An AI-powered, localised rainfall forecast system developed specifically for Uttar Pradesh on a pilot basis, was launched in New Delhi by Jitendra Singh, minister of state (independent charge) on Tuesday.
The forecast system features a high spatial resolution of up to 1 km and covers a 10-day outlook.
Jitendra Singh said the initiative would be particularly useful for agriculture, water resources, renewable energy, urban planning, disaster management and infrastructure sectors. He said farmers will now be able to make more informed decisions relating to sowing, irrigation, crop protection and harvest planning with far greater local precision.
The services of this system will be available during the upcoming 2026 monsoon season.
This system, which utilises an AI-based mechanism to forecast monsoon advancement across various parts of the country, was developed under the aegis of “Mission Mausam,” an initiative operated by the ministry of earth sciences, government of India, a release issued by Lucknow meteorological department, read.
The minister said the high spatial resolution rainfall forecast for Uttar Pradesh, has been developed as a pilot service to generate rainfall forecasts at 1-km spatial resolution up to 10 days in advance. The system uses advanced AI-driven downscaling techniques and integrates data from Automatic Rain Gauges (ARGs), Automatic Weather Stations (AWSs), Doppler Weather Radars and satellite-based rainfall datasets.
“The two products launched today include, introduction of the first artificial intelligence (AI)-driven system by India Meteorological Department (IMD) in the form of AI-enabled ‘Forecast of Monsoon Advance over Different Parts of the Country’ and a ‘High Spatial Resolution Rainfall Forecast for Uttar Pradesh’ as a pilot service. The systems have been developed jointly by the IMD, Indian Institute of Tropical Meteorology (IITM), Pune, and National Centre for Medium Range Weather Forecasting (NCMRWF),” the release read.
The minister said the newly launched systems mark a major shift from conventional weather forecasting towards impact-based and decision-support forecasting, capable of providing precise, location-specific and actionable information to farmers, administrators, disaster managers and citizens.
Referring to the rapid modernisation of India’s weather infrastructure, Jitendra Singh said the country had barely 16 to 17 Doppler Weather Radars nearly a decade ago, while the number has now increased to around 50, with another 50 planned under Mission Mausam.
He said this expansion of observational networks, automatic weather stations, high-performance computing systems and digital dissemination platforms has substantially improved forecasting capability and early warning systems across the country.