TAME Extreme Weather and Wildfires Act
HB2770, the TAME Extreme Weather and Wildfires Act, directs the National Oceanic and Atmospheric Administration (NOAA) to expand its use of artificial intelligence for weather, water, space weather, and wildfire forecasting. The bill requires NOAA’s Under Secretary for Oceans and Atmosphere to develop and curate comprehensive training datasets, assess and build on existing federal datasets, and potentially develop and test global AI-based weather models. It also authorizes NOAA to explore advanced AI applications for improving forecast delivery, public preparedness, and decision support for communities and emergency managers.
The bill further creates a wildfire-focused fire environment modeling program that would use AI, observational data, and synthetic data to predict, detect, and monitor wildfires, smoke, and related hazards. It encourages partnerships with private and academic entities, supports workforce development for AI forecasting expertise, and directs NOAA to provide technical assistance on the use of AI weather models, including reforecast analysis and best practices for integrating AI and traditional numerical weather models. The bill also includes a public data-access provision allowing data and code developed under the act to be released openly, subject to national security, intellectual property, and other legal protections.
If enacted, the bill would expand NOAA’s statutory responsibilities by adding explicit authority and direction to develop AI-based forecasting datasets, models, and operational support tools. It would affect NOAA’s research, forecasting, and data-sharing practices, while also encouraging interagency coordination with DOE, NASA, NSF, Interior, Agriculture, and Homeland Security. The bill would not replace numerical weather modeling, but would require continued support for traditional observational systems, Earth system research, and numerical forecast development alongside AI tools.
The bill appears generally favorable and innovation-oriented, with its structure emphasizing modernization, public safety, and improved forecasting for extreme weather and wildfires. Because there were no committee transcripts or recorded votes provided, there is no evidence of formal opposition or support in the available record beyond the bill’s introduction and referral. The text suggests a bipartisan-appeal policy frame centered on resilience, emergency preparedness, and scientific advancement.
The main potential points of contention are likely to involve the role of private-sector and academic partnerships, the use of synthetic data, intellectual property and data-rights issues, and whether NOAA should prioritize AI systems over or alongside existing numerical weather models. Another possible concern is the bill’s open-data approach, which is limited by exceptions for national security, trade secrets, and contract restrictions. Some stakeholders may also question the environmental impacts of AI computing and the extent to which federal resources should be directed toward new AI infrastructure versus traditional forecasting capabilities.