Foa_Content_of_NOAA-OAR-CPO-2027-33392.pdf

NOTICE OF FUNDING OPPORTUNITY

NOAA NOFO Page 1 of 23

Table of Contents

NOTICE OF FUNDING OPPORTUNITY

Executive Summary Full Text of Announcement

I. Funding Opportunity Description II. Award Information III. Eligibility Information IV. Application and Submission Information V. Application Review Information VI. Award Administration Information VII. Agency Contacts VIII. Other Information

Executive Summary Federal Agency Name OAR Climate Program Office (CPO)

Funding Opportunity Title Climate Program Office FY 2027 - Super Intelligence/Machine Learning Innovation to Advance NOAA's Earth System Science and Support Hazard Resilience

Announcement Type Competitive

Funding Opportunity Number

NOAA-OAR-CPO-2027-33392

Assistance Listing Number(s) 11.431

Dates Dates: Letters of intent (LOIs) should be received by email by 11:59 p.m. Pacific Time on November 17, 2026.

Full Applications: Full applications must be received by 11:59 p.m. Pacific Time, on February 9, 2027.

IMPORTANT NOTE: Applicants will need an eRA Commons Account PRIOR to full application submission.

It is recommended to start the process of registering for an eRA Commons Account at least six weeks before the application deadline to allow ample time for registration.

Funding Opportunity Description Through this Notice of Federal Funding Opportunity, the NOAA Climate Program Office (https://cpo.noaa.gov/funding-opportunities/) is soliciting proposals for a FY 2027 grants competition focused on Super Intelligence/Machine Learning Innovation to Advance NOAA's Earth System Science and Support Hazard Resilience.

https://cpo.noaa.gov/funding-opportunities/

NOAA NOFO Page 2 of 23

The NOAA Office of Oceanic and Atmospheric Research (OAR), or "NOAA Research," provides the research foundation for understanding the complex systems that support our planet. Through cutting-edge research and innovation, OAR is the engine that drives the next-generation science and technology that NOAA depends upon in order to produce operational products, tools, and services. Working in partnership with other organizational units of NOAA, a bureau of the Department of Commerce, OAR enables better forecasts, earlier warnings for natural hazards, improved monitoring of Earth systems, and a greater understanding of those systems. The mission of OAR is to conduct research to understand and predict the Earth system; develop technology to improve NOAA science, service, and stewardship; and transition the results into use to help meet challenges faced by society.

As part of OAR, the Climate Program Office (CPO) supports mission-driven research to advance understanding of climate and to deliver actionable information to society to help Americans plan and respond. This FY 2027 Notice of Federal Funding Opportunity (NOFO) aligns with one of CPO's core functions, to advance extramural research through a competitive process for continued innovation across NOAA. Key aspects of CPO's work include:

• Advancing foundational and applied, cross-disciplinary climate and Earth system sciences, capacity building, tool development, and engagement.

• Collaborating closely with partners within NOAA and with the broader community to advance knowledge and support decisions.

• Building networks, partnerships, and collaborations, converging around the best ideas, and providing support to accelerate emerging innovation.

• Empowering communities across the Nation to be safer, healthier, and more prosperous in the face of climate-relevant hazards, including supporting preparedness for and protection against extreme weather, heat, floods, wildfire, and related air quality issues; managing for precipitation and drought; addressing coastal change and inundation; and sustaining marine and freshwater ecosystems.

In FY 2027, the CPO Modeling, Analysis, Predictions and Projections (MAPP) Program, the Adaptation Sciences (AdSci) Program, and the National Integrated Heat Health Information System (NIHHIS) Program are jointly soliciting proposals to accelerate innovation in NOAA's Earth system science and to inform hazard resilience decision making through the application of Super Intelligence/Machine Learning (SI/ML). Proposals will focus on examining the application of SI/ML to advance NOAA's capabilities across the following three Priority Areas: 1) multi-annual to decadal prediction, 2) hazard resilience decision-support information, and 3) extreme heat predictions and preparedness.

Full Text of Announcement I. Funding Opportunity Description A. Program Objective The Climate Program Office (CPO) [1], in the National Oceanic and Atmospheric Administration (NOAA)'s Office of Oceanic and Atmospheric Research (OAR), advances NOAA's mission of science, service, and stewardship. CPO supports mission-driven climate research to advance understanding and deliver actionable information that helps Americans plan and respond. CPO collaborates closely with partners within NOAA and with the broader academic, Federal, Tribal, and private sector communities. CPO works in close partnership with OAR laboratories and programs to complement and support their in-house research. CPO also works with other parts of NOAA to support their mission areas in weather, oceans, fisheries, and service delivery. Undertaking a range of science and services initiatives, CPO helps communities address climate-related challenges (e.g. economic, safety, security, and health impacts) and pursue solution-focused opportunities. CPO's definition of services is comprehensive, encompassing both the development and dissemination of actionable science to inform decision-making, as well as the partnerships to engage in and understand the contexts within which relevant decisions are made.

https://cpo.noaa.gov/

NOAA NOFO Page 3 of 23

CPO programs engage across physical-biogeochemical, socio-economic, communication and engagement research communities to meet CPO's objectives. This joint research solicitation is relevant to the research objectives of the Modeling, Analysis, Predictions and Projections Program [2], the Adaptation Sciences Program [3], and the National Integrated Heat Health Information System Program [4].

B. Program Priorities Competition Title

Super Intelligence/Machine Learning Innovation to Advance NOAA's Earth System Science and Support Hazard Resilience

Competition Information

Accelerating Federal use of AI/SI through innovation is an ongoing U.S. Government priority [5, 6, 7].

The NOAA Artificial Intelligence Strategy [8] set the course for applying AI/SI to achieve transformational advancements in the quality and timeliness of products and services across the agency's mission areas.

Goals and objectives aim to advance AI/SI research and innovation in support of NOAA's mission, accelerate the transition of AI/SI research to applications, strengthen and expand AI/SI partnerships, and promote AI/SI proficiency in the workforce. The NOAA Center for Artificial Intelligence (NOAA Center for AI) [9] has been a conduit for AI/SI and Machine Learning (ML), exploring the needs and capabilities of the NOAA community across mission areas.

SI/ML innovation for NOAA Earth system science and services has emerged through projects supported by CPO programs involving a variety of partners across NOAA and the external community [e.g., 10].

These innovations have led to advances in process research, and promising experimental new mapping, modeling, and prediction decision-support tools. CPO-supported advances have complemented and augmented significant and rapid SI/ML innovation occurring internally at NOAA OAR laboratories and other NOAA Line Offices [e.g., 11]. CPO has also partnered with the NOAA Center for AI to disseminate information on AI/SI innovation for Earth system sciences, promote the creation of research data that can be used by these tools (AI/SI-Ready), and support AI/SI proficiency in the NOAA workforce.

In FY 2027, the Climate Program Office's Modeling, Analysis, Predictions and Projections Program, the Adaptation Sciences Program, and the National Integrated Heat Health Information System Program are jointly soliciting proposals to accelerate innovation in NOAA's Earth system science and to inform hazard resilience through the application of SI/ML. Project proposals for this competition must focus on the Priority Areas listed below, and may elect to address one or multiple of those Priority Areas. Overall project selections will be balanced among Priority Areas to achieve the intended objectives of this competition. Projects from this competition will aim to enhance partnerships and accelerate progress for SI/ML innovation across NOAA, including across OAR laboratories, with the NOAA Center for AI and the NWS as well as other NOAA service Line Offices, advancing extramural research through competitive research.

Priority Area 1 – SI/ML Innovation to Advance Multi-Annual to Decadal Prediction

NOAA stakeholders need multi-annual to decadal climate predictions to plan activities across U.S. socio-economic sectors, including water, energy and the built environment [e.g., 12]. The need is for predictive information that is reliable, timely, and at a scale that is ready to use. The science community has been examining predictability sources, and there are experimental predictive systems' prototypes that aim at multi-annual to decadal prediction, but no U.S. system that currently delivers such information routinely and authoritatively [13]. OAR CPO has long been engaged in research efforts to expand the prediction horizon from weather to longer timescales, and to create information that better responds to NOAA's stakeholder needs (e.g., actionable quantification of uncertainty regarding hazards, clear characterization of predictability limits, etc.) [e.g., 14]. The application of SI/ML has the potential to bring significant innovation in diagnosing predictability sources and improving the efficiency and capability of NOAA Earth system prediction systems.This NOFO supports relevant SI/ML innovation in the scientific community.

https://cpo.noaa.gov/divisions-programs/earth-system-science-and-modeling-division/modeling-analysis-predictions-and-projections/ https://cpo.noaa.gov/divisions-programs/climate-and-societal-interactions/the-adaptation-sciences-program/ https://cpo.noaa.gov/national-integrated-heat-health-information-system/ https://www.federalregister.gov/documents/2025/01/31/2025-02172/removing-barriers-to-american-leadership-in-artificial-intelligence https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/ https://www.noaa.gov/ai/research https://www.drought.gov/sites/default/files/2022-10/2022%E2%80%932026_NIDIS_StrategicPlan_Aug22.pdf https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021MS002529 https://doi.org/10.1175/BAMS-D-12-00050.1

NOAA NOFO Page 4 of 23

Proposals responsive to Priority Area 1 will focus on addressing gaps in NOAA modeling and prediction capabilities, examining how SI/ML innovation can accelerate the development of multi-annual to decadal ("M2D" hereafter) Earth system climate predictions (at 2–10 years lead times) and reliable predictive information for decision-relevant applications. Proposed research should address one or both of the following objectives:

a. Accelerate Predictability Discovery and Diagnosis. Proposed research will develop and/or use existing SI/ML methods for improved signal-to-noise ratios of known M2D predictability sources or to identify new, effective sources of or pathways for improved M2D predictability. Research must be grounded in physical interpretability and testing of robustness across independent datasets or frameworks, demonstrating improvements upon current capabilities. Proposals may tackle issues particular to the application of SI/ML techniques to prediction on these timescales, such as the learned signal from the forced trend versus internal variability driving apparent prediction skill, as well as robustness of prediction approaches across predictability regimes. Proposals may also examine how predictability sources vary across spatial scales relevant to prediction systems, regimes, and regional predictability footprints. Proposed research should use model simulations (i.e., NOAA SPEAR, CMIP6, or other suitable large modeling datasets) [15, 16] and/or diverse types of observational data (e.g., NOAA 20CR [17], ERA5).

b. Improve Computational Efficiency and Predictive Systems. Proposed research should develop and/or use existing SI/ML emulators of NOAA models that are or can be applied for M2D timescales [e.g., 15] or their components to improve their computational efficiency, while demonstrating preserved model performance and process fidelity. Proposals should explore issues related to the coupling of SI/ML-derived emulators or alternative SI/ML emulator approaches for the development of systems for the efficient simulation and prediction of Earth system processes. Proposed systems may include SI/ML-based post-processing or spatial refinement where these steps enhance predictive skill and preserve model fidelity. Proposed research may use emulator systems to develop very large ensembles of predictions to better sample the uncertainty space and improve signal-to-noise ratio. Proposals may develop and apply SI/ML or hybrid prediction approaches to best exploit predictability sources and emulator technologies for improved M2D NOAA prediction systems (e.g., improved initial Earth system state, embedding of human activities, aiding in "best" ensemble members selection). This may also include SI/ML-based refinements of undergirding training datasets (e.g., 20CR) that can yield improvements for prediction systems. Proposals may consider issues related to forecast-of-opportunity windows, such as state-dependent predictability or testing strategies to trigger forecast initialization based on potential utility of forecast outputs.

In addition to the requirements and considerations valid across all Priority Areas (see section below), research proposals for Priority Area 1 should:

• Clearly articulate how research findings could ultimately lead to improved NOAA M2D predictions.

• Include interpretability of SI/ML results, and provide validation and verification, with an emphasis on process fidelity, as feasible.

• Quantify and characterize how SI/ML methods represent or reduce predictive uncertainty at M2D timescales.

• Include benchmarking approaches of proposed SI/ML methods in comparison with conventional approaches, in alignment with common modeling community practices, and examine any advantages from the SI/ML methods.

• Teams are strongly encouraged to be interdisciplinary and include individuals with SI/ML, modeling, and Earth systems/prediction expertise. Teams should demonstrate a clear understanding of NOAA's stakeholders predictive M2D needs.

• Include, but not limit research to, the use of NOAA model and observational data.

https://www.gfdl.noaa.gov/spear/ https://wcrp-cmip.org/cmip-phases/cmip6/ https://psl.noaa.gov/data/20thC_Rean/ https://www.gfdl.noaa.gov/spear/

NOAA NOFO Page 5 of 23

• Have clear data and methodology sharing plans, potentially including the transfer of data or methods to relevant NOAA institutional recipients, and embed engagement of NOAA relevant partners, as feasible. This could include plausible pathways by which approaches developed through the proposed work could generally inform future NOAA prediction system development.

• Consider the relevance and applicability of M2D predictive advances across CPO-led programs that inform decisions (e.g., the National Integrated Drought Information System [18], the National Integrated Heat Health Information System [19], Regional Integrated Sciences and Assessments [20]).

• Engage stakeholders in visioning or co-development of systems, as feasible.

Priority Area 2 – SI/ML Innovation for Hazard Resilience Decision Support

Americans have rapidly integrated emerging SI/ML tools for many aspects of their daily lives, including finding information about weather and climate hazards to support their immediate and longer-term plans.

SI/ML tools often make such information easily accessible and interactive. As such, these new tools have the potential to significantly contribute to informing decisions regarding weather and climate hazards.

However, because of the rapidity with which SI/ML tools have become available, research on how to best use SI/ML innovation for hazard and resilience decision support is just emerging [e.g., 21]. It is often unclear how people are using or interpreting NOAA information provided by SI/ML tools when making hazard-related decisions, what is affecting SI/ML tool uptake, and how to evaluate their value for decision-making. OAR CPO has long engaged with the community to improve weather and climate hazard resilience decision support for its stakeholders, including understanding relevant social and behavioral dynamics, and developing best engagement practices [3, 18, 19, 20]. The emergence of SI/ML-based decision-support tools represents a new frontier in CPO's research efforts to inform hazard decision making and planning for improved resilience.

Proposals responsive to Priority Area 2 will focus on SI/ML innovations to support resilience to weather and climate hazards through risk-informed decision making. Proposed research should address one or more of the following objectives:

a. Evaluate Current and Potential SI/ML Applications for Hazard Decision Support. Research should apply socio-economic methodologies to assess how SI/ML is being used in the U.S. at a community or organization level, to inform decisions related to weather and climate hazard risks, and the potential to use SI/ML to improve hazard planning and resilience through the integration of new types of data. Research may examine any or all of the following: 1) scales, settings, and modality demonstrating successful use-cases of SI/ML applications in hazard decision making, and types of hazards best suited for SI/ML decision support, 2) potential pitfalls and risks associated with applying SI/ML to hazard decision making, and lessons learned that can inform further development of standards and best practices for the development of SI/ML tools meant to support risk-informed decision making, and/or 3) the applicability of SI/ML to more efficient processing and integration of various forms of social and infrastructure-oriented data, including qualitative data, into decision-support analyses and tools. Research will aim at gaining an improved understanding of how SI/ML can best be leveraged to develop more effective and comprehensive tools that include NOAA's weather and climate information to support hazard adaptation and resilience.

https://www.drought.gov https://heat.gov/ https://www.nationalacademies.org/projects/DEPS-BEES-25-03 https://cpo.noaa.gov/divisions-programs/climate-and-societal-interactions/the-adaptation-sciences-program/ https://www.drought.gov https://heat.gov/

NOAA NOFO Page 6 of 23

b. Identify SI/ML Adoption Enabling Socio-Technical Factors. Proposed research will examine the socio-technical factors that shape how U.S. communities and organizations at different scales can utilize SI/ML for weather and climate hazard risk-informed decision making in NOAA's mission areas.

This may include examining how SI/ML application is affected by institutional barriers, trust, shifting roles of decision makers and stakeholders, available data and scales, and questions of governance.

Research on small- to mid-sized communities/organizations, who may have limited capacities to plan for resilience and/or utilize SI/ML (e.g., due to staffing limitations, data literacy limiting technology integration), is of particular interest, given SI/ML's potential to be resource-efficient in supporting risk-informed decision making. Proposed research will strive to achieve a better understanding of the factors and capacities that underpin how communities perceive, interact with, and utilize SI/ML for risk-informed decision making to inform more effective and appropriate application of SI/ML in a specific context and place to improve resilience.

In addition to the requirements and considerations valid across all Priority Areas (see section below), research proposals for Priority Area 2 should:

• Focus on SI/ML tools that provide information for weather and climate hazard risk decision making for the U.S. and draw from NOAA data, products, and services.

• Consider communication pathways to NOAA for research findings.

• Examine how SI/ML tools may be using or could be using NOAA information (i.e., data, model forecasts, etc.). In this regard, PIs are strongly encouraged to collaborate with NOAA staff with expertise in NOAA services (e.g., NWS, NESDIS/NCEI, NOS, NMFS) and NOAA OAR entities developing experimental SI/ML-based information sharing tools.

• Leverage CPO-led decision-support engagement networks [3, 18, 19, 20], if relevant to proposed research, and examine SI/ML-augmented capabilities for existing mechanisms.

Priority Area 3 – SI/ML for Extreme Heat Thresholds, Prediction, and Preparedness

Extreme heat is a leading cause of weather-related fatalities each year [22], with significant impacts also on infrastructure and across economic sectors (e.g., agriculture). Extreme heat prediction and preparedness are critical to protect people and property, and NOAA provides relevant products and services working with many partners [19]. OAR CPO has been at the forefront of extreme heat engagement and coordination efforts for improved resilience [4], and has also supported research to advance NOAA capabilities, through process research, modeling, and predictions. SI/ML application to address extreme heat provides the opportunity to potentially accelerate progress.

Proposals responsive to Priority Area 3 will focus on SI/ML innovation to improve predictions of extreme heat and enhance preparedness. Proposed research should address one or more of the following objectives:

https://cpo.noaa.gov/divisions-programs/climate-and-societal-interactions/the-adaptation-sciences-program/ https://www.drought.gov https://heat.gov/ https://heat.gov/learn-about-extreme-heat/ https://heat.gov/ https://cpo.noaa.gov/national-integrated-heat-health-information-system/

NOAA NOFO Page 7 of 23

a. Identify and Model Critical Extreme Heat Thresholds and Interactions. Proposed research will develop and/or apply SI/ML methods to identify extreme heat thresholds for hazards to people and property, and model the complex interactions unleashed by extreme heat across U.S. systems and infrastructure. Research will apply SI/ML to examine and integrate information across different types of extreme heat-relevant data (e.g., Earth system, human infrastructures (including built environment), and behavior dynamics), data sources (e.g., in situ, high-resolution remote sensing, aerial imagery and other geospatial information, and citizen-science urban heat campaigns), and for specific U.S. environments. For example, proposals may consider temperature, humidity, wildfire pollutants, and soil moisture data, in combination with water scarcity, power outages, health and air quality indicators, and infrastructure stressors. Proposals may leverage SI/ML to efficiently process and integrate non-conventional data for human systems (e.g., interview data, reports, behavioral information, cooling center data, labor data, etc.). Research should focus on examining and modeling thresholds and interactions of relevance across health, built infrastructure, and agriculture, among various economic sectors. Proposals may elect to focus on extreme heat thresholds and interactions specifically in select urban areas, where extreme heat is aggravated by the "urban island effect."

These proposals will apply SI/ML to gain more precise representations of extreme heat in urban contexts (e.g., extreme heat intensity, duration, and unique spatiotemporal dynamics across different cities) and the interactions across urban systems.

b. Identify Extreme-Heat Enhanced Prediction Opportunities. Research proposals will apply SI/ML to examine U.S. extreme heat forecast-of-opportunity windows, that is, conditions in which the skill of extreme heat predictions is enhanced. Research must provide a physical interpretation regarding the sources of predictability and phenomena that lead to enhanced predictions, as suggested by SI/ML analyses. Research should include assessing whether NOAA models and forecasting systems (research or operational) capture such forecast opportunities, as depicted in SI/ML-based observational analyses. Proposals may develop SI/ML forecast post-processing methods and forecast metrics that are time- and location-dependent so as to inform specifically on these extreme heat forecast-of-opportunity windows. Proposals should engage relevant NOAA partners to accelerate any relevant internal research efforts, facilitate the uptake of information regarding when/where improved extreme heat prediction skill can be expected, and identify which prediction metrics to use to best convey this information.

In addition to the requirements and considerations valid across all Priority Areas (see section below), research proposals for Priority Area 3 should:

• Apply relevant NOAA data (e.g., from NESDIS, NWS), as useful.

• Engage with NIHHIS partner agencies [23] to inform research and communicate findings.

Requirements and Considerations Valid Across All Priority Areas

In addition to the Priority Area-specific requirements listed above, the following requirements are valid across all Priority Areas. Proposed projects should:

• Provide interpretations of SI/ML-based results in terms of established processes and phenomena in relevant domain sciences (e.g., physical, socio-economic, behavioral, etc.) to support their robustness and reliability.

• Advance NOAA SI/ML-Ready data [24, 25] and workforce goals by: 1) making SI/ML-Ready NOAA data developed as a result of projects publicly available; 2) considering contributing a Python computational notebook for the project to the NOAA Learning Journeys Library [26]; 3) when addressing team composition, considering how research will contribute to AI workforce development through training, mentorship, education, and participation of students and early-career professionals.

• Collaborate with and/or leverage relevant partners, including: mission-driven organizations, academic institutions, state and local governments, as well as NOAA partners.

https://heat.gov/about-nihhis/ https://www.noaa.gov/ai/resources https://github.com/esipfed/data-readiness https://www.noaa.gov/resources/learning-journey-library

NOAA NOFO Page 8 of 23

• Include representatives from a variety of sciences and sectors required to fulfill the goals and objectives of the research. In particular, teams involving both SI/ML expertise and subject-matter expertise are strongly encouraged. Investigator teams should also include members of relevant communities that will use and benefit from research outcomes.

• Include letters of support in their proposal from relevant community and partners organizations who will benefit from and/or be impacted by the project outcomes.

• Have clear data and methodology sharing plans, potentially including the transfer of data or methods to relevant NOAA institutional recipients, and embed engagement of NOAA relevant partners, as feasible. This could include plausible pathways by which approaches developed through the proposed work could inform or integrate with future NOAA prediction system development.

• Investigators from this competition may be asked to participate in NOAA workshops, webinars, or meetings, to facilitate the collaborations and communications.

Competition Contacts

Competition Manager for general NOFO information purposes: Kathleen Palermo (Kathleen.Palermo@noaa.gov).

For programmatic questions, applicants should contact the most relevant Program Manager for their proposal as follows:

• Priority Area 1: Modeling, Analysis, Predictions and Projections (MAPP) Program, Dan Barrie (Daniel.Barrie@noaa.gov).

• Priority Area 2: Adaptation Sciences (AdSci) Program, Bhaskar Subramanian (Bhaskar.Subramanian@noaa.gov).

• Priority Area 3:

• National Integrated Heat Health Information System (NIHHIS), Barbara Boustead

(barbara.boustead@noaa.gov).

• MAPP, Dan Barrie (Daniel.Barrie@noaa.gov).

• AdSci, Andrea Miralles- Barboza (Andrea.Miralles-Barboza@noaa.gov).

Competition Supporting Information

1. https://cpo.noaa.gov/

2. https://cpo.noaa.gov/divisions-programs/earth-system-science-and-modeling-division/modeling-analysis-predictions-and-projections/

3. https://cpo.noaa.gov/divisions-programs/climate-and-societal-interactions/the-adaptation-sciences-program/

4. https://cpo.noaa.gov/national-integrated-heat-health-information-system/

5. https://www.federalregister.gov/documents/2025/01/31/2025-02172/removing-barriers-to-american-leadership-in-artificial-intelligence

6. https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf

7. https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/

8. https://sciencecouncil.noaa.gov/wp-content/uploads/2023/04/2020-AI-Strategy.pdf

9. https://www.noaa.gov/ai

10. https://cpo.noaa.gov/webinar-series/ai-applications-in-earth-system-and-climate-science/

11. https://www.noaa.gov/ai/research

12. https://www.drought.gov/sites/default/files/2022-

10/2022%E2%80%932026_NIDIS_StrategicPlan_Aug22.pdf

13. https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021MS002529

14. https://doi.org/10.1175/BAMS-D-12-00050.1

15. https://www.gfdl.noaa.gov/spear/ https://cpo.noaa.gov/ https://cpo.noaa.gov/divisions-programs/earth-system-science-and-modeling-division/modeling-analysis-predictions-and-projections/ https://cpo.noaa.gov/divisions-programs/earth-system-science-and-modeling-division/modeling-analysis-predictions-and-projections/ https://cpo.noaa.gov/divisions-programs/climate-and-societal-interactions/the-adaptation-sciences-program/ https://cpo.noaa.gov/divisions-programs/climate-and-societal-interactions/the-adaptation-sciences-program/ https://cpo.noaa.gov/national-integrated-heat-health-information-system/ https://www.federalregister.gov/documents/2025/01/31/2025-02172/removing-barriers-to-american-leadership-in-artificial-intelligence https://www.federalregister.gov/documents/2025/01/31/2025-02172/removing-barriers-to-american-leadership-in-artificial-intelligence https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/ https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/ https://sciencecouncil.noaa.gov/wp-content/uploads/2023/04/2020-AI-Strategy.pdf https://www.noaa.gov/ai https://cpo.noaa.gov/webinar-series/ai-applications-in-earth-system-and-climate-science/ https://www.noaa.gov/ai/research https://www.drought.gov/sites/default/files/2022-10/2022%E2%80%932026_NIDIS_StrategicPlan_Aug22.pdf https://www.drought.gov/sites/default/files/2022-10/2022%E2%80%932026_NIDIS_StrategicPlan_Aug22.pdf https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021MS002529 https://doi.org/10.1175/BAMS-D-12-00050.1 https://www.gfdl.noaa.gov/spear/

NOAA NOFO Page 9 of 23

16. https://wcrp-cmip.org/cmip-phases/cmip6/

17. https://psl.noaa.gov/data/20thC_Rean/

18. https://www.drought.gov

19. https://heat.gov/

20. https://cpo.noaa.gov/divisions-programs/climate-and-societal-interactions/cap-risa

21. https://www.nationalacademies.org/projects/DEPS-BEES-25-03

22. https://heat.gov/learn-about-extreme-heat/

23. https://heat.gov/about-nihhis/

24. https://www.noaa.gov/ai/resources

25. https://github.com/esipfed/data-readiness

26. https://www.noaa.gov/resources/learning-journey-library

C. Program Authority 49 U.S.C. 44720(b), 15 U.S.C. 2904, 15 U.S.C. 2931-2934

II. Award Information A. Funding Availability This Notice of Federal Funding may fund up to 15 new awards. It is anticipated that most awards will be at a funding level of up to $250,000 per year.

Additional Specifications Across Priority Areas

• Funding is subject to the availability of funds.

• Federal funding for FY 2028 may be used to fund awards submitted under this Notice of Funding

Opportunity.

• Current or previous grantees are eligible to apply for a new award that builds on, but does not replicate, activities covered in existing or previous awards.

• Current grantees should not apply for supplementary funding through this announcement.

B. Project/Award Period The project award period will last 1-3 years, depending on scope.

C. Type of Funding Instrument The funding instrument for awards will be a grant. If, however, it is anticipated that NOAA will be substantially involved in the implementation of the project, a cooperative agreement may be awarded.

• Examples of substantial involvement may include, but are not limited to, applications for collaboration between NOAA scientists and a recipient scientist.

• NOAA will make decisions regarding the use of a cooperative agreement on a case-by-case basis.

• Funding for contractual arrangements for services and products for delivery to NOAA is not available under this announcement.

III. Eligibility Information A. Eligible Applicants Eligible applicants are:

• Institutions of higher education

• Other nonprofits

• Commercial organizations

• Local and federally recognized Tribal governments.

• Federal agencies that possess the statutory authority to receive transfers of funds.

• The funding instrument for a selected application from a non-NOAA Federal applicant will be through an inter-agency transfer of funds, provided:

https://wcrp-cmip.org/cmip-phases/cmip6/ https://psl.noaa.gov/data/20thC_Rean/ https://www.drought.gov https://heat.gov/ https://cpo.noaa.gov/divisions-programs/climate-and-societal-interactions/cap-risa https://www.nationalacademies.org/projects/DEPS-BEES-25-03 https://heat.gov/learn-about-extreme-heat/ https://heat.gov/about-nihhis/ https://www.noaa.gov/ai/resources https://github.com/esipfed/data-readiness https://www.noaa.gov/resources/learning-journey-library

NOAA NOFO Page 10 of 23

1. Legal authority exists for the Federal applicant to receive funds from another agency.

2. PLEASE NOTE: Before non-NOAA Federal applicants may be funded, they must demonstrate that they have applicable legal authority for an interagency transfer of funds.

3. Because this announcement is not proposing to procure goods or services from applicants, the Economy Act (31 USC 1535) is not an appropriate legal basis See “special instructions for federal applicants” on the CPO website;

https://cpo.noaa.gov/funding-opportunities/.

Foreign or international institutions are not eligible to apply.

B. Cost Share or Matching Requirement The competition listed in this NOFO does not have any cost sharing or matching criteria.

C. Other Criteria that Affect Eligibility None.

IV. Application and Submission Information A. Address to Request Application Package Application packages can be found on grants.gov. For applicants without Internet access, please contact the CPO Grants Specialist Kathleen Palermo by mail to obtain an application package:

Kathleen Palermo

NOAA Climate Program Office (R/CP1)

SSMC3, Room 12712

1315 East-West Highway, Silver Spring, MD 20910

B. Content and Form of Application Content and Form of Letter of Intent

The purpose of the Letter of Intent (LOI) process is:

• To provide information to potential applicants on the relevance of their proposed project to the Competition in advance of preparing a full application.

• Full applications will be encouraged only for LOIs deemed relevant.

• While LOIs are strongly encouraged, applicants are not required to submit them and may submit a full application even if they have not submitted a LOI.

The LOI should provide a concise description of the proposed work and a statement regarding its relevance to the Competition. The LOI should be no more than two pages in length and should include the items listed below. If these items are not included or the LOI is submitted late, the LOI may not be considered:

• Competition Name and Priority Area targeted by the LOI.

• A tentative project title.

• Name(s) and institution(s) of the Lead Principal Investigator(s) and other Principal

Investigator(s).

• Email addresses to receive the LOI response.

• Statement of the problem.

• Brief summary of work to be completed, methodology to be used, data sets needed or to be collected

• Partners that will be involved.

https://cpo.noaa.gov/funding-opportunities/

NOAA NOFO Page 11 of 23

• Approximate cost of the project.

• Project duration.

• Relevance to the Competition and Priority targeted by the LOI.

A response to the LOI from CPO (e-mail or letter) will be sent to the investigator within four weeks after the LOI due date encouraging or discouraging a full application based on its relevance to the Competition.

It is then entirely up to the investigator whether to submit a full application.

Full Application Requirements

Failure to comply with required provisions below will result in applications being returned without review.

Required page limit and formatting: a maximum of 25 pages (under 3 Principal Investigators, PIs hereafter) or 30 pages (3 or more PIs). 12-point font type, single spaced, with one-inch margins on standard 8.5 by 11 inch paper.

Required elements for each application (within the above page limit):

1. Title Page (page limit: 1 page; 2 pages for 3 or more PIs)

Identify PIs, Competition name/number, and funding details for each budget period.

The Lead PI and institutional representative should be identified by: full name, title, organization, telephone number, email, and address.

2. Abstract (page limit: 1)

Include project title, Competition/Priority Area, problem introduction, rationale, summary of work and impacts.

3. Project Narrative (page limit: 15; 20 pages for 3 or more PIs)

Describe objectives, benefits, relevance to the Competition, and roles. Applicants are encouraged to indicate in the project narrative the extent to which, if any, generative SI technology was used and how it was used to develop their proposal.

4. Data/Information Sharing Plan (page limit: 2 pages)

Data/information sharing management plan. See section VI.B. Administrative and National Policy requirements for more information.

5. Budget Table & Narrative

Detailed table with expenses and justifications for each expense. Duplicate work with different federally-funded projects, commonly referred to as "double dipping," is not permitted. As stated in the Code of Federal Regulations, specifically Subpart E- Cost Principles,2 CFR 200.430 (i)(1)(i-vii), Standards for Documentation of Personnel Expenses, "Charges to Federal awards for salaries and wages must be based on records that accurately reflect the work performed." The regulations additionally state that the work, "Reasonably reflects the total activity for which the employee is compensated by the non-Federal entity, not exceeding 100% of compensated activities." The budget narrative will also delineate PI roles, responsibilities, and work timeline as it relates to budget.

Additional required elements for all applications but excluded from page limits:

6. Bibliography

7. Vitaes

Curriculum vitae for all PIs/Co-PIs.

8. Current and Pending Support

NOAA NOFO Page 12 of 23

Federal support list; include project title, supporting agency, investigator months/year, dollar value and duration.

9. Negotiated indirect cost rate agreement (NICRA)

10. Federal Forms

SF424, SF424A, SF424B, CD511 and other mandated forms.

11. High Performance computing request and transition plans (only required if applicable and only for MAPP Program-directed proposals).

The form to request the use of NOAA's high-performance computing platforms is considered part of the full proposal. Transition plans should not exceed one page in length.

Additional optional elements excluded from page limits:

12. Letters of Support

For Co-applicants: All sections of the co-application must be identical to the Primary Investigator's (Lead PI) application (as above) except for "Budget Table and Narrative", "NICRA", and "Federal Budget Forms" which must be specific to the co-applicant institution.

For Subawardees: Subawardees should not submit a separate application. However, subwards still need to submit to the Lead PI their own federal forms (SF424 and SF424a) and budget information, and the Lead PI will provide them with their funding.

For First Time Applicants: Ensure SAM registration and UEI before applying (see section C below).

• Tip: Start early to avoid delays.

• Indirect Costs: Use established rates or 15% de minimis rate if no rate agreement in place.

All Applicants: Please reference the "Application Checklist" on the CPO website to assist you in submitting your application.

Proposals submitted in response to this Announcement must include a Data Management Plan (up to 2 pages). See Section VI.B., Administrative and National Policy Requirements, below for additional information on what the plan should contain.

Proposals submitted in response to this Announcement must include a Data Management Plan (up to 2 pages). See Section VI.B., Administrative and National Policy Requirements, below for additional information on what the plan should contain.

National Environmental Policy Act (NEPA) Questionnaire: This program does not require any NEPA questions to be answered as part of the application.

C. Unique entity identifier and System for Award Management (SAM) Excerpt 2 CFR Appendix-I-to-Part-200(b)(5)(ii)

• Each applicant (unless the applicant is an individual or Federal awarding agency that is excepted from those requirements under 2 CFR 25.110(a) or (b)) is required to:

(i) Be registered in SAM before submitting its application;

(ii) Provide a valid unique entity identifier (UEI) in its application; and

(iii) Continue to maintain an active SAM registration with current information at all times during which it has an active Federal award or an application or plan under consideration by a Federal awarding agency.

• NOAA may not make a Federal award to an applicant:

• Until the applicant has complied with all applicable UEI and SAM requirements.

NOAA NOFO Page 13 of 23

• If an applicant has not fully complied with the requirements by the time NOAA is ready to make a Federal award, NOAA may determine that the applicant is not qualified to receive a Federal award and use that determination as a basis for making a Federal award to another applicant.

Grants.gov

After receiving a UEI from SAM.gov, applicants must register their organization in Grants.gov.

Register early to avoid delays.

To apply:

• Register for a user ID and password.

• Process time: 3-5 days or up to 4 weeks if all steps are not completed correctly.

• Start early and read the instructions before the deadline.

For organization registration, see Grants.gov registration info https://www.grants.gov/applicants/applicant-registration.

Keep Grants.gov and SAM registrations current. This is essential for your applications to be accepted.

Create a new SAM user account, as CCR usernames won't work. Registration on SAM is mandatory.

• Stay registered: Organizations already on Grants.gov don't need to register again.

• Maintain: Ensure your SAM and Grants.gov passwords are up-to-date.

• Check status: For more info or to verify a current registration, visit www.sam.gov/portal/public/SAM.

• Once an organization submits their registration in SAM.gov, it can take at least ten business days for it to become active.

If you experience a Grants.gov systems issue (technical problems or glitches with the Grants.gov website) that you believe threatens your ability to complete a submission before the application deadline, please do all of the following:

• Print any error message received

• Call the Grants.gov Contact Center at 1-800-518-4726 for immediate assistance

• Contact NOAA using the contact information in section VIII. of this NOFO prior to the close of the Competition

• Ensure that you obtain a case number regarding your communications with Grants.gov

In the event of a confirmed systems issue, NOAA reserves the right to accept an application in an alternate format prior to the application deadline. Problems with an applicant organization’s computer system or equipment are not considered system issues. Similarly, an applicant’s failure to do the following are not considered systems issues:

• Complete the required registration

• Ensure that a registered Authorized Organization Representative (AOR) submits the application

• Read an email message with guidance from Grants.gov.

eRA Commons

Prior to submitting in Grants.gov, applicant organizations must first register in eRA

Commons.

• The eRA registration can start while an organization is waiting for their final SAM.gov approval of their UEI..

• eRA Commons registration must be completed by the Signing Official (SO). An SO is someone in the organization with signatory authority such as a President, Executive Director, Owner, etc.

• Instructions can be found here: https://www.era.nih.gov/register-accounts/register-in-era-commons.htm https://www.grants.gov/applicants/applicant-registration http://grants.gov/applicants/organization_registration.jsp http://www.sam.gov/portal/public/SAM https://www.era.nih.gov/register-accounts/register-in-era-commons.htm https://www.era.nih.gov/register-accounts/register-in-era-commons.htm

NOAA NOFO Page 14 of 23

• Organizations registering in the eRA Commons for the first time should allow 2-4 weeks to complete the registration process.

Common Errors

• A Project Director/Principal Investigator (PD/PI) account must be created and entered on the Applicant Identifier field of the SF-424 for a successful submission.

• The applicant’s congressional district number must be included in the SF-424 for a successful submission. It must be the two-letter abbreviation, a hyphen, and the three-digit district number.

For example: State of Virginia, 1st Congressional District would be “VA-001.”

• Refer to the “Common Errors” section of the NOAA Fisheries site for more information on common errors that can impede a successful submission:

https://www.fisheries.noaa.gov/national/funding-financial-services/grant-application-process

D. Submission Dates and Times Dates: Letters of intent (LOIs) should be received by email by 11:59 p.m. Pacific Time on November 17, 2026.

Full Applications: Full applications must be received by 11:59 p.m. Pacific Time, on February 9, 2027.

E. Intergovernmental Review Applications under this program are not subject to Executive Order 12372, Intergovernmental Review of Federal Programs.

F. Funding Restrictions Fees and profits are not permitted.

G. Other Submission Requirements All applications should be submitted through grants.gov.

If an applicant does not have Internet access, CPO Grants Specialist Kathleen Palermo should be contacted by mail at: NOAA Climate Program Office (R/CP1), SSMC3, Room 12712, 1315 East-West Highway, Silver Spring, MD 20910 for hard copy submission instructions.

Faxed or emailed copies of applications will not be accepted.

H. Address for Submitting Proposals CPO Grants Specialist Kathleen Palermo

NOAA Climate Program Office (R/CP1), SSMC3, Room 12712, 1315 East-West Highway, Silver Spring, MD 20910

V. Application Review Information

1. Importance/relevance and applicability of proposed projects to the program goals

Maximum Points: 5

(Final Weight=25%)

NOAA NOFO Page 15 of 23

This criterion ascertains whether there is intrinsic value in the proposed work and/or relevance to NOAA, federal, regional, state, tribal, indigenous or local activities. For the CPO grant competition in this NOFO, this includes importance and relevance to the program objective in Section I.A, program priorities in Section I.B, , the PI's record of making his/her data accessible and usable by the scientific community in the past, and the present Data/Information Sharing Plan described in Section IV.B(5) will also be considered when evaluating the importance and relevance of the application.

2. Technical/scientific merit

(Final Weight=50%) This criterion assesses whether the approach is technically sound and/or innovative, if the methods are appropriate, and whether the goals of the Competition will be realized through clear project goals and objectives.

3. Overall qualifications of applicants

(Final Weight=15%) This criterion assesses whether the applicant team possesses the necessary education, experience, training, facilities, and/or administrative resources to accomplish the project.

4. Project costs

(Final Weight =10%) This criterion evaluates the budget to determine if it is realistic and commensurate with the project needs and time frame.

Evaluation Criteria Review and Selection Process Application Process Overview Once a full application has been received, an administrative review will be conducted to determine compliance with requirements and completeness of the application. The Competition will be evaluated based on criteria provided in section V.A. Grant proposals for the Competition will be reviewed by a panel of subject matter experts who will score them for technical merit, applicants' qualifications, project costs, and relevance. Panelists may consist of both Federal and/or non-Federal experts. Panels will not give consensus advice. We protect the identities of reviewers to the extent permitted by law. Reviewers will be prohibited from uploading any content from grant applications, review information, and related records to generative SI tools.

Each reviewer…