diagnostics beyond sunspot proxies.

Regions can be tracked across multiple solar rotations.

Abstract

We present an automated system for detecting, tracking, and cataloging emerging active regions throughout their evolution and decay using SOHO Michelson Doppler Interferometer (MDI) magnetograms. The SolarMonitor Active Region Tracking (SMART) algorithm relies on consecutive image differencing to remove both quiet-Sun and transient magnetic features, and region-growing techniques to group flux concentrations into classifiable features. We determine magnetic properties such as region size, total flux, flux imbalance, flux emergence rate, Schrijver's R-value, R* (a modified version of R), and Falconer's measurement of non-potentiality. A persistence algorithm is used to associate developed active regions with emerging flux regions in previous measurements, and to track regions beyond the limb through multiple solar rotations. We find that the total number and area of magnetic regions on disk vary with the sunspot cycle. While sunspot numbers are a proxy to the solar magnetic field, SMART offers a direct diagnostic of the surface magnetic field and its variation over timescale of hours to years. SMART will form the basis of the active region extraction and tracking algorithm for the Heliophysics Integrated Observatory (HELIO).