“Uttar Pradesh is leveraging cutting-edge weather technology to enhance disaster prediction, utilizing AI, supercomputers, and Doppler radars. The state’s upgraded systems provide hyperlocal forecasts, improving preparedness for floods, heatwaves, and storms. These advancements aim to protect lives, agriculture, and infrastructure, aligning with India’s push for precise, real-time weather forecasting to combat climate-driven disasters.”
Uttar Pradesh Bolsters Disaster Preparedness with Advanced Weather Technology
Uttar Pradesh, India’s most populous state, is at the forefront of adopting advanced weather forecasting technologies to mitigate the impact of natural disasters, which have become more frequent due to climate change. The state has integrated artificial intelligence (AI), machine learning (ML), and high-resolution supercomputing systems to enhance the accuracy of weather predictions, particularly for extreme events like floods, heatwaves, and thunderstorms.
The India Meteorological Department (IMD), in collaboration with the Uttar Pradesh State Disaster Management Authority (UPSDMA), has deployed state-of-the-art tools to provide hyperlocal weather forecasts at a resolution of 6 kilometers, a significant improvement over the previous 12-km models. The Bharat Forecasting System (BFS), powered by the Arka supercomputer at the Indian Institute of Tropical Meteorology (IITM), is a cornerstone of this initiative. Launched in May 2025, BFS offers real-time predictions up to 10 days in advance, enabling precise forecasting at the village and panchayat levels. This granularity is critical for a state like Uttar Pradesh, where diverse geography—from the Gangetic plains to the Himalayan foothills—poses unique challenges for disaster management.
AI and ML algorithms are central to UP’s weather forecasting upgrades. These technologies analyze vast datasets, including satellite imagery, Doppler radar inputs, and historical weather patterns, to predict short-term events like thunderstorms and long-term phenomena like monsoons. The IMD’s regional center in Lucknow has been equipped with AI-driven models that provide early warnings for heatwaves, floods, and lightning strikes, which claimed over 600 lives in Uttar Pradesh in 2023 alone, according to the Centre for Science and Environment (CSE). By processing real-time data, these models have improved forecast accuracy by up to 64%, particularly for heavy rainfall and cyclone tracking.
Doppler radar networks, expanded across Uttar Pradesh in 2024, play a pivotal role in monitoring weather systems. These radars, installed in cities like Lucknow, Varanasi, and Kanpur, provide high-resolution data on precipitation, wind patterns, and storm development. The state has also integrated the System for Assessing, Tracking, and Alerting Disaster Risk Information (SATARK), developed by the Odisha State Disaster Management Authority in collaboration with the Regional Integrated Multi-Hazard Early Warning System (RIMES). SATARK delivers real-time alerts for multiple hazards, including floods, lightning, and heatwaves, with user-friendly advisories tailored for disaster managers and the public.
The adoption of these technologies has had tangible impacts. During the 2024 monsoon season, hyperlocal forecasts enabled authorities to issue timely flood alerts in districts like Gorakhpur and Ballia, reducing casualties and property damage. The UPSDMA utilized BFS data to preposition relief teams and resources, minimizing the impact of flash floods in eastern Uttar Pradesh. Additionally, farmers in the state, who rely heavily on monsoon rains, have benefited from agro-meteorological advisories delivered via SMS to over 25 million mobile users, aiding crop planning and reducing losses due to unseasonal weather.
Despite these advancements, challenges remain. Data scarcity, particularly in the Himalayan regions of Uttar Pradesh, hampers AI model reliability. Experts like Irfan Rashid from the University of Kashmir emphasize the need for standardized data collection on glaciers and glacial lakes to improve predictions of glacial lake outburst floods (GLOFs), which threaten northern districts like Pithoragarh. The state is addressing this through partnerships with institutions like the Wadia Institute of Himalayan Geology, which is developing AI-based early warning systems for glacial hazards.
Uttar Pradesh’s investment in weather technology aligns with India’s broader “Mission Mausam,” launched in 2023 to enhance forecasting infrastructure. The state’s collaboration with the IMD and IITM has positioned it as a leader in disaster preparedness, with plans to further expand radar networks and computing capabilities by 2026. These efforts are critical as extreme weather events, which affected Uttar Pradesh on 113 days in 2023, continue to rise in frequency and intensity.
Disclaimer: This article is based on recent reports, meteorological data, and expert insights from sources like the India Meteorological Department, Centre for Science and Environment, and news outlets such as The Hindu and Times of India. Information is accurate as of August 2025, but weather forecasting technologies and data may evolve.