Group Sunspot Numbers: A New Reconstruction of Sunspot Activity Variations from Historical Sunspot Records Using Algorithms from Machine Learning

Historical sunspot records and the construction of a comprehensive database are among the most sought after research activities in solar physics. Here, we revisit the issues and remaining questions on the reconstruction of the so-called group sunspot numbers (GSN) that was pioneered by D. Hoyt and colleagues. We use the modern tools of artificial intelligence (AI) by applying various algorithms based on machine learning (ML) to GSN records. The goal is to offer a new vision in the reconstruction of sunspot activity variations, i.e. a Bayesian reconstruction, in order to obtain a complete probabilistic GSN record from 1610 to 2020. This new GSN reconstruction is consistent with the historical GSN records. In addition, we perform a comparison between our new probabilistic GSN record and the most recent GSN reconstructions produced by several solar researchers under various assumptions and constraints. Our AI algorithms are able to reveal various new underlying patterns and channels of variations that can fully account for the complete GSN time variability, including intervals with extremely low or weak sunspot activity like the Maunder Minimum from 1645 -1715. Our results show that the GSN records are not strictly represented by the 11-year cycles alone, but that other important timescales for a fuller reconstruction of GSN activity history are the 5.5-year, 22-year, 30-year, 60-year, and 120-year oscillations. The comprehensive GSN reconstruction by AI/ML is able to shed new insights on the nature and characteristics of not only the underlying 11-year-like sunspot cycles but also on the 22-year Hale's polarity cycles during the Maunder Minimum, among other results previously hidden so far. In the early 1850s, Wolf multiplied his original sunspot number reconstruction by a factor of 1.25 to arrive at the canonical Wolf sunspot numbers (WSN). Removing this multiplicative factor, we find that the GSN and WSN differ by only a few percent for the period 1700 to 1879. In a comparison to the international sunspot number (ISN) recently recommended by Clette et al. (Space Sci. Rev. 186, 35, 2014), several differences are found and discussed. More sunspot observations are still required. Our article points to observers that are not yet included in the GSN database.