Primary Convener:
Mingyue Tang, University of Hawai'i at Mānoa

Convener:
Sandro Lubis, Pacific Northwest National Laboratory
Jing-Jia Luo, NUIST Nanjing University of Information Science and Technology
X. Li, CAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences and Center for Ocean Mega-Science, Chinese Academy of Sciences
Mingting Li, Sun Yat-sen University
Yoo-Geun Ham, Seoul National University
Swadhin K. Behera, JAMSTEC
Ning Zhao, JAMESTEC

Early Career Convener:
Mingyue Tang, University of Hawai'i at Mānoa

Chair:
Mingyue Tang, University of Hawai'i at Mānoa
Sandro Lubis, Pacific Northwest National Laboratory
Jing-Jia Luo, Bureau of Meteorology
X. Li, CAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences and Center for Ocean Mega-Science, Chinese Academy of Sciences
Marybeth Arcodia, Colorado State University

The Indo-Pacific region is a nexus of atmospheric and oceanic processes generated and maintained on multiple spatial and temporal scales, and it also serves as a conduit for interocean exchanges of heat and salt, spreading a significant global impact. This session aims to foster interdisciplinary discussions and advance our ability to understand and predict the variations in the Indo-Pacific and other areas by connecting traditional sciences with the innovative power of machine learning. We invite contributions on (but not limited to): 1) Understanding of atmosphere-ocean processes using observations, numerical modeling, and data-driven approaches; 2) Predictions at different timescales from weather forecast, subseasonal to seasonal climate, and future projections; 3) Data qualification, reconstruction and assimilation for multiple sources of data provided by different monitoring platforms; 4) Monitoring, detection, classification, and segmentation of environmental disasters; 5) Dynamical model bias traceback, correcting and downscaling; 6) Explainable AI and 'physics + AI' hybrid modelling.

Index Terms
3314 Convective processes
3315 Data assimilation
3373 Tropical dynamics
4504 Air|sea interactions

Suggested Itineraries:
Disasters‚ Calamities and Extreme Events
Machine Learning and AI

Cross-Listed:
NH - Natural Hazards
OS - Ocean Sciences

Co-Organized Sessions:
Natural Hazards

Neighborhoods:
3. Earth Covering
1. Science Nexus