How accurate are India’s cyclone forecasts and how have they saved lives over the years?

India’s ability to predict cyclones has improved markedly over the last decade, with measurable gains in forecast accuracy for cyclone track, intensity, and landfall location. Data presented in Parliament shows that these scientific advancements have played a crucial role in reducing loss of life, even as cyclonic activity continues to affect the Indian coastline.

According to year-wise analysis by the India Meteorological Department (IMD) for the period from 2016 to 2025, cyclone forecasting accuracy has improved significantly due to continuous upgrades in observation systems, numerical weather prediction models, data assimilation techniques, and warning dissemination mechanisms. Compared to the period between 2016 and 2020, forecast accuracy during 2021–2025 improved by about 20–25 per cent for cyclone track prediction and by 35–45 per cent for landfall and intensity forecasts.

Tracking forecast error data over the ten years shows a consistent decline in average errors, particularly at shorter lead times such as 12, 24, and 48 hours. In several recent years, 12-hour and 24-hour forecast errors remained well below earlier decade averages, reflecting improved model resolution and better use of satellite, radar, and ocean-based observations. Even at longer lead times—up to 120 hours—forecast precision has steadily improved, enabling authorities to plan evacuations and emergency responses well in advance.

A similar trend is evident in cyclone intensity forecasts, measured in knots of maximum sustained wind. Average intensity forecast errors have declined over the years, with particularly sharp improvements observed after 2020. By 2025, 12-hour and 24-hour intensity forecast errors dropped to among the lowest levels recorded in the decade, demonstrating the growing reliability of IMD’s storm-strength predictions. These improvements are critical for estimating potential damage and planning coastal safety measures.

Landfall point prediction, often the most crucial factor for disaster preparedness, has also become more accurate. Annual average landfall errors at shorter lead times have reduced substantially in several recent years, allowing for more precise identification of vulnerable districts. While longer lead-time errors still vary depending on storm behaviour, overall accuracy has improved enough to support early evacuation and targeted disaster response.

This progress in forecasting has translated into a sharp reduction in cyclone-related fatalities across the country. Data compiled by the National Crime Records Bureau for the period 2014–2023 shows a clear downward trend in deaths despite multiple cyclones making landfall. For instance, total deaths across India fell from 133 in 2017 and 125 in 2018 to just 9 in 2022 and 2 in 2023. During this period, cyclones continued to strike coastal states, but improved early warnings and timely action by central and state governments significantly limited casualties.

State-wise data highlights that traditionally vulnerable regions such as Andhra Pradesh, Odisha, Tamil Nadu, West Bengal, Gujarat, and Maharashtra have seen reduced fatalities in recent years. This improvement is attributed to better coordination between IMD forecasts, disaster management authorities, and local administrations, leading to faster evacuations and preparedness measures.

IMD’s cyclone forecasting system now relies on a combination of state-of-the-art numerical weather prediction models, multi-model ensemble techniques, advanced data assimilation, and continuous monitoring through satellites, Doppler Weather Radars, ocean buoys, and coastal observation networks. These inputs are integrated using an in-house Decision Support System to generate precise forecasts and warnings tailored for disaster managers.

To further strengthen forecasting and early-warning capabilities, the Government of India launched Mission Mausam in early 2025. The mission aims to modernise the national weather observation and forecasting infrastructure by expanding the network of weather stations, upgrading radar systems, and incorporating machine-learning tools and modern forecasting models. These efforts are supported by high-performance computing systems and intelligent decision-support platforms to enhance forecast accuracy and speed.

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Together, the data indicate that improvements in cyclone forecasting accuracy are not merely technical achievements but have had a direct, life-saving impact. As forecasting systems continue to evolve under Mission Mausam, India’s capacity to manage cyclone risks is expected to strengthen further, reducing vulnerability along its extensive coastline.