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
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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 |
- MSEAS Deterministic Ocean Forecasts
Real-Time Estimates of Present (XX Apr 0000Z) Environmental Conditions (initialized from downscaled Mercator) Gulf Modeling Domain Sections Locations Overlaid on Bathymetrry Interactive Ocean Physics Forecast 2m Vorticity 0m Sigma-T 0m Sigma-T Unc. Sec. X Temperature Sec. X Temp. Unc. Sec. X Salinity Sec. X Salinity Unc. Nowcast and Forecast Products
with descriptive dynamics
[Product details]Analyses and Forecasts Issued On April Ocean Physics Horizontal Maps Central Forecast Interactive Forecast Vertical Sections Central Forecast
MSEAS tidally-forced forecasts initialized from downscaled MercatorNowcast and Forecast Products
with descriptive dynamics
[Product details]Analyses and Forecasts Issued On April Ocean Physics Horizontal Maps Central Forecast Interactive Forecast Vertical Sections Central Forecast - MSEAS Probabilistic Ocean Forecasts: Physics-balanced stochastic models and ESSE dominant subspace decompositions are used to represent the dominant uncertainties in the initial and boundary conditions for T, S, u, v, w, and η fields for the HYCOM and Mercator modeling system fields, in the MSEAS model parameters, in the atmospheric surface forcing flux fields, and in the tidal forcing parameters.
- Glider Planning:
Product April 0-1000m Avg. Vel. Reachability Analysis Reachable sets and reachability front
Reachability Prob. - Methods and Systems: The probabilistic MIT-MSEAS Primitive Equation (PE) ocean modeling system is utilized in real time to provide ocean forecasts in the region. The modeling system was set up in an implicit 2-way nesting configuration (1/X° resolution Gulf domain and 1/X° resolution process domains). The ocean forecasts are initialized from HYCOM or Mercator, downscaled to higher resolution and updated with ocean data from varied open sources of opportunity (ARGO floats, gliders, SST, etc.). Ensemble forecasts are initialized using ESSE procedures. These ocean simulations are forced by atmospheric flux fields forecast by the Global Forecast System (GFS) 0.25° or the North American 12km Model (NAM) from the National Centers for Environmental Prediction (NCEP) and by tidal forcing from TPXO-10, but adapted to the bathymetry and coastlines. For ESSE probabilistic forecasts, initial conditions, model parameters, boundary conditions, atmospheric forcing and tidal forcing amplitudes and phases, are all perturbed according to their respective uncertainties.
- MIT-MSEAS PE Forecast skill: MSEAS forecasts compared with observed data
Forecast
Issue DateMSEAS Fct.
downscaled from X (MSEAS-X)Data dates Apr XX MSEAS-HYCOM MSEAS-Mercator MSEAS Probabilistic Fcts - MSEAS-Processed Data
- Summary of all available data of opportunity:
- Summary by type: March 20 to present
- Locations with time: March 20 to present
- Data of opportunity:
- Argo profiles: March 20 to present
- Gliders (Source: IOOS Glider DAC): March 20 to present
- NDBC Buoys: March 20 to present
- SST: MetOffice/CMEMS OSTIA Analysis (daily 0.05°): March 20 to present
- SSH (March 20 to present):
- AVISO (DUACS-processed NRT multi-satellite; Source: CMEMS):
- SWOT Swath ADT (Source: PO.DAAC): March 20 to present (2km; daily)
- SSC: Multi-sensor DINEOF global gap-filled Chl-a (March 20 to present; 9km; daily)
- Summary of all available data of opportunity:
- MSEAS-processed atmospheric forcing flux forecasts:
Merged NCEP NAM 12km and GFS 0.25°: April 2025 Daily average wind stress, E-P, heat flux, and SW Radiation (from 0Z forecast each day) Flux snapshot plots
(1 fct issued daily)1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 - Woods Hole Group Mapper
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Data sources
- Initialization and BCs
- Ocean synoptic
- ARGO float data access
- Gliders:
- National Data Buoy Center station selection
- SST Imagery/Data: Global Ocean OSTIA Sea Surface Temperature and Sea Ice Analysis (CMEMS)
- SSH Imagery/Data:
- SSC Imagery/Data: NOAA CoastWatch DinEOF3 9km gridded product
- HF Radar:
- Ocean historical/climatological
- Data sets and products NOAA National Centers for Environmental Information
- World Ocean Database (WOD)
- Data sets and products NOAA National Centers for Environmental Information
- Atmospheric forcing
- Weather Research and Forecasting (WRF) Model Real-Time Forecasts
- National Centers for Environmental Prediction (NCEP) products:
- Global Forecast System Model: version 4 (GFS), at 0.5 degree resolution (GFSp5) and also at 0.25 degree resolution (GFSp25)
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