Japan Geoscience Union Meeting 2025

Session information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-TT Technology &Techniques

[A-TT35] Machine Learning Techniques in Weather, Climate, Ocean, Hydrology and Disease Predictions

Fri. May 30, 2025 1:45 PM - 3:15 PM Exhibition Hall Special Setting (2) (Exhibition Hall 7&8, Makuhari Messe)

convener:Venkata Ratnam Jayanthi(Application Laboratory, JAMSTEC), Patrick Martineau(Japan Agency for Marine-Earth Science and Technology), Takeshi Doi(JAMSTEC), Swadhin Behera(Application Laboratory, JAMSTEC, 3173-25 Showa-machi, Yokohama 236-0001), Chairperson:Venkata Ratnam Jayanthi(Application Laboratory, JAMSTEC), Patrick Martineau(Japan Agency for Marine-Earth Science and Technology)

Advances in the machine learning techniques such as deep learning have led to an increase in the application of the techniques to a wide range of topics such as weather, climate, ocean, hydrology, and disease predictions. In the recent times, these techniques are being increasingly used to predict extreme events such as malaria outbreaks, heat waves, cold spells, flooding, droughts, tropical cyclones, typhoons, El Nino/Indian Ocean Dipole events among many others. In addition, machine-learning techniques are helping researchers to improve parameterization schemes in numerical prediction models. Machine-learning is also being used to improve numerical model predictions by providing methods to reduce biases and improve the horizontal resolution of the predictions. This session aims to bring together the researchers working on various machine learning techniques to discuss and enhance our understanding of weather, climate, Ocean, hydrology and tropical diseases as well as their predictions and applications for societal benefits and well-being.

2:30 PM - 2:45 PM

*Linna ZHAO1, Linna ZHAO2, Shu LU3, Dan QI4 (1.Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, 2.Union Centre for Extreme Weather, Climate and Hydrogeological Hazards, China Meteorological Administration-China University of Geosciences, Wuhan 430074, 3.Hunan Meteorological Observatory, Changsha 410118, 4.National Meteorological Center, Beijing 100081)

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