There is an increasing need of advanced systems to manage and mitigate the impacts of frequent and severe climate events, such as monsoons and cyclones
Artificial Intelligence, big data and machine learning are some of the structures through which India is developing for improved capacity of weather forecasting in the future. It aims at making weather forecasting more accurate for extreme weather events such as floods and droughts. This will be led at the front by the Indian Meteorological Department (IMD), which is testing AI-driven models promising more precise predictions as a cost-effective solutions option. These developments are especially critical in the context of India's massive population and its position as a significant agricultural producer.

India is also adding its computing dependence on the latest in supercomputers that can deliver high performance-necessary for modern weather forecasting- in carrying out complex calculations. It is one such example-the AI supercomputer 'AIRAWAT' at Pune, which assists in imparting detail in accurate weather forecasting for all regions of the country.??
A memorandum of understanding (MoU) to improve the technical capacities of the National Meteorological Office (Onamet) was signed in June 2024 between the Dominican Republic and India. The MoU includes personnel training, sharing early warning system expertise, and using satellite data to improve weather forecasts. Through programs like "Mission Mausam," which entails contracts for cutting-edge technology and infrastructure upgrades to improve the accuracy and reach of weather forecasts, India has been actively developing and upgrading its weather forecasting systems in 2023. These projects are primarily managed by the India Meteorological Department (IMD) and the National Centre for Medium Range Weather Forecasting (NCMRWF), which is under the Ministry of Earth Sciences. These projects include providing real-time extended range predictions for a variety of sectors, including agriculture, aviation, and disaster relief.
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