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MASTR Real-Time Sea Experiment 2024

Gulf of Mexico – February–April 2024

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 Project Main Page

The MASTR collaborative sea experiment occurs in the Gulf of Mexico from February to April 2024. 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 MASTR team members for their input and collaboration, namely Steve DiMarco, Andrew Dancer, Xiao Ge, Anthony Knap, Yun Liu, Sakib Mahmud, and Uchenna Chizaram Nwankwo (TAMU); Scott Glenn, Travis Miles, David Aragon, Kaycee Coleman, and Michael Smith (Rutgers); Michael Leber, Rafael Ramos, and Jill Storie (Woods Hole Group); Grant Stuart, Joseph Marble, and Paulo Barros (Fugro); Eric Chassignet (FSU); Amy Bower (WHOI); Benjamin de la Cruz and Lynn Shay (Miami); M. J. Costa de Almeida Tenreiro and Enric Pallas Sanz (CICESE); Doug Wilson (UVI); Jan van Smirren (Ocean Sierra); Monreal Gómez María Adela and Román Ismael Contreras Morales (UNAM); and finally Michael Feldman and Megha Khadka (NAS). 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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