Spot cycle reconstruction: an empirical tool - Application to the sunspot cycle

TL;DR

This paper presents an empirical tool for reconstructing sunspot cycles based on solar data, enabling realistic simulations of sunspot properties and revealing limitations in existing area-lifetime relations.

Contribution

The authors develop a stochastic, empirical model for sunspot cycle reconstruction that accurately reproduces observed solar cycle properties and proposes a correction to the area-lifetime rule.

Findings

The model successfully replicates main sunspot cycle features.

The Gnevyshev-Waldmeier rule is inadequate for small sunspot groups.

A corrected area-lifetime relation improves synthetic cycle accuracy.

Abstract

The increasing interest in understanding stellar magnetic activity cycles is a strong motivation for the development of parameterized starspot models which can be constrained observationally. In this work we develop an empirical tool for the stochastic reconstruction of sunspot cycles, using the average solar properties as a reference. The synthetic sunspot cycle is compared with the sunspot data extracted from the National Geophysical Data Center, in particular using the Kolmogorov-Smirnov test. This tool yields synthetic spot group records, including date, area, latitude, longitude, rotation rate of the solar surface at the group's latitude, and an identification number. Comparison of the stochastic reconstructions with the daily sunspot records confirms that our empirical model is able to successfully reproduce the main properties of the solar sunspot cycle. As a by-product of this work, we show that the Gnevyshev-Waldmeier rule, which describes the spots' area-lifetime relation, is not adequate for small groups and we propose an effective correction to that relation which leads to a closer agreement between the synthetic sunspot cycle and the observations.