TAME Extreme Weather and Wildfires Act
- Sponsor
- Rep. Franklin, Scott [R-FL-18]
- Committees
- Science, Space, and Technology Committee (primary)
- Last action
- Apr 9, 2025
Bottom line
This bill aims to modernize NOAA's forecasting capabilities and improve public safety and resilience against extreme weather and wildfires by integrating advanced artificial intelligence technologies across its operations and fostering collaboration.
What it actually does
H.R. 2770 directs the National Oceanic and Atmospheric Administration (NOAA) to significantly expand its use of artificial intelligence (AI) for Earth system forecasting, including weather, water, and wildfire prediction. It mandates the development of comprehensive AI training datasets, the exploration of AI weather models, and the provision of technical assistance to external entities on AI model use. The bill also establishes a fire environment modeling program utilizing AI and encourages partnerships with private and academic sectors for innovation, while also addressing workforce expertise and data access.
Proponents argue
Supporters argue that leveraging AI will dramatically improve the accuracy, speed, and reliability of weather, water, and wildfire forecasts, leading to better preparedness, reduced economic losses, and enhanced public safety. They believe it will accelerate scientific understanding of Earth systems and foster innovation through public-private partnerships, positioning the U.S. as a leader in environmental forecasting.
Opponents contend
Opponents might raise concerns about the significant investment required for AI infrastructure and expertise, potential over-reliance on AI models without sufficient human oversight, and the challenges of ensuring data quality, privacy, and ethical AI development. They might also question the environmental impact of large-scale AI computing and the potential for job displacement among traditional forecasters.
The bill is relatively short and clearly structured, making it accessible for an informed reader to understand its core provisions within a reasonable timeframe.
Sec. 3
Earth System Forecasting and Information Delivery
This section directs NOAA to develop and maintain comprehensive training datasets for weather forecasting using relevant Earth system data within two years. It also authorizes NOAA to develop and test a global artificial intelligence weather model and explore AI for information dissemination. The section mandates continued support for traditional observational data, basic research, and numerical weather models, ensuring a balanced approach.
Supporters argue
Supporters argue that robust AI training datasets are fundamental for developing accurate AI weather models, and a global AI model would significantly enhance forecasting capabilities, leading to better preparedness and resilience.
Critics contend
Critics might argue that diverting resources to AI model development could detract from existing, proven numerical weather models, or that the environmental impact of AI computing needs more rigorous assessment before full-scale implementation.
Tradeoffs
Balancing investment in novel AI approaches with continued support for traditional, established numerical weather modeling and basic research.
Sec. 4
Advanced Artificial Intelligence Applications for Weather and Information Delivery
This section directs NOAA to explore advanced AI applications to enhance weather forecasts and information delivery. This includes improving data assimilation, using AI models to emulate numerical models for confidence assessment, and enhancing impact-based decision support for communities.
Sec. 5
Technical Assistance on Use of Artificial Intelligence Weather Models
NOAA is directed to inventory and assess non-Federal AI weather models, providing technical assistance and best practices for their use. This includes supporting forecasters, social scientists, and emergency managers in testing and evaluating AI models. The section also mandates the development of a common framework for assessing both numerical and AI weather models through reforecast analysis, in collaboration with other agencies and sectors.
Sec. 6
Fire Environment Modeling Program
Within one year, NOAA, in coordination with Interior, Agriculture, and Homeland Security, must develop a program using AI to analyze environmental data for wildfire prediction, detection, and forecasting of propagation and impacts. This includes warning at-risk communities and responders, integrating social science research, and forecasting smoke hazards. NOAA is also authorized to acquire data and curate a training dataset for this purpose.
Sec. 7
Partnerships for Transformational Innovation
This section directs NOAA to explore novel partnership structures with private and academic entities to foster transformative innovation in weather, water, wildfire, and space weather forecasting. It specifically encourages co-investment strategies, including non-Federal contributions to high-risk research, shared intellectual property rights, and other resource-sharing approaches.
Sec. 8
Federal Government Workforce Expertise
NOAA is directed to develop, recruit, and sustain a professional workforce skilled in AI applications for weather forecasting. This includes leveraging public-private partnerships to provide employees with training, experience, and long-term development opportunities in AI and weather forecasting.
Sec. 9
Public Data and Code Access with Safeguards
NOAA is authorized to make data and code developed under this Act publicly available at no cost and under an open license, with no restrictions on use. However, it also includes accommodations to protect national security, intellectual property, trade secrets, and NOAA's mission to protect lives and property, ensuring that sensitive information is not jeopardized.
The Under Secretary shall develop and disseminate best practices to minimize environmental impacts from the use of artificial intelligence to carry out this section.
Sec. 3(e)
Why it matters:This is standard legislative practice to include environmental considerations, but its brevity might suggest it's not a primary focus.
Case for: Proponents would argue that addressing the environmental footprint of large-scale AI computing (energy consumption, carbon emissions) is crucial for responsible technological development, especially for an agency focused on environmental science.
Case against: Some might argue that the immediate benefits of improved forecasting outweigh the environmental costs, or that this is a minor issue compared to the primary mission.
Estimated impact: Potentially significant long-term impact on the sustainability of federal AI initiatives, depending on the rigor of the best practices developed and adopted.
While generally promoting open data, this subsection allows NOAA to make accommodations to protect national security, intellectual property, trade secrets, and NOAA's mission to protect lives and property when releasing data or code.
Sec. 9(b)
Why it matters:These are critical safeguards, but they are often placed after the primary directive in legislative text to ensure the main intent (open access) is clear, while also addressing necessary practical and legal limitations.
Case for: Supporters would argue these accommodations are essential to prevent the misuse of sensitive data, protect proprietary information, and ensure that open access does not inadvertently compromise national security or critical operational functions.
Case against: Critics of broad exceptions might argue that they could be used to limit transparency or restrict access to data that should be public, potentially undermining the spirit of open science.
Estimated impact: Defines the practical limits of data openness, potentially affecting the scope and utility of publicly available datasets for researchers and commercial entities.