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

The summary for the Climate Program Office FY 2027 - Super Intelligence/Machine Learning Innovation to Advance NOAA's Earth System Science and Support Hazard grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the DOC NOAA - ERA Production, which is the U.S. government agency offering this grant.

Climate Program Office FY 2027 - Super Intelligence/Machine Learning Innovation to Advance NOAA's Earth System Science and Support Hazard: 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. 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.