The India Meteorological Department (IMD) on 12 May 2026 released the country's first artificial intelligence enabled block-level monsoon onset advance forecasting model in New Delhi, marking a major leap from district-level to sub-district granularity in operational monsoon prediction. Developed in collaboration with the Indian Institute of Tropical Meteorology Pune and the National Centre for Medium Range Weather Forecasting Noida, the system currently covers 3,196 blocks across 15 states and one Union Territory, largely in rainfed regions where the timing of monsoon onset is critical for sowing decisions. The model fuses outputs from existing numerical weather prediction systems with machine learning trained on the IMD historical archive, generating probabilistic forecasts every Wednesday for up to four weeks ahead with an error margin of about four days. Outputs will be shared with farmers through application programming interfaces designed by the Ministry of Agriculture and Farmers Welfare and pushed through the Agri Stack platform that powers the digital agriculture mission. Roughly 52 per cent of India cultivated area is rainfed, and block-level lead time is expected to improve choice of crop variety, fertiliser scheduling, crop insurance enrolment under PMFBY and labour planning. The IMD clarified that the new tool is independent of the seasonal long range outlook, which currently projects the 2026 southwest monsoon at around 92 per cent of the long period average. Coverage will be progressively expanded to additional states in the coming seasons.
India Meteorological Department on 12 May 2026 Releases Country's First AI-Enabled Block-Level Monsoon Onset Advance Forecasting Model Covering 3,196 Blocks Across 15 States and One Union Territory With Four-Week Lead Time and Four-Day Error Margin
IMD on 12 May 2026 launched India's first AI-enabled block-level monsoon onset forecasting model covering 3,196 blocks in 15 states and one UT with up to four-week lead time and four-day error, to support rainfed sowing decisions through Agri Stack APIs.
Key facts
- IMD on 12 May 2026 launched India's first AI-enabled block-level monsoon onset forecasting model in New Delhi.
- The system covers 3,196 blocks across 15 states and one Union Territory, largely in rainfed regions.
- Developed jointly with Indian Institute of Tropical Meteorology Pune and National Centre for Medium Range Weather Forecasting Noida.
- Forecasts are issued every Wednesday for up to four weeks with about a four-day error margin.
- Outputs flow to farmers via Ministry of Agriculture APIs and the Agri Stack platform under digital agriculture mission.
- About 52 per cent of India cultivated area is rainfed; the 2026 monsoon is expected at 92 per cent of long period average.
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How many blocks are covered by the AI-enabled block-level monsoon onset forecasting model launched by the India Meteorological Department on 12 May 2026?
IMD on 12 May 2026 launched the AI-based block-level monsoon onset model covering 3,196 blocks across 15 states and one Union Territory. The model issues weekly probabilistic forecasts up to four weeks ahead with about a four-day error margin.
Source: IMD / Business Standard
Frequently asked questions
What new system did the India Meteorological Department launch on 12 May 2026?
IMD launched the country first AI-enabled block-level monsoon onset advance forecasting model that issues probabilistic forecasts of monsoon arrival up to four weeks ahead with about a four-day error margin.
How many blocks and states does the new IMD model currently cover?
The system covers 3,196 blocks across 15 states and one Union Territory, mostly in rainfed regions critical for kharif sowing.
Which institutions partnered with IMD to develop the AI monsoon model?
It was developed in collaboration with the Indian Institute of Tropical Meteorology Pune and the National Centre for Medium Range Weather Forecasting Noida, in consultation with the Ministry of Agriculture and Farmers Welfare.
How will block-level forecasts reach farmers?
Forecast outputs will be delivered to farmers through application programming interfaces of the Ministry of Agriculture and integrated into the Agri Stack platform of the digital agriculture mission.
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