Multidisciplinary and Interdisciplinary (M)
Session Sub-categoryGeneral Geosciences, Information Geosciences & Simulations (GI)
Session IDM-GI27
Session Title Data-driven approaches for weather and hydrological predictions
Short Title Data driven study in weather prediction
Date & Time Oral
Session
AM1-AM2 Thu, 29 MAY
On-site Poster
Coretime
PM3 Thu. 29 MAY
Main Convener Name Shunji Kotsuki
Affiliation Center for Environmental Remote Sensing, Chiba University
Co-Convener 1 Name Daisuke Hotta
Affiliation Meteorological Research Institute
Co-Convener 2 Name Yuki Yasuda
Affiliation Tokyo Institute of Technology
Co-Convener 3 Name Thomas Sekiyama
Affiliation Meteorological Research Institute
Session Language E
Scope (Session Description) 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.
Session Format Orals and Posters session
Co-sponsorship Partner Union(s) -
JpGU Society Member(s) Meteorological Society of Japan, Japan Society of Hydrology & Water Resources
International Collaborative Society -
Organizations Other Than JpGU Society Members -