| Name: | Sreejith Padinhatteeri |
| Affiliation: | Manipal Academy of Higher Education |
| Conference ID : | ASI2024_1001 |
| Title : | An automated algorithm to classify Sunspot groups |
| Authors : | Sreejith Padinhatteeri 1, H. N. Adithya 1
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| Authors Affiliation: | 1. Manipal Centre for Natural Sciences, Manipal Academy of Higher Education, Manipal - 576104 |
| Mode of Presentation: | Poster |
| Abstract Category : | Sun, Solar System, Exoplanets, and Astrobiology |
| Abstract : | Sunspots are dark features that appear on the photosphere due to a strong magnetic field. There are various classification schemes for sunspot groups based on their morphological and magnetic properties. The most commonly used classification is the Mt Wilson scheme, where sunspots are categorized into different groups such as Alpha, Beta, Gamma, and Delta based on their magnetic complexity. However, the current classifications are done manually with human interference, which results in delays, biases, and human errors.
Several successful attempts have been made to automate the classification methods using modern computational tools. In this work, we present an algorithm that automatically categorises sunspot groups into the Mt Wilson classification. The algorithm is tested using the continuum and magnetogram data from the Helioseismic and Magnetic Imager (HMI) onboard NASA's Solar Dynamic Observatory (SDO).
Furthermore, we discuss the need to develop a new classification scheme that includes information from the chromosphere and corona. This will help to improve the accuracy of the classification and provide better meaning to the sunspot groups coupling with the upper atmosphere. |
