AI studies 100 years of Sun images to track bright solar regions from the Kodaikanal Solar Observatory

📌 Summary:

• Researchers used Artificial Intelligence (a U-Net supervised machine-learning model) to analyse 100 years (1916–2007) of hand-drawn Sun records ("suncharts") from the Kodaikanal Solar Observatory (KoSO)
• The model located the Sun's disk in each scanned drawing and traced "plages" (bright, magnetically active patches) across nine solar cycles (Cycles 15–23)
• Plages are a reliable "fingerprint" of the Sun's magnetism; digitising old archives links historical activity to modern space-age measurements
• Output: a "butterfly diagram" showing how magnetic activity shifts with latitude and solar-cycle phase
• Significance: a longer baseline for studying solar activity, which affects satellites, navigation and power grids on Earth
• Study led by Dibya Kirti Mishra (ARIES, under DST) with IIST Thiruvananthapuram, Southwest Research Institute (USA) and the Indian Institute of Astrophysics (IIA), Bangalore; published in the Astrophysical Journal

🎯 UPSC Relevance: GS3 – Science & Technology: space/solar physics and application of AI/ML to historical scientific archives by indigenous research institutions.

📝 Prelims Facts:

• KoSO = Kodaikanal Solar Observatory (Tamil Nadu); suncharts span 1904–2022
• ARIES is an autonomous institute under the Department of Science & Technology (DST)
• "Butterfly diagram" maps sunspot/plage latitude across solar cycles

🔑 Key Term: Plage – a bright region in the Sun's chromosphere linked to concentrated magnetic fields, used as a marker of solar activity.