Meteorologists and AI-based forecasting tools working together to predict and manage cyclones in India | Image: AI-Skymet
While cyclones can unleash unimaginable destruction, India has built a strong and coordinated system to track storms, warn communities, and minimize casualties. This effort brings together scientists, disaster managers, armed forces, and communication networks, all working in sync before, during, and after a cyclone makes landfall.
Forecasting and Tracking Agencies
- India Meteorological Department (IMD): The IMD, under the Ministry of Earth Sciences, is the primary cyclone forecasting authority in India. Recognized as the Regional Specialized Meteorological Centre (RSMC) for the North Indian Ocean, it not only issues warnings for India but also provides cyclone advisories to 12 neighboring countries. Using a network of Doppler weather radars, ground stations, and advanced satellite data from the INSAT series, the IMD continuously monitors storm formation, intensity, and movement.
- Indian Space Research Organisation (ISRO): ISRO plays a crucial supporting role by providing high-resolution satellite imagery through its INSAT and Oceansat satellites. These satellites help track cyclone eye formation, rainfall patterns, and wind speeds, vital inputs for accurate IMD forecasts.
Disaster Management and Response Agencies
- National Disaster Management Authority (NDMA): The NDMA is India’s apex body for disaster preparedness and mitigation. It formulates policies, coordinates large-scale evacuations, and ensures that relief measures are ready before a cyclone makes landfall.
- National Disaster Response Force (NDRF): The NDRF is the frontline rescue force during cyclones. Its specialized teams, equipped with search-and-rescue gear, inflatable boats, and medical kits, are deployed in advance to vulnerable coastal regions. They evacuate people, clear debris, and provide immediate relief.
- State Disaster Management Authorities (SDMAs): Every cyclone-hit state has its own SDMA, which works closely with the NDMA and district administrations. They manage local shelters, coordinate evacuations, and ensure relief materials like food, water, and medicines reach affected people.
- Armed Forces: The Army, Navy, Air Force, and Coast Guard are critical in post-landfall operations. The Navy and Coast Guard rescue fishermen at sea, while the Army and Air Force transport relief supplies, restore connectivity, and set up medical camps. Their heavy-lift helicopters and transport aircraft ensure aid reaches even the most inaccessible villages.
Communication and Warning Dissemination
- All India Radio (AIR) & Doordarshan: In rural and remote coastal areas where internet and mobile networks fail, these public broadcasters become lifelines by relaying cyclone alerts, safety instructions, and evacuation orders in local languages.
- Indian National Centre for Ocean Information Services (INCOIS): Based in Hyderabad, INCOIS provides specialized ocean forecasts, including storm surge warnings, high wave alerts, and potential coastal flooding zones—information that is crucial for fishermen and coastal authorities.
Through this multi-agency coordination, India has transformed its cyclone preparedness in the past two decades. The result is visible: while earlier cyclones like the 1999 Odisha Super Cyclone killed nearly 10,000 people, recent cyclones of similar intensity—such as Fani (2019) and Amphan (2020), saw far fewer casualties, thanks to early warnings, mass evacuations, and quick response systems.
Beyond Traditional Forecasting: The Rise of AI and Private Sector Innovation
While government agencies like the IMD remain the primary source for official weather forecasts, the field of climate prediction is being revolutionized by the convergence of massive datasets, powerful computing, and advanced AI models. Over the past decade, private companies and AI research labs have increasingly complemented official forecasts, using advanced models to improve predictions of severe weather events.
Aurora: Microsoft's Atmospheric Foundation Model
Microsoft's Aurora is an AI model designed to predict severe weather events with high resolution and speed. By training on petabytes of climate data, it aims to provide forecasts faster and with greater detail than is possible with conventional supercomputers. Aurora has shown improved ability to predict extreme weather events, such as sudden increases in wind speed during storms, outperforming other AI models in certain scenarios.
GraphCast: Google's AI-Driven Forecasting
GraphCast, developed by Google DeepMind, is an AI-based weather model that has demonstrated remarkable accuracy in medium-range forecasts (3–10 days). Trained on decades of historical weather data, it predicts weather patterns with high speed and efficiency, often outperforming traditional numerical weather prediction (NWP) models in certain parameters. Notably, GraphCast can generate a 10-day forecast in under a minute, significantly reducing computational energy costs.
Skymet Weather: India's Private Forecasting Pioneer
Established in 2003, Skymet Weather Services is a leading private company in India providing weather forecasts and climate-related services. Skymet Weather Services combines over 5,500 automatic weather stations, satellite data, and proprietary forecasting models to monitor and predict severe weather events, including cyclones, across India. By analyzing real-time data and historical patterns, it provides hyper-local alerts and forecasts, helping authorities, farmers, and industries prepare for potential disasters. Its services support risk management, crop insurance, and early warning systems, while the public-facing platform and app deliver timely cyclone warnings in multiple regional languages.
Skymet is currently advancing into the frontier of AI-assisted meteorology, developing proprietary systems that integrate machine learning (ML), neural network ensembles, and adaptive data assimilation algorithms to enhance the precision and speed of cyclone forecasting.
We aim to build a next-generation hybrid forecasting ecosystem capable of producing rapid, hyper-localized, and self-improving forecasts. This fusion of climatological expertise and AI innovation positions Skymet as a global contender in the emerging era of AI-driven meteorological intelligence—one that continuously learns from nature’s own data signatures to anticipate extreme weather with unprecedented accuracy. Do not miss:
