Principal component analysis of sunspot cycle shape
Jouni Takalo, Kalevi Mursula

TL;DR
This study applies principal component analysis to sunspot cycle data to identify typical cycle shapes, analyze asymmetry, validate Waldmeier rules, and interpret the Gnevyshev gap, revealing patterns related to cycle symmetry and activity.
Contribution
It introduces a PCA-based approach to characterize sunspot cycle shapes and asymmetries, providing new insights into cycle classification and the Gnevyshev gap.
Findings
Model cycles are mostly even-numbered cycles.
Odd cycles tend to be more asymmetric.
Waldmeier rules are generally valid, with some variations.
Abstract
We study the shape of sunspot cycles using the Wolf sunspot numbers and group sunspot numbers of solar cycles 1-23. We determine the most typical "model" cycles and the most asymmetric cycles, and test the validity of the two Waldmeier rules: the anti-correlation between cycle height and the length of its ascending phase (rule 1), and between cycle height and the length of the preceding cycle (rule 2). We applied the principal component analysis to sunspot cycles and studied the first two components, which describe the average cycle shape and cycle asymmetry, respectively. We also calculated their autocorrelation in order to study their recurrence properties. The best model cycles for Wolf numbers are SC12, SC14, and SC16, the successive even cycles from a long period of rather low overall solar activity. We find that the model cycles in eight different analyses using both sunspot…
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