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Category — GS Paper 3 ///Published — 2026-05-14 ///Exam — Both Prelims and Mains ///Tags — Artificial Intelligence, Disaster Management, Indian Economy ///Category — GS Paper 3 ///Published — 2026-05-14 ///Exam — Both Prelims and Mains ///Tags — Artificial Intelligence, Disaster Management, Indian Economy ///

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India's AI Weather Forecasting Revolution

IMD has unveiled two cutting-edge AI-based weather forecasting tools - India's first AI-enabled monsoon forecasting system at block level and a 1-km resolution rainfall forecast for Uttar Pradesh. These developments, part of Mission Mausam and the Bharat Forecasting System, mark a significant milestone in disaster preparedness and agricultural strategy, with India becoming the only country to provide operational forecasts at 6-km granularity.

2026-05-14

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Key AI-Driven Weather Forecasting Systems

1. AI-enabled Forecast of Monsoon Advance

First of its kind: India's first AI-based monsoon forecasting system
Granularity: Provides forecasts at 'block level' (hyper-local)
Coverage: 16 States, more than 3,000 sub-districts within monsoon core zone
Update frequency: Probabilistic forecasts every Wednesday for next four weeks
Purpose: Helps farmers plan sowing, irrigation, crop protection, and harvesting
Technical approach: Blends AI-based models, statistical techniques, and global weather models using nearly a century of meteorological data
Developed by: IMD, IITM Pune, and NCMRWF

2. High Spatial Resolution Rainfall Forecast for Uttar Pradesh

Resolution: 1-km spatial resolution (pilot project)
Lead time: Up to 10 days in advance
Model: Uses Mithuna weather model (12.5 km resolution refined to 1 km)
Data sources: Automatic Rain Gauges, Automatic Weather Stations, Doppler Weather Radars, satellite-based rainfall datasets
Applications: Agriculture, water resources, disaster management, renewable energy, urban planning

Bharat Forecasting System (BharatFS)

Key Features

Resolution: 6 km (operational since May 2025)
Grid: Triangular Cubic Octahedral (TCO) grid
Supercomputing: Powered by 'Arka' (11.77 Peta FLOPS) and 'Arunika' (8.24 Peta FLOPS)
Accuracy improvements: 64% overall accuracy, 30% better extreme weather warnings
Lead times: Short-range (3 days) and medium-range (7 days)
Significance: India becomes the only country in the world to provide operational forecasts at 6-km granularity

Strategic Importance

Atmanirbhar Bharat: In-house development by IITM Pune
Reduced dependency: No longer solely reliant on US (NCEP) or Europe (ECMWF) models
Customized for Indian topography: Specifically calibrated for Himalayas and Western Ghats

Mission Mausam

Launch: 2024 under Ministry of Earth Sciences (MoES)
Objective: Make India 'Weather Ready' and 'Climate Smart'
Implementing agencies: IMD, IITM, NCMRWF
Infrastructure: Doppler radars, weather stations, supercomputers (Pratyush, Mihir)
Mausam App: Provides forecasts for 450 cities
Need: India's dependence on agriculture, increasing climate variability, frequent extreme weather events

Constitutional/Policy Context

Article 51A(g): Duty to protect and improve the natural environment
Disaster Management Act, 2005: Emphasizes early warning systems
National Disaster Management Plan: Integration of weather forecasting for disaster preparedness