- Why in news
- On 12 May 2026, Dr Jitendra Singh launched two Ministry of Earth Sciences forecast products in New Delhi: IMD's first AI-driven monsoon advance forecast, and a 1-km rainfall forecast pilot for Uttar Pradesh.
- What it is
- These are two forecast services built jointly by IMD, IITM Pune and NCMRWF under the Ministry of Earth Sciences. One gives probabilistic forecasts of monsoon progression using AI models. The other uses AI downscaling to give very fine-scale rainfall forecasts. Both aim at impact-based, location-specific advice for farmers and administrators.
- Developers
- IMD, IITM Pune and NCMRWF jointly developed both systems under MoES.
- Monsoon advance forecast
- Probabilistic forecasts of monsoon progression are issued every Wednesday, up to four weeks ahead.
- Coverage
- The monsoon product serves farmers in 16 States and over 3,000 sub-districts, through the Agriculture Ministry's dissemination framework.
- Uttar Pradesh pilot
- A pilot gives rainfall forecasts at 1-km resolution up to 10 days ahead, using AI downscaling.
- Data inputs
- The UP system uses automatic rain gauges, automatic weather stations, Doppler radars and satellite rainfall data.
- Doppler radars
- India had 16-17 Doppler Weather Radars about a decade ago; now around 50, with another 50 planned under Mission Mausam.
Don’t confuse with IMD vs IITM vs NCMRWF: IMD issues operational forecasts; IITM Pune is a research institute on tropical meteorology; NCMRWF runs medium-range numerical weather prediction. All fall under MoES.
Don’t confuse with Downscaling vs forecasting: Downscaling converts coarse model output to finer local resolution; it is not a separate forecast model.
Science and technology: 57 Prelims questions since 2013; most test the concept behind the news, not the news itself. In Mains, 12 news-triggered questions.
Why it matters
- Local, impact-based forecasts help farmers decide sowing, irrigation and harvest timing.
- Better early warnings support disaster management and sectors like water, energy and urban planning.
Problems
- Fine-scale forecasts need dense observation networks, which exist unevenly, so the UP service is only a pilot.
- Last-mile delivery and administrative compliance with advisories decide real impact.
Way forward
- Expand observation networks (radars, AWS, rain gauges) under Mission Mausam so services can extend to other States.
- Strengthen multi-channel advisory dissemination and local response capacity.
Put in your answer
Forecast accuracy: The Minister claimed about 40% better accuracy for severe weather forecasts over the last decade compared to the previous one.
Cyclone forecasts: 72-hour cyclone track, intensity and landfall forecasts improved by about 30-35% in five years.
Dissemination channels: Advisories reach people via mobile apps, SMS, WhatsApp, Kisan portals and TV.
- 2026Mains GS1 · Q15Role of satellite technologies in climate-smart agriculture and food security
- 2022Mains GS1 · Q5Meaning of IMD colour-coded weather warnings for cyclone-prone areas
- 2017Prelims Q66Indian Ocean Dipole's definition and its influence on monsoon
- 2026Prelims Q84Bharat Forecast System's objective and developing institution
UPSC’s own questions that come close to this issue, from our Prelims and Mains banks.
No practice question for this one; the card may still help an answer. Why: A lasting topic in weather technology; facts are mostly product details, so a Prelims question is unlikely.
Worth revising until Prelims 2027: most news questions come within two years of the event.