Observing the Ocean,
Predicting the Future
Combining physics and AI models with observations and data analysis to understand the complexities of the ocean and its interaction with the atmosphere.
- Feb 2025 Conference OceanAI and OceanNet were presented at the AMS Annual Meeting 2025, New Orleans.
- Dec 2024 Conference OceanAI and OceanNet were presented at AGU Fall Meeting 2024, Washington D.C.
Pioneering Excellence in Marine Science
The Ocean Observing and Modeling Group (OOMG) conducts innovative marine research in the Department of Marine, Earth & Atmospheric Sciences at North Carolina State University.
We focus on advancing oceanographic science through integrated ocean observations, remote sensing data analysis, data-assimilative numerical modeling, and the application of artificial intelligence and machine learning to gain an integrated understanding of ocean–atmosphere interactions and of physical, biological, geological, and chemical marine processes.
Coastal Circulation Dynamics
Western boundary currents, especially the Gulf Stream. Shelf–open ocean exchange. Sea level rise.
Numerical Modeling & Data Assimilation
Physics-based and AI models filling gaps in observational data. Predictive modeling forecasts and hindcasts.
Marine Physical-Biogeochemical Interactions
Implications of ocean circulation on the food chain and fisheries. Temperature, salinity, and chemistry.
Air–Sea Interactions
Hurricanes' effects on ocean dynamics. Gas flux at the ocean surface.
Satellite Oceanography
Remote sensing observations of the ocean surface. Detection of chlorophyll and debris.
Coastal Ocean Observing Systems
In situ data collection including the Pioneer Array. Autonomous underwater vehicles (AUVs). Ship-board instruments.
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2025
Gulf Stream near Cape Hatteras modulates sea level variability along the southeastern coast of North America
Geophysical Research Letters — Wu & He -
2025
Long-term prediction of the Gulf Stream meander using OceanNet: A neural operator-based digital twin
Ocean Sciences — Gray, Chattopadhyay, Wu, Lowe & He -
2024
Gulf Stream mesoscale variabilities drive bottom marine heatwaves in northwest Atlantic continental margin methane seeps
Nature Communications Earth & Environment — Wu & He -
2024
OceanNet: A principled neural operator-based digital twin for regional oceans
Scientific Reports — Chattopadhyay, Gray, Wu, Lowe & He -
2024
Forecasting ocean waves off the U.S. East Coast using an ensemble learning approach
AI for the Earth Systems — Chaichitehrani & He
- Caribbean Through-flow Water Mass Transformation Processes National Science Foundation · 2025–2028
- EcoTern: CI Workforce for Sustainable Environmental Science Research National Science Foundation · 2024–2027
- PARTNER: AI/ML Collaborative for SE Florida Coastal Environmental Data National Science Foundation · 2023–2027
- Advancing Gulf of Mexico Operational Forecasting (GOFFISH) National Academies of Science · 2022–2027
- NSF AI Institute for Trustworthy AI in Weather, Climate & Coastal Oceanography (AI2ES) National Science Foundation · 2020–2025
Products
An AI-powered ocean data platform built on OceanNet. Visualize sea surface height, ocean currents, and current speed across the Gulf of Mexico with animated time controls and satellite imagery.
The OOMG Ocean Prediction Dashboard delivers daily 120-day ensemble forecasts. Select OceanNet or CNAPS2, choose a date, and explore sea surface height and velocity fields with uncertainty quantification for the Gulf of Mexico.
Prospective Students & Collaborators
We welcome graduate students, postdoctoral researchers, and collaborators with interests in physical oceanography, AI/ML for earth systems, coastal modeling, and marine observing technologies. Prospective graduate students should apply through the NC State MEAS department. For inquiries, contact Dr. He at rhe [at] ncsu [dot] edu.