FY2024 Coastal and Ocean Modeling Testbed Project

Closed Posted

Opportunity number
NOAA-NOS-IOOS-2024-2008197
Agency
Applications due
Award size
$100,000 to $300,000

Opportunity facts

Assistance listings
Funding instrument
Cooperative Agreement
Categories
  • Environment
  • Natural Resources
Eligible applicants
  • Other

Opportunity details come from Grants.gov. Updated .

About this opportunity

The NOAA National Ocean Service and U.S. Integrated Ocean Observing System program seek proposals for the Fiscal Year 2024 Coastal and Ocean Modeling Testbed Project. Eligible applicants include institutions of higher education, nonprofits, for-profit organizations, and state/local governments to advance coastal and ocean modeling, prediction tools, and forecast products toward operational use through a modeling testbed environment. Full proposals are due February 26, 2024 and will be evaluated based on technical merit, qualifications, and outreach with anticipated start dates between September 1, 2024 to October 1, 2024.

Awards will be made to multiple recipients in amounts up to $300,000 per year, not to exceed $1.5 million total annually, for project periods of up to five years. The work supported under these awards will take place across various ocean and coastal regions of the United States as the funding aims to transition advanced modeling innovation projects to operational use in multiple locations.

Synopsis

The overarching purpose of the U.S. Integrated Ocean Observing System (IOOS®) is to address regional and national needs for ocean information, to gather reliable data on key coastal, ocean, and Great Lakes variables, and to ensure timely and sustained dissemination

and availability of these data. IOOS is a national, regional and private-sector partnership working to enhance the nation's ability to collect, disseminate, and use ocean information. U.S. IOOS is designed to address regional and national needs for ocean information, to gather specific data on key coastal, ocean, and Great Lakes variables, and to ensure timely and sustained dissemination and availability of these data to support national defense, marine commerce, navigation safety, weather, climate, and marine forecasting, energy siting and production, economic development, ecosystem-based marine, coastal, and Great Lakes resource management, public safety, and public outreach training and education.

The IOOS Coastal and Ocean Modeling Testbed (COMT) is an ongoing, multi-year effort to transition prototype ocean, coastal, and Great Lakes models, modeling tools and techniques, products, and data management advances to operations using a process that includes stakeholder engagement from industry, government, academia, and others invested in the modeling and prediction of the nation's ocean and coastal regions. IOOS, along with the other seven program offices within the National Ocean Service (NOS), has recently published a NOS Modeling Strategy (https://aambpublicoceanservice.blob.core.windows.net/oceanserviceprod/tools/coastalpredictions/ NOS-Modeling-Strategy-2023.pdf) that describes a holistic, interdisciplinary, and community built modeling portfolio to deliver the applications and services needed to reduce risks to life and property, enhance the economy, and promote social well-being in concert with our ocean, coastal, and Great Lakes environments. The COMT program aims to bring this vision to fruition through co-development of operational models. Operational mode is defined as the actual application of the technology in its final form and under

mission requirements. Within this context, the U.S. IOOS Program is managing a competitive research and development project in which the IOOS Program funds advanced ocean, coastal, and Great Lakes modeling, prediction innovation projects designed to enable evaluation and transition of these models, modeling tools and techniques to operations mode. This funding will support modeling and prediction transitions in regions across the United States.

Files

File Type Posted
NOAA-NOS-IOOS-2024-2008197 NOFO Report.pdf PDF

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