2026年5月27日(水) 17:15 〜 19:00
ポスター会場 (幕張メッセ国際展示場 7・8ホール)
Recent advances in machine learning, particularly deep learning, have enabled transformative applications across diverse fields, including weather, climate, oceanography, hydrology, and disease prediction. Increasingly, these techniques are being employed to forecast high-impact extreme events such as malaria outbreaks, heatwaves, cold spells, floods, droughts, tropical cyclones, typhoons, and large-scale climate phenomena like El Nino and the Indian Ocean Dipole. Beyond prediction, machine learning is proving valuable in improving parameterization schemes within numerical models, reducing systematic biases, and enhancing horizontal resolution in forecasts. This session aims to bring together researchers advancing machine learning methodologies to improve prediction and understanding of weather, climate, oceans, hydrology, and tropical diseases. Discussions will emphasize both scientific progress and practical applications that support societal resilience, well-being, and informed decision-making.
