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Core Model Evaluation for Physical Oceanography Applications
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The National Oceanic and Atmospheric Administration’s National Ocean Service is conducting market research to evaluate and identify an optimal set of open-source, community-supported physical oceanography model codes that can effectively support its mission across safe navigation, coastal resilience, and other critical applications. Current operations rely on multiple core models—including ROMS, FVCOM, ADCIRC, and SCHISM—each supporting distinct regional forecast systems, but this diversity strains resources in terms of staffing, funding, high-performance computing allocation, and software maintenance. The goal is to consolidate capabilities by selecting models that not only meet current operational needs but also enable future advancements in computing infrastructure, such as HPC, cloud systems, and GPU architectures, while integrating seamlessly with NOAA’s Unified Forecast System and incorporating emerging non-physics-based methodologies like artificial intelligence and machine learning. The evaluation will assess both existing core models and innovative approaches, including hybrid physics-AI systems and other emerging solutions from academia and industry, using a combination of quantitative and qualitative criteria. The scope is specifically focused on physical oceanography models and excludes non-core or non-physical approaches unless they offer transformative integration potential. Participants are invited to provide information through a linked Google Form by the August 14, 2026 deadline, with submissions helping shape future procurement and development decisions. The effort is led by the Office of Ocean Services and Coastal Zone Management based in Norfolk, Virginia, with primary points of contact available for questions regarding modeling requirements and submission guidelines.
General Info
Agency
NAICS
Place of Performance
VA, USASet-Aside
Timeline
Submission Closed
Organization & Contact Information
Full Description
On behalf of the Department of Commerce’s National Oceanic and Atmospheric Administration, the National Ocean Service (NOS) is conducting market research to understand capabilities related to open-source, community-supported oceanographic models and their current and planned future capabilities. This information may be used to support an evaluation to determine an optimal set of physical core model codes and approaches that can meet the NOAA mission; this will help position NOS to incorporate advances in computing infrastructure, data integration, and non-physics-based prediction methodologies over the coming decade.
NOS currently maintains several physical oceanography applications based on a variety of community-supported core models developed and supported by the external modeling community. As examples, the Chesapeake Bay Operational Forecast System (CBOFS) was built using the core model called the Regional Ocean Modeling System (ROMS), the Salish Sea and Columbia River Operational Forecast System (SSCOFS) uses the core model called the Finite Volume Community Ocean Model (FVCOM), and the Surge and Tide Operational Forecast System (STOFS-2D-Global and STOFS-3D-Atlantic) application runs on the Advanced Circulation Model (ADCIRC) and Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM) core models. While this diversity allows for supporting the entire NOS mission, it also dilutes resources as multiple software packages need to be supported. This resource dilution impacts human capital, appropriation of funds, High-Performance Computing (HPC) allocations, and software maintenance efficiencies.
The scope of this effort centers on an evaluation of physical oceanography models. There is a critical need for NOS to evaluate and select an optimal set of core community model codes that can:
- Holistically meet NOS mission and/or modeling requirements (e.g., safe navigation, coastal resilience, etc.),
- Position NOS to better incorporate advances in computing infrastructure (e.g., HPC, cloud, graphics processing unit (GPU) architecture, etc.),
- Leverage non-physics-based prediction methodologies like AI/ML, and
- Integrate seamlessly with NOAA’s UFS.
This evaluation will be based on both quantitative and qualitative criteria and will, at a minimum, target the underlying core codes currently used across NOS (i.e., ADCIRC, SCHISM, FVCOM, ROMS), as well as novel AI/ML architectures, hybrid physics-AI systems and other approaches or emerging models supported by academia and private industry that have the potential to meet NOS modeling requirements (see Attachment A).
Please see the attached Request for Information and Attachment A - NOS Modeling Requirements. If interested, please complete the linked Google Form (https://forms.gle/eZJSqg9zMdii4cxE7).
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