Iterative construction of the optimal sunspot number series

TL;DR

The paper introduces an iterative algorithm to construct a stable, representative sunspot number series by optimally combining multiple observer data, accounting for observational changes and providing uncertainty estimates.

Contribution

It presents a novel iterative method for creating a consistent sunspot number series from diverse observations, improving upon previous reconstructions.

Findings

Results comparable to recent sunspot reconstructions.

Method accounts for observer changes and observational conditions.

Provides uncertainty estimates for the reconstructed series.

Abstract

The relative number of sunspots represents the longest evidence describing the level of solar activity. As such, its use goes beyond solar physics, e.g. towards climate research. The construction of a single representative series is a delicate task which involves a combination of observation of many observers. We propose a new iterative algorithm that allows to construct a target series of relative sunspot number of a hypothetical stable observer by optimally combining series obtained by many observers. We show that our methodology provides us with results that are comparable with recent reconstructions of both sunspot number and group number. Furthermore, the methodology accounts for the possible non-solar changes of observers' time series such as gradually changing observing conditions or slow change in the observers vision. It also provides us with reconstruction uncertainties. We apply the methodology to a limited sample of observations by \v{C}ESLOPOL network and discuss its properties and limitations.