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Home Marathi news AI-powered monsoon forecast system developed at Pune’s IITM promises farmers four-week heads-up

AI-powered monsoon forecast system developed at Pune’s IITM promises farmers four-week heads-up

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AI-powered monsoon forecast system developed at Pune’s IITM promises farmers four-week heads-up


Pune: The IITM, in collaboration with the IMD among others, has developed an artificial intelligence-powered forecast system that can predict the onset of monsoon at the local-level up to four weeks in advance.The Local Monsoon Onset Forecasting System — launched recently — has been designed as a probabilistic forecast platform. It combines artificial intelligence, weather prediction models and statistical techniques to provide location-specific guidance for farmers. The system can change how farmers prepare for the monsoon season.The initiative has been developed jointly by institutions under the ministry of earth sciences (MoES), including the India Meteorological Department (IMD), Pune-based Indian Institute of Tropical Meteorology (IITM) and the scientific team from Human-Centered Weather Forecasts Initiative (HCWF). Scientists said the system was intended to address one of the most critical decisions in agriculture — when the monsoon is likely to arrive in a particular area.A delay or early arrival of monsoon often affects sowing, irrigation scheduling and crop management practices. Existing seasonal forecasts provide broader outlooks, but the new framework aims to generate more localised and probabilistic information for agricultural planning.The forecasting platform uses a blended approach that combines three distinct systems rather than relying on a single prediction model. One of these is the Artificial Intelligence Forecasting System (AIFS), an open-access AI weather prediction system developed by the European Centre for Medium-Range Weather Forecasts (ECMWF) and operated at the IITM. It also uses the IITM-Extended Range Prediction model, operated jointly by the IITM and the IMD, along with the Evolving Expectation Model developed by the HCWF team.



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