AI traces 100 years of Kodaikanal Sun records
Next story · 1 Jul11 years of Digital India
A team led by ARIES, an autonomous institute of DST, used machine learning (U-Net) to read hand-drawn sun charts from the Kodaikanal Solar Observatory. It traced bright magnetic patches called plages from 1916 to 2007, across nine solar cycles. The results match Kodaikanal’s Ca II K images and can fill gaps in long-term solar data.
- Release
- 1 Jul 2026, Ministry of Science and Technology
- Lead institute
- ARIES (DST autonomous institute) with IIST, IIA and a US partner
- Data
- Kodaikanal Solar Observatory suncharts, 1904 to 2022
- Period studied
- 1916 to 2007, Solar Cycles 15 to 23
- Method
- supervised machine learning (U-Net)
- Journal
- Astrophysical Journal
AI on Kodaikanal sun charts: what happened?
For over a century, observers at Kodaikanal drew the Sun by hand every day. Those drawings hold a long memory of the Sun’s moods. Old paper and different drawing styles made them hard to use, until AI learned to read them.
- Step one: the model found the Sun’s disk in each scan, fixing its centre, size and tilt.
- Step two: it traced plages, the bright magnetic patches, across the drawings.
- The result is a “butterfly diagram” showing how activity shifts in latitude through each cycle.
- Plage areas from drawings match those from Ca II K full-disk observations.
Why do long solar records matter?
- Solar cycles drive sunspots, flares and eruptions that can disrupt satellites, navigation and power on Earth.
- Long, consistent records help compare cycles and understand space weather risk.
Why does AI on Kodaikanal sun charts matter?
- Science: Turns old archives into machine-readable data.
- Space weather: Longer records improve risk understanding for satellites and grids.
What can Prelims ask on AI on Kodaikanal sun charts?
- Kodaikanal Solar Observatory suncharts: 1904 to 2022.
- AI (U-Net) traced plages from 1916 to 2007, Solar Cycles 15 to 23.
- Plages: bright, magnetically active patches; a fingerprint of solar magnetism.
How to use this in Mains
- As per PIB (2026-07-01): AI scanned hand-drawn Sun records (1916–2007) from Kodaikanal Solar Observatory to trace magnetically active regions.
- A century of records shows long-term solar cycles.
Quotable data pointAI scanned hand-drawn Sun records (1916–2007) from Kodaikanal Solar Observatory to trace magnetically active regions.
PIB: S&T: AI and Kodaikanal records, 1 Jul 2026
Exam angle
Prelims: observatories.
Practice MCQs
Original practice questions (not PYQs).
The Kodaikanal Solar Observatory sun-chart study of 2026 used AI to trace which solar feature?
Answer (b) & explanation
PIB (S&T), 1 Jul 2026.
Questions students ask about this
What did the AI study of Kodaikanal records do?
It used machine learning to read hand-drawn sun charts and trace solar plages from 1916 to 2007.
What are plages?
Bright, magnetically active patches on the Sun, a reliable fingerprint of its magnetism.
Why is this useful?
It builds long, consistent records of solar magnetic activity that help understand space weather risks to technology on Earth.
Keep studying
Go deeper
Official source: PIB: S&T: AI and Kodaikanal records, 1 Jul 2026
facts from cited sources only; faculty review pending