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Find similar grantsFY2024 Coastal and Ocean Modeling Testbed Project is sponsored by NOAA National Ocean Service (NOS) U.S. Integrated Ocean Observing System (IOOS). This opportunity supports mission-aligned projects and measurable outcomes.
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Coastal and Ocean Modeling Testbed - The U.S. Integrated Ocean Observing System (IOOS) System status NORMAL. To check individual assets and information, visit ioos. us and/or the Environmental Sensor Map .
Coastal and Ocean Modeling Testbed Coastal and Ocean Modeling Testbed About Coastal and Ocean Modeling Testbed Coastal waters and lowlands of the U.S. are threatened by sea-level rise, flooding, oxygen depleted “dead zones," oil spills, and unforeseen disasters.
With funding from the IOOS Program Office, strong and strategic collaborations among experts from academia, federal operational centers and industry are forged to create the U.S. IOOS Coastal and Ocean Modeling Testbed (COMT). The COMT serves as a conduit between the federal operational and research communities and allows sharing of numerical models, observations and software tools.
The COMT supports integration, comparison, scientific analyses and archiving of data and model output needed to elucidate, prioritize, and resolve federal and regional operational coastal ocean issues associated with a range of existing and emerging coastal oceanic, hydrologic, and ecological models.
The Testbed has enabled significant community building (within the modeling community as well as enhancing academic and federal operational relations) which has dramatically improved model development.
COMT projects are designed to assess the performance of existing models, create new model code and tools, inform and train users, and build a repository of evaluation data sets to expand and improve the modeling capabilities of operational partners and the broader coastal and ocean modeling community.
A crucial component of COMT is cyberinfrastructure, which includes hosting a data server, tools and toolkits to facilitate access to data, models, model input files, and model results (i.e. the IOOS Model Viewer ), coordination with NOS development and skill assessment for models transitioning to operations, the IOOS compliance checker , and access to high performance computing resources such as the NOS Coastal Modeling Cloud Sandbox .
For the most up to date information on current projects, please see comt. ioos. us .
Chesapeake Bay Environmental Forecasting System LiveOcean Model Enhancement Multi-Physics Water Level Modeling From Global to Meter Scales Data Assimilation Algorithms for U.
S West and East Coast OFS Coupled Ocean Modeling Testbed Platform Coastal Waves, Surge and Inundation in the Gulf of Maine Coastal Waves, Surge and Inundation in the Gulf of Mexico Coupling the National Water Model to the Coastal Ocean Northeast Coastal Ocean Forecast System (NECOFS) A Unified Framework for IOOS Model Data Access Advancing the West Coast Ocean Forecasting System Operational Forecast System for the Salish Sea US West Coast Model Intercomparison Project Puerto Rico/ U.S. Virgin Islands Inundation 2021 Community Modeling Workshop Booklet 2021 Community Modeling Workshop Summary White Papers and Publications Luettich et al, The U.S. IOOS Super-regional Coastal Ocean Modeling Testbed: Implementation and Overview of Findings, Journal of Geophysical Research: Oceans Special Issue, Dec, 2013 COMT Terms of Reference 120914 COMT Roundup and Progress (April 2018) COMT presentation to NOAA Testbeds and Proving Grounds Apr 2016 COMT PO presentation at COMT All Hands July 2015 COMT and EFR presentation to MEOPAR June 2015 NOAA's Testbeds and Proving Grounds NOAA's Technology Partnership Office Chen, C.
, Beardsley, R. C. , Luettich Jr, R.
A. , Westerink, J. J.
, Wang, H. , Perrie, W. , & Toulany, B.
(2013). Extratropical storm inundation testbed: Intermodel comparisons in Scituate, Massachusetts. Journal of Geophysical Research: Oceans, 118(10), 5054-5073.
Durski, S. M. , Kurapov, A.
L. , Allen, J. S.
, Kosro, P. M. , Egbert, G.
D. , Shearman, R. K.
, & Barth, J. A. (2015).
Coastal ocean variability in the US Pacific Northwest region: seasonal patterns, winter circulation, and the influence of the 2009–2010 El Niño. Ocean Dynamics, 65, 1643-1663. Fennel, K.
, Laurent, A. , Hetland, R. , Justić, D.
, Ko, D. S. , Lehrter, J.
, ... & Zhang, W. (2016).
Effects of model physics on hypoxia simulations for the northern Gulf of Mexico: A model intercomparison. Journal of Geophysical Research: Oceans, 121(8), 5731-5750. Hope, M.
E. , Westerink, J. J.
, Kennedy, A. B. , Kerr, P.
C. , Dietrich, J. C.
, Dawson, C. , ... & Westerink, L.
G. (2013). Hindcast and validation of Hurricane Ike (2008) waves, forerunner, and storm surge.
Journal of Geophysical Research: Oceans, 118(9), 4424-4460. Irby, I. D.
, Friedrichs, M. A. , Friedrichs, C.
T. , Bever, A. J.
, Hood, R. R. , Lanerolle, L.
W. , ... & Xia, M.
(2016). Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison. Biogeosciences, 13(7), 2011-2028.
Joyce, B. R. , Gonzalez‐Lopez, J.
, Van der Westhuysen, A. J. , Yang, D.
, Pringle, W. J. , Westerink, J.
J. , & Cox, A. T.
(2019). US IOOS coastal and ocean modeling testbed: Hurricane‐induced winds, waves, and surge for deep ocean, reef‐fringed islands in the Caribbean. Journal of Geophysical Research: Oceans, 124(4), 2876-2907.
Kerr, P. C. , Martyr, R.
C. , Donahue, A. S.
, Hope, M. E. , Westerink, J.
J. , Luettich Jr, R. A.
, ... & Westerink, H. J.
(2013). US IOOS coastal and ocean modeling testbed: Evaluation of tide, wave, and hurricane surge response sensitivities to mesh resolution and friction in the Gulf of Mexico. Journal of Geophysical Research: Oceans, 118(9), 4633-4661.
Kerr, P. C. , Donahue, A.
S. , Westerink, J. J.
, Luettich Jr, R. A. , Zheng, L.
Y. , Weisberg, R. H.
, … & Cox, A. T. (2013).
US IOOS coastal and ocean modeling testbed: Inter‐model evaluation of tides, waves, and hurricane surge in the Gulf of Mexico. Journal of Geophysical Research: Oceans, 118(10), 5129-5172. Kim, S.
Y. , Kurapov, A. L.
, & Kosro, P. M. (2015).
Influence of varying upper ocean stratification on coastal near‐inertial currents. Journal of Geophysical Research: Oceans, 120(12), 8504-8527. Kurapov, A.
L. , Erofeeva, S. Y.
, & Myers, E. (2017). Coastal sea level variability in the US west coast ocean forecast system (WCOFS).
Ocean Dynamics, 67, 23-36. Luettich Jr, R. A.
, Wright, L. D. , Nichols, C.
R. , Baltes, R. , Friedrichs, M.
A. , Kurapov, A. , ...
& Howlett, E. (2017). A test bed for coastal and ocean modeling.
Eos, 98. Luettich Jr, R. A.
, Wright, L. D. , Signell, R.
, Friedrichs, C. , Friedrichs, M. , Harding, J.
, ... & Baltes, R. (2013).
Introduction to special section on the US IOOS coastal and ocean modeling testbed. Journal of Geophysical Research: Oceans, 118(12), 6319-6328. Moore, A.
M. , Jacox, M. G.
, Crawford, W. J. , Laughlin, B.
, Edwards, C. A. , & Fiechter, J.
(2017). The impact of the ocean observing system on estimates of the California current circulation spanning three decades. Progress in Oceanography, 156, 41-60.
Pringle, W. J. , Gonzalez‐Lopez, J.
, Joyce, B. R. , Westerink, J.
J. , & van der Westhuysen, A. J.
(2019). Baroclinic coupling improves depth‐integrated modeling of coastal sea level variations around Puerto Rico and the US Virgin Islands. Journal of Geophysical Research: Oceans, 124(3), 2196-2217.
Scully, M. E. (2016).
The contribution of physical processes to inter‐annual variations of hypoxia in Chesapeake Bay: A 30‐yr modeling study. Limnology and Oceanography, 61(6), 2243-2260. Wiggert, J.
D. , Hood, R. R.
, & Brown, C. W. (2017).
Modeling hypoxia and its ecological consequences in Chesapeake Bay. Modeling Coastal Hypoxia: Numerical Simulations of Patterns, Controls and Effects of Dissolved Oxygen Dynamics, 119-147. Zheng, L.
, Weisberg, R. H. , Huang, Y.
, Luettich, R. A. , Westerink, J.
J. , Kerr, P. C.
, & Akli, L. (2013). Implications from the comparisons between two‐and three‐dimensional model simulations of the Hurricane Ike storm surge.
Journal of Geophysical Research: Oceans, 118(7), 3350-3369. Anderson, C. , Newton, J.
, Ruhl, H. , Garfield, T. , DeVogelaere, A.
, Moore, T. , & Edwards, C. (2019).
West Coast Ocean Forecast System (WCOFS) – Coastal Ocean Model Testbed (COMT) Stakeholder Engagement Workshop Summary Report, https://sccoos. org/wp-content/uploads/2020/12/COMTStakeholderEngagementWorkshop_REPORT. pdf Matranga, J.
(2021). Thinning algorithms for remote sensing observations in support of ocean data assimilation, M. S.
Thesis, University of California, Santa Cruz. Bunya, S. , Luettich Jr, R.
A. , & Blanton, B. O.
(2023). Techniques to embed channels in finite element shallow water equation models. Advances in Engineering Software, 185, 103516.
Chen, C. , Lin, Z. , Beardsley, R.
C. , Shyka, T. , Zhang Y.
, Xu Q. , Qi, J. , Lin, H.
, & Xu, D. (2020). Impacts of sea-level rise on future storm-induced coastal inundation over Massachusetts Coast, Natural Hazards, https://doi.
org/10. 1007/s11069-020-04467-x. Chen, C.
, Zhao, L. , Gallager, S. , Ji, R.
, He, P. , Davis, C. , Beardsley, R.
C. , Hart, D. , Gentleman, W.
C. , Wang, L. , Li, S.
, Lin, H. , Stokesbury, K. , & Bethoney, D.
(2021). Impact of larval behaviors on dispersal and connectivity of sea scallop larvae over the northeast U.S. shelf. Progress in Oceanography, 195, 102604, https://doi.
org/10. 1016/j. pocean.
2021. 102604. Grogan, D.
S. , Zuidema, S. , Prusevich, A.
, Wollheim, W. M. , & Glidden, S.
(2022). WBM: A scalable gridded global hydrologic model with water tracking functionality. Geoscientific model development discussions, 1(54).
Li, S. (2022). Development of a coupled FVCOM-WRF model: applications for Hurricane Sandy.
Ph. D. dissertation, University of Massachusetts-Dartmouth, 184pp.
Li, S. , Chen, C. , Wu, Z.
, Beardsley, R. C. , & Li, M.
(2020). Impacts of oceanic mixed layer on hurricanes: A simulation experiment with Hurricane Sandy. Journal of Geophysical Research: Oceans, 125(11), e2019JC015851.
Wang, D. (2022). Impacts of climate change on seasonal and interannual variabilities of the Beaufort gyre and freshwater content in the Arctic Ocean.
Ph. D. dissertation, University of Massachusetts-Dartmouth, 201pp.
(Note: Global-FVCOM is used to nest with NECOFS) Zhang, Z. , Chen, C. , Beardsley, R.
C. , Li, S. , Xu, Q.
, Song, Z. , Zhang, D. , Hu, D.
, & Guo, F. (2020). A FVCOM study of the potential coastal flooding in Apponagansett Bay and Clark Cove, Dartmouth Town (MA).
Natural Hazards, http://doi. org/10. 1007/s11069-020-04102-9.
Zang, Z. , R. Ji, Z.
Feng, C. Chen, S. Li, and C.
S. Davis, 2021. Spatially varying phytoplankton seasonality on the Northwest Atlantic Shelf: A model-based assessment of patterns, drivers and implications.
ICES Journal of Marine Science, fsab102, 1920-1934. Zang, Z. , Ji, R.
, Liu, Y. , Chen, C. , Li, Y.
, Li, S. , & Davis, C. S.
(2022). Remote silicate supply regulates spring phytoplankton bloom magnitude in the Gulf of Maine. Limnology and Oceanography Letters, 7(3), 277-285.
Bever, A. J. , Friedrichs, M.
A. M. , & St-Laurent, P.
(2021). Real-time environmental forecasts of the Chesapeake Bay: Model setup, improvements, and online visualization. Environmental Modelling and Software, 105036, https://doi.
org/10. 1016/j. envsoft.
2021. 105036 Horemans, D. M.
L. , Friedrichs, M. A.
M. , St-Laurent, P. , Hood, R.
R. , Brown, C. W.
(2023). Forecasting Prorocentrum minimum blooms in the Chesapeake Bay using empirical habitat models. Frontiers in Marine Science, 10, https://doi.
org/10. 3389/fmars. 2023.
1127649 Horemans, D. M. L.
, Friedrichs, M. A. M.
, St-Laurent, P. , Hood, R. R.
, & Brown, C. W. (2024).
Evaluating the skill of correlative species distribution models trained with mechanistic model output. Ecological Modeling, 491, 110692. https://doi.
org/10. 1016/j. ecolmodel.
2024. 110692 St-Laurent, P. , & Friedrichs, M.
A. M. (2024).
An atlas for physical and biogeochemical conditions in the Chesapeake Bay, SEANOE, https://doi. org/10. 17882/99441 Contreras, M.
T. , Woods, B. , Blakely, C.
, Wirasaet, D. , Westerink, J. J.
, Cobell, Z, Pringle, W. , Moghimi, S. , Myers, E.
, Seroka, G. , Lalime, M. , Funakoshi, Y.
, Van der Westhuysen, A. , Abdolala, A. , Ma, Z.
, Lui, F. , Valseth, E. , & Dawson, C.
(2023). A channel-to-basin scale ADCIRC based hydrodynamic unstructured mesh model for the US East and Gulf of Mexico Coasts, NOAA Technical Memorandum NOS CS 41, National Oceanic and Atmospheric Administration. Broatch, E.
M. , & MacCready, P. (2022).
Mixing in a Salinity Variance Budget of the Salish Sea is Controlled by River Flow. Journal of Physical Oceanography, 52(10), 2305-2323. doi:10.
1175/jpo-d-21-0227. 1. MacCready, P.
, & Geyer, W. R. (2024).
Estuarine Exchange Flow in the Salish Sea. Journal of Geophysical Research: Oceans, 129(1). doi:10.
1029/2023jc020369. MacCready, P. , McCabe, R.
M. , Siedlecki, S. A.
, Lorenz, M. , Giddings, S. N.
, Bos, J. , Albertson, S. , Banas, N.
S. , & Garnier, S. (2021).
Estuarine Circulation, Mixing, and Residence Times in the Salish Sea. Journal of Geophysical Research: Oceans, 126(2). doi:10.
1029/2020jc016738. Morzaria-Luna, H. , Kaplan, I.
C. , Harvey, C. J.
, Girardin, R. , Fulton, E. A.
, MacCready, P. , Chasco, B. , Horne, P.
, & Schmidt, M. (2022). Design and Parameterization of a Spatially Explicit Atlantis Ecosystem Model for Puget Sound.
(NMFS-NWFSC-177). Sunday, J. M.
, Howard, E. , Siedlecki, S. , Pilcher, D.
J. , Deutsch, C. , MacCready, P.
, Newton, J. , & Klinger, T. (2022).
Biological sensitivities to high-resolution climate change projections in the California current marine ecosystem. Global Change Biology, 28(19), 5726-5740. doi:10.
1111/gcb. 16317. Bao, D.
, Xue, Z. G. , Warner, J.
C. , Moulton, M. , Yin, D.
, Hegermiller, C. A. , et al.
(2022). A numerical investigation of Hurricane Florence-induced compound flooding in the Cape Fear Estuary using a dynamically coupled hydrological-ocean model. Journal of Advances in Modeling Earth Systems, 14, e2022MS003131.
https://doi. org/10. 1029/2022MS003131 Xue, Z.
Bao, D. , Yin, D, & Warner, J. (2023).
A novel dynamically coupled land-river-ocean modeling suite for hurricane-induced compound flooding. Coastal Sediments 2023: The Proceedings of the Coastal Sediments 2023. 2659-2668.
Moore, A. M. , Arango, H.
G. , Wilkin, J. , & Edwards, C.
A. (2023). Weak constraint 4D-Var data assimilation in the Regional Ocean Modeling System (ROMS) using a saddle-point algorithm: Application to the California Current Circulation.
Ocean Modelling, 186, 102262. Wilkin, J. , Levin, J.
, Moore, A. , Arango, H. , López, A.
, & Hunter, E. (2022). A data-assimilative model reanalysis of the US Mid Atlantic Bight and Gulf of Maine: Configuration and comparison to observations and global ocean models.
Progress in Oceanography, 209, 102919. OTT/COMT Kickoff Meeting (September 2021) COMT/OTT Performance Progress Report Template Post Award Grant Management: Progress Reports, Grants Online Submission U.S. Integrated Ocean Observing System indicates a link leaves the site. View our Link Disclaimer for more information.
According to the current listing, eligibility includes: Not specified, but typically includes academic institutions, non-profit organizations, state and local governments, and tribal entities. Confirm the full requirements in the official notice before applying.
FY2024 Coastal and Ocean Modeling Testbed Project is funded by NOAA National Ocean Service (NOS) U.S. Integrated Ocean Observing System (IOOS). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
Dear Colleague Letter NSF 26-024, issued August 27, 2026, asks nine questions about the future of NSF-supported ocean observing. It is the input mechanism NSF promised in June when it halted the dismantling of the $386 million Ocean Observatories Initiative. Responses are capped at 3,250 characters per question and become public.
Read articleNOAA runs a separate Broad Agency Announcement for every line office that awards financial assistance — rolling, no cost share, open to individuals and foreign organizations. The FY2024–2026 window closes 11:59:59 p.m. ET on September 30, 2026, with no published successor. Here is how standing BAAs actually work and how to use the last days of this one.
Read articleDARRP Restoration Implementation Grants close November 18, 2026, with an award range of $2.5 million to $100 million, no cost share, and funding that comes from legal settlements rather than appropriations. The eligibility exclusions are the whole design, and they tell you exactly what NOAA is buying.
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