MoES AI Monsoon Forecasts: Block-Level and 1-km Rainfall
Why in the news
The Union Minister for Earth Sciences launched two AI-enabled forecasting tools from MoES. They move Indian weather prediction from broad district-level outlooks to block-level and even 1-km resolution, to help farmers, urban planners and disaster managers make real-time decisions.
Key facts
- Developers: IMD, IITM Pune and NCMRWF, all MoES bodies.
- Reach: 16 states, over 3,000 sub-districts (blocks).
- Horizon: up to 10 days for rainfall; up to 4 weeks for monsoon advance.
The two systems compared
| Feature | AI-enabled Forecast of Monsoon Advance | High Spatial Resolution Rainfall Forecast |
|---|---|---|
| Resolution | Block level, a first for India | 1 km (downscaled from 12.5 km) |
| Coverage | 3,196 blocks, 15 states and 1 UT, mainly the rainfed monsoon core zone | Uttar Pradesh (pilot) |
| Lead time | Weekly probabilistic updates, up to 4 weeks | 10 days |
| Base / data | About 100 years of IMD data, global models and AI analytics | Mithuna model; AWS network, Doppler radars, satellite data |
| Use | Feeds the Agriculture Ministry’s advisory pipeline for sowing and irrigation | Urban planning, water management, disaster mitigation |
The first system also follows the monsoon’s progress from its onset over Kerala.
Significance
- Block-level forecasts let villages time sowing, irrigation and harvest, and cut crop loss from erratic rain.
- Uttar Pradesh was picked as the most populous state, with big farm belts, dense cities, flood, heat and drought exposure, and a thick observation network.
- AI helps by spotting patterns in large datasets, downscaling coarse outputs, giving probabilistic and impact-based forecasts, and improving as data grows.
- Urban planners gain for drainage, flood control and reservoir operation.
Background
- MoES: oversees atmospheric science (IMD, IITM, NCMRWF), oceanography (INCOIS, NIOT), geosciences, polar research and seismology.
- IMD: set up in 1875; national weather service; works under MoES.
- IITM: Pune, established 1962; autonomous MoES institute for tropical meteorology and monsoon research.
- NCMRWF: Noida; medium-range (3-10 day) forecasting.
- Monsoon core zone: central India (parts of MP, Chhattisgarh, Maharashtra, Odisha), largely rainfed.
- Probabilistic forecast: states a chance of rain rather than a single yes/no outcome.
- Mission Mausam: scheme to modernise weather and climate services; the push also covers the Bharat Forecast System and more radars and AWS.
Why monsoon forecasting matters
- About 50% of net sown area is rainfed.
- Agriculture supports around 45% of employment.
- Reservoirs, hydropower, drinking water, food inflation and flood-drought risk all follow the monsoon.
Exam angle
- Nodal ministry: Earth Sciences; institutions: IMD, IITM, NCMRWF.
- Numbers: 3,196 blocks; 1 km vs 12.5 km; 4 weeks and 10 days.
- Southwest monsoon (June-September) brings about 75% of annual rainfall.