Detection of Solar Filaments Using Suncharts from Kodaikanal Solar Observatory Archive Employing a Clustering Approach

Abstract

With over 100 yr of solar observations, the Kodaikanal Solar Observatory (KoSO) is a one-of-a-kind solar data repository in the world. Among its many data catalogs, the “suncharts” at KoSO are of particular interest. These suncharts (1904–2020) are colored drawings of different solar features, such as sunspots, plages, filaments, and prominences, made on papers with a Stonyhurst latitude–longitude grid etched on them. In this paper, we analyze this unique data by first digitizing each sunchart using an industry-standard scanner and saving those digital images in a high-resolution “.tif” format. We then examine cycle 19 and cycle 20 data (two of the strongest cycles of the last century) with the aim of detecting filaments. To this end, we employed the “K-means clustering” method, and obtained different filament parameters such as position, tilt angle, length, and area. Our results show that filament length (and area) increases with latitude and the poleward migration is clearly dominated by a particular tilt sign. Lastly, we cross verified our findings with results from KoSO digitized photographic plate database for the overlapping time period and obtained a good agreement between them. This work, acting as a proof-of-theconcept, will kickstart new efforts to effectively use the entire hand-drawn series of multifeature, full-disk solar data and enable researchers to extract new sciences, such as the generation of pseudomagnetograms for the last 100 yr.