论文标题
使用Kodaikanal太阳天文台档案库中的Suncharts使用聚类方法检测太阳丝
Detection of Solar Filaments using Suncharts from Kodaikanal Solar Observatory Archive Employing a Clustering Approach
论文作者
论文摘要
有了超过100年的太阳观测，Kodaikanal太阳能天文台（KOSO）是世界上一种独一无二的太阳能数据存储库。在其许多数据目录中，Koso的“阳光”特别感兴趣。这些阳台（1904-2020）是不同太阳能特征的彩色图纸，例如黑子，诗篇，细丝和隆隆声，在纸上刻有刻有stonyhurst stonyhurst stonyhurst stonyhurst stone niture grid网格上。在本文中，我们通过使用行业标准的扫描仪首先将每个固定器数字化并以高分辨率的“ .tif”格式保存这些数字图像来分析这些独特的数据。然后，我们检查了〜19周期和〜20个数据（上个世纪最强的周期中的两个），目的是检测细丝。为此，我们采用了“ K-均值聚类”方法，并获得了不同的细丝参数，例如位置，倾斜角，长度和面积。我们的结果表明，灯丝长度（和面积）随纬度的增加而增加，而极向迁移显然由特定的倾斜标志主导。最后，我们通过KOSO数字化摄影板数据库的结果进行了交叉验证的发现，并在它们之间获得了良好的一致性。这项作品作为概念证明，将启动新的努力，以有效地使用整个手绘的多种功能，全盘太阳能数据，并使研究人员能够提取新科学，例如在过去100年中产生的伪磁图。
With over 100 years of solar observations, the Kodaikanal Solar Observatory (KoSO) is a one-of-a-kind solar data repository in the world. Among its many data catalogues, the `suncharts' at KoSO are of particular interest. These Suncharts (1904-2020) are coloured 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 suncharts using an industry-standard scanner and saving those digital images in high-resolution `.tif' format. We then examine the 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 `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 pole-ward 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-the-concept, will kick-start new efforts to effectively use the entire hand-drawn series of multi-feature, full-disk solar data and enable researchers to extract new sciences, such as the generation of pseudo magnetograms for the last 100 years.
