AI paves the way for enhanced predictions of extreme weather events, WMO reports

A recent report coordinated by the World Meteorological Organization (WMO) highlights the potential of Artificial Intelligence (AI) and Machine Learning (ML) in revolutionizing weather forecasting. Unlike the traditional numerical weather prediction system, AI and ML can predict extreme weather events with greater accuracy.

The WMO report, titled “United in Science: Reboot Climate Action,” indicates that AI/ML models are beginning to outperform physics-based models in predicting weather variables and hazardous events, such as tropical cyclones. Notably, these models can forecast the El Niño Southern Oscillation (ENSO) up to three years in advance.

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These findings come at a critical time, as scientific projections show increased warming trends for the next five years, which are expected to disrupt weather patterns globally, including in India. The report states that, under current policies, global temperatures could rise by up to 3°C over pre-industrial levels. Only in the most optimistic scenarios, where all net-zero pledges are met, is there a chance to limit global warming to 2°C.

Machine Learning is a subset of AI that uses algorithms to process data, enabling predictions based on vast datasets. Experts believe that improving the interpretation of available observational data will be crucial in addressing recent gaps in weather forecasting.

However, challenges remain. Issues such as data availability, model resolution, and ethical considerations like transparency and equitable access must be addressed. The WMO emphasizes that AI/ML models trained on observational datasets can make weather forecasting faster and more cost-effective compared to traditional methods.

The Union Cabinet recently approved “Mission Mausam,” aimed at enhancing the accuracy of forecasts through AI and ML. M. Ravichandran, Secretary of the Ministry of Earth Sciences, noted that human intelligence will still be necessary for the final interpretation of weather data. The mission seeks to improve localized warnings and increase the frequency of nowcast warnings from every six hours to every hour.

As part of this initiative, the ministry plans to install 100 radars across India, in addition to other equipment, to bolster weather observation capabilities. M. Rajeevan, former Secretary of the Ministry of Earth Sciences, cautioned forecasters against relying solely on raw model outputs, as they may contain systematic biases. AI and ML methods could enhance the interpretation of these outputs, leading to better forecasting decisions.

With these advancements, the future of weather forecasting could be more precise and responsive, aiding preparedness for extreme weather events.

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