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GRand Adaptive Sampling Experiment 2025

Gulf of Mexico – April–September 2025

P.F.J. Lermusiaux, P.J. Haley,
C. Mirabito, E. Mule
Massachusetts Institute of Technology
Center for Ocean Engineering
Mechanical Engineering
Cambridge, Massachusetts

MSEAS Deterministic Ocean Forecasts
MSEAS Probabilistic Ocean Forecasts
MSEAS Methods & Systems
Atmos. Forecasts

Data sources
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This research is sponsored by the The National Academies of Sciences, Engineering, and Medicine.

GOFFISH MASTR Sea Exercise Page
GOFFISH Project Main Page

The GRand Adaptive Sampling Experiment (GRASE) is a collaborative sea experiment that occurs in the Gulf of Mexico from April to September 2025. We employ our MIT-MSEAS data-assimilative Primitive-Equation (PE) submesoscale-to-regional-scale ocean-modeling system for real-time deterministic and probability forecasts of ocean fields and derived quantities. Specific objectives include (i) multi-resolution ensemble forecasts with initial conditions downscaled from multiple models and implicit 2-way nesting, (ii) mutual information forecasts for predictability studies, (iii) optimal adaptive sampling guidance for air and sea sensing platforms, and (iv) reachability forecasts for underwater vehicles. Finally, we provide varied data sets that we process. We thank all of the GRASE team members for their input and collaboration. We also thank the HYCOM Consortium and Mercator Ocean for their ocean model fields, and NCEP for their atmospheric forcing data. Finally, we thank our MSEAS group members, and Yoland Gao and Wael Hajj Ali for help with the 2DSeaVizKit software.


Real-time MSEAS Forecasting

Deterministic Probabilistic

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Data sources

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