Increasing Lifetime of Recurrent Sunspot Groups within the Greenwich Photoheliographic Results
R. Henwood, S.C. Chapman, D.M. Willis

TL;DR
This study uses machine learning to analyze long-term changes in recurrent sunspot group lifetimes from historical data, revealing a century-long increase followed by a decline, with implications for solar activity understanding.
Contribution
The paper introduces a machine learning approach to identify recurrent sunspot groups in historical data, enabling analysis of lifetime changes over a century.
Findings
Sunspot group lifetime increased by 1.4 days between 1915 and 1940.
Recurrent sunspot groups exhibit a larger Gnevyshev-Waldmeier Relationship.
Evidence suggests a decline in sunspot group lifetime after 1950.
Abstract
Long-lived (>20 days) sunspot groups extracted from the Greenwich Photo- heliographic Results (GPR) are examined for evidence of decadal change. The problem of identifying sunspot groups which are observed on consecutive solar rotations (recurrent sunspot groups) is tackled by first constructing manually an example dataset of recurrent sunspot groups and then using machine learning to generalise this subset to the whole GPR. The resulting dataset of recurrent sunspot groups is verified against previous work by A. Maunder and other Royal Greenwich Observatory (RGO) compilers. Recurrent groups are found to exhibit a slightly larger value for the Gnevyshev-Waldmeier Relationship than the value found by Petrovay and van Driel-Gesztelyi (Solar Phys. 51, 25, 1997), who used recurrence data from the Debrecen Photoheliographic Results. Evidence for sunspot group lifetime change over the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
