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S 1484119th CongressIn Committee

FORECAST Act of 2025

Introduced: Apr 10, 2025
Standard Summary
Comprehensive overview in 1-2 paragraphs

The FORECAST Act of 2025 aims to strengthen NOAA’s weather research and forecasting, with a major focus on subseasonal-to-seasonal (S2S) forecasting—forecasts that cover the coming weeks to months. It broadens NOAA’s mandate to fund fundamental research on why S2S forecasts are possible or limited, improve data collection and use across the Earth system, and advance multi-model ensemble forecasting, data assimilation, and cross-model data exchanges. The bill directs NOAA to develop a national and regional clearinghouse for these forecasts and related information, and to leverage new technologies such as artificial intelligence, machine learning, and unmanned systems. It also requires alignment with a 2018 Congress-published report on S2S forecasting plans. Separately, the bill creates a new Workforce Innovation Program to educate and recruit next-generation talent in weather and Earth system technologies, with an emphasis on data assimilation, advanced computing, AI/ML, and new observing systems. It requires a formal workforce plan, use of pathways programs to help hire, and partnerships with colleges, universities, and nonprofit entities. The bill also updates NOAA’s direct hiring authorities to include these new programs and institutes a two-year report on the program’s effectiveness. Overall, the bill would increase funding for core S2S activities (through 2026-2027) and institutionalize a long-term investment in workforce development.

Key Points

  • 1Improvements to subseasonal-to-seasonal forecasting: NOAA must conduct fundamental research, collect/analyze Earth-system observations, advance multi-model ensemble forecasts, develop data assimilation methods, and create a national/regional internet clearinghouse for S2S forecasts and related information; build on AI/ML and emerging technologies; align with the 2018 Congress report.
  • 2Funding authorizations: For fiscal years 2026 and 2027, authorize $28.5 million for core S2S activities, plus additional funds as needed for Weather Research and Forecasting Innovation Act activities related to cross-development of fully coupled S2S forecast systems; funds may support the Earth Prediction Innovation Center and higher-education collaborations in specified focus areas (high-performance computing, scientific innovation, management/planning, external engagement).
  • 3Workforce Innovation Program (Sec. 415): Establish a program to educate and recruit personnel for weather/earth-system modeling and data assimilation; include scholarships/fellowships and pathways for next-generation researchers and practitioners who work with advanced computing, AI/ML, unmanned systems, and data assimilation.
  • 4Human capital planning: Require annual updates to a workforce plan that identifies needs, funding gaps, hiring challenges, and retention policies; include mechanisms to recruit via pathways programs and to fund partnerships with higher education or nonprofits to integrate new tech into the weather enterprise.
  • 5Updates to hiring authorities and accountability: Update NOAA’s direct-hiring rules to include the new programs and fellowships, and require an evaluation report within two years on the program’s effectiveness and impact on workforce quality and preparedness.

Impact Areas

Primary group/area affected: NOAA and the broader U.S. weather and climate forecasting enterprise; researchers and practitioners involved in data assimilation, Earth-system modeling, and subseasonal-to-seasonal forecasting; students and professionals through new scholarships/fellowships.Secondary group/area affected: Higher education institutions, nonprofit entities, and industry partners engaged in weather and climate science, data assimilation, AI/ML applications, and high-performance computing; potential expansion of interagency collaboration.Additional impacts: Development of a national clearinghouse and regional forecast information; increased use of AI/ML and unmanned systems in weather research; potential budget and workforce shifts toward long-term training and capacity-building to support advanced forecasting capabilities and cross-agency modeling efforts.
Generated by gpt-5-nano on Oct 31, 2025