2026年5月25日(月) 10:45 〜 12:15 106 (幕張メッセ国際会議場)

座長:澤田 洋平(東京大学)、小槻 峻司(千葉大学　環境リモートセンシング研究センター)

In the digital era, data-driven techniques are transforming our understanding and prediction capabilities of complex earth systems. This session aims to explore the cutting-edge methodological and applicational studies for weather, climate and hydrological predictions. Key themes includes: (1) methodological studies to deepen data-driven approaches for geoscience problems, (2) machine/deep learning studies applied for extreme weather-related disasters, (3) climate predictive analysis to discern climate variability, trends, and anomalies, (4) integrating remote sensing and ground data to refine prediction models. This session aims to foster a rich dialogue among experts, highlighting both the advancements and challenges in data-driven environmental modeling. Participants will gain insights into current best practices and envision the future trajectory of this rapidly evolving domain.