2023年5月22日(月) 13:45 〜 15:00 展示場特設会場 (4) (幕張メッセ国際展示場)

コンビーナ:Jayanthi Venkata Ratnam(Application Laboratory, JAMSTEC)、Patrick Martineau(Japan Agency for Marine-Earth Science and Technology)、土井 威志(JAMSTEC)、Behera Swadhin(Climate Variation Predictability and Applicability Research Group, Application Laboratory, JAMSTEC, 3173-25 Showa-machi, Yokohama 236-0001)、Chairperson:Patrick Martineau(Japan Agency for Marine-Earth Science and Technology)、土井 威志(JAMSTEC)、Jayanthi Venkata Ratnam(Application Laboratory, JAMSTEC)

Machine learning techniques have found a wide range of applications in weather, climate, ocean, hydrology, and disease predictions. In 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. The aim of this session is to bring together researchers working on various techniques of machine learning to enhance the understanding and skill of weather, climate, ocean, hydrology and disease predictions for the benefit of the society.