Improving Atmospheric River Forecasts Act

• Authority: United States Congress
• Parent authority: Federal government
• Jurisdiction: United States
• Collections: U.S. federal laws
• Most recent activity: Defunct
• Most recent activity date: 2025-01-03

Risk subdomain coverage

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.

• Governance failure
• Lack of capability or robustness

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

This document has minimal risk domain coverage, primarily addressing AI system safety and robustness (7.3) through its focus on improving forecast reliability. There is implicit mention of governance structures (6.5) related to federal AI implementation. The document does not substantially address discrimination, privacy, misinformation, malicious actors, human-computer interaction, or most socioeconomic risks.

Sector coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.

• Scientific Research & Development Services
• Public Administration (excl. National Security)

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.

• Information
• Professional & Technical Services
• Educational Services
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This Act primarily governs AI use in Public Administration (federal weather forecasting agencies) and Scientific Research and Development Services (atmospheric research). It also has implications for Professional and Technical Services through partnerships with consultants and research institutions.

Legislative Status

Hard Law

Legislative Status Summary

This is a Congressional Act with binding legal obligations on federal agencies, using mandatory language ('shall') throughout and establishing specific program requirements with oversight mechanisms.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Entities: United States Congress; Senate; House of Representatives
• Summary: The document is enacted by the Senate and House of Representatives of the United States of America in Congress assembled, establishing Congress as the proposing authority for this legislation.

Target

• Entity Types: AI_Governance_Actor, AI_Developer
• Entities: National Oceanic and Atmospheric Administration (NOAA); Under Secretary; Office of Oceanic and Atmospheric Research; weather enterprise in the United States; institutions of higher education
• Summary: The Act primarily targets NOAA (through the Under Secretary) to establish and implement the atmospheric river forecast improvement program. It also involves the weather enterprise and institutions of higher education as collaborative partners in developing AI-driven forecasting tools.

Enforcer

• Entity Types: AI_Governance_Actor
• Entities: Committee on Commerce, Science, and Transportation of the Senate; Committee on Science, Space, and Technology of the House of Representatives; Under Secretary (NOAA)
• Summary: Congressional committees provide oversight through mandatory plan submission and review. The Under Secretary has operational authority to implement and enforce program requirements within NOAA.

Monitor

• Entity Types: AI_Governance_Actor
• Entities: Committee on Commerce, Science, and Transportation of the Senate; Committee on Science, Space, and Technology of the House of Representatives; Under Secretary (NOAA); Office of Oceanic and Atmospheric Research
• Summary: Congressional committees monitor implementation through plan review and oversight. NOAA's Office of Oceanic and Atmospheric Research maintains atmospheric river observatories and ensures ongoing monitoring of program effectiveness.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

• Plan and Design
• Collect and Process Data
• Build and Use Model
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document covers multiple AI lifecycle stages with primary focus on Build and Use Model (developing AI/ML forecasting systems), Verify and Validate (establishing forecast skill metrics and testing), Deploy (operationalizing prototype systems), and Operate and Monitor (ongoing evaluation and improvement of forecasting capabilities). It addresses the complete lifecycle from planning through operational monitoring.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

• AI Models
• AI Systems
• Predictive AI
• Task-specific AI

Technical Scope Summary

The document explicitly mentions AI and machine learning methods for improving atmospheric river forecasts. It focuses on predictive AI systems for weather forecasting rather than generative AI. No specific compute thresholds, foundation models, or open-weight models are mentioned. The scope is task-specific AI for atmospheric river prediction and forecasting.