http://arxiv.org/abs/2304.06615
Bipolar Magnetic Regions (BMRs) provide crucial information about solar magnetism. They exhibit varying morphology and magnetic properties throughout their lifetime, and studying these properties can provide valuable insights into the workings of the solar dynamo. The majority of previous studies have counted every detected BMR as a new one and have not been able to study the full life history of each BMRs. To address this issue, we have developed an Automatic Tracking Algorithm (AutoTAB) for BMRs, that tracks the BMRs for their entire lifetime or throughout their disk passage. AutoTAB uses the binary maps of detected BMRs to automatically track the regions. This is done by differentially rotating the binary maps of the detected regions and checking for overlaps between them. In this first article of this project, we provide a detailed description of the working of the algorithm and evaluate its strengths and weaknesses. We also compare its performance with other existing tracking techniques. AutoTAB excels in tracking even for the small features and it successfully tracks 9152 BMRs over the last two solar cycles (1996-2020), providing a comprehensive dataset that depicts the evolution of various properties for each tracked region. The tracked BMRs follow familiar properties of solar cycles except for these small BMRs that appear at all phases of the solar cycle and show weak latitudinal dependency, which is represented through the butterfly diagram. Finally, we discuss the possibility of adapting our algorithm to other datasets and expanding the technique to track other solar features in the future.
A. Sreedevi, B. Jha, B. Karak, et. al.
Fri, 14 Apr 23
2/64
Comments: 14 pages including 9 figures; Submitted in ApJS; Comments are welcome