“AI is not magic; it’s just another tool, its power lies in how wisely we use it.” - Fei-Fei Li, AI researcher and professor at Stanford University
Cautious optimism from the meteorological community
The India Meteorological Department (IMD) has begun experimenting with artificial intelligence (AI) models in weather prediction. Early pilot projects show encouraging results, but IMD remains cautious about their precision, especially in forecasting the intensity of storms and rainfall.
Ongoing collaboration and pilot initiatives
Under the Ministry of Earth Sciences, a panel of experts from IMD and other national institutions is exploring AI-driven forecast models. These teams are using tools like ChatGPT-like communication systems and translation-enabled forecasting apps to improve multilingual accessibility of weather information.
Global perspective on AI limitations
According to IMD Director-General, even globally, AI has not replaced traditional physics-based weather models. Countries such as China and members of the European Centre for Medium-Range Weather Forecasts (ECMWF) continue to use AI only for smaller, supportive tasks like heat index analysis and cyclone tracking.
Accuracy challenges and future readiness
AI forecasting systems sometimes fail to match the reliability of established numerical models. For example, during the prediction of tropical cyclone Mocha, IMD relied on multiple models rather than one AI-based system. The results highlighted both the potential and current limitations of AI-driven methods.
The road ahead for AI in forecasting
IMD plans to continue research while validating AI outcomes against proven models. Experts agree that AI can assist but not yet replace core forecasting systems. Its role remains supplementary until models become robust enough for full-scale adoption.
Summary
AI in weather forecasting shows promise but remains in its infancy. India’s IMD and global agencies are exploring its applications while emphasizing that traditional physical models still form the foundation of reliable forecasting.
Food for thought
If AI can beat humans at chess, why does it still struggle to predict tomorrow’s rain?
AI concept to learn: AI models in forecasting
AI forecasting models use machine learning to identify patterns in vast weather datasets. They learn from historical trends to predict future outcomes, complementing traditional numerical models that rely on physical and mathematical equations.
[The Billion Hopes Research Team shares the latest AI updates for learning and awareness. Various sources are used. All copyrights acknowledged. This is not a professional, financial, personal or medical advice. Please consult domain experts before making decisions. Feedback welcome!]
COMMENTS