Quantifying sunspot group nesting with density-based unsupervised clustering
Nurdan Karapinar, Emre Isik, Natalie A. Krivova, Hakan V. Senavci

TL;DR
This paper presents an automated density-based clustering method to quantify sunspot group nesting, revealing that about 60% of sunspot groups emerge within nests, with nesting degree correlating with solar activity levels.
Contribution
The study introduces a novel kernel density estimation and DBSCAN-based approach to identify and quantify sunspot nesting in long-term solar observations.
Findings
Approximately 60% of sunspot groups are within nests.
Nesting is strongest at mid-latitudes (10°-20°).
Nesting degree correlates with solar activity level.
Abstract
Sunspot groups often emerge in spatial-temporal clusters, known as nests or complexes of activity. Quantifying how frequently such nesting occurs is important for understanding the organisation and recurrence of solar magnetic fields. We introduce an automated approach based on kernel density estimation and DBSCAN clustering to identify nests in the longitude-time domain and to measure the fraction of sunspot groups that belong to them. The method combines a smooth representation of emergence patterns with a density-based clustering procedure, validated using synthetic solar-like cycles and corrected for variations in data density. We apply this method to 151 years of sunspot-group observations from the Royal Greenwich Observatory Photoheliographic Results (RGO, 1874-1976) and Kislovodsk Mountain Astronomical Station (KMAS, 1955-2025) catalogues. Across all cycles and latitude bands,…
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Taxonomy
TopicsSolar and Space Plasma Dynamics · Stellar, planetary, and galactic studies · Electrical and Electromagnetic Research
