NOAA's emerging conduit for artificial intelligence (AI) and machine learning (ML) for mission science initiatives
We're exploring the needs and capabilities of the NOAA community. We want to spark conversations, provide space for networking, and encourage information sharing about AI/ML within NOAA and its scientific communities. We welcome your participation in the evolution of NCAI and the development of our Community of Practice.
News and events
This seminar series features cutting-edge research from NOAA scientists and NOAA-supported investigators, showcasing how AI and machine learning tools are transforming the way we study complex Earth systems.
- April 4, 1-2pm ET: Aerosols and Air Quality
Discover how AI and machine learning are transforming aerosol and air quality research. Jianhao Zhang (NOAA Chemical Sciences Laboratory), Andy May (The Ohio State University), and Hanyang Li (San Diego State University) will share advances in understanding black carbon, aerosol-cloud interactions, and the impacts of emission regulations—plus a look at their upcoming work.
- April 11, 1-2pm ET: Precipitation
Learn from scientists who are using AI in their research to study precipitation forecasting on a Seasonal-to-Subseasonal scale. Andrew Rosenow (Cooperative Institute for Severe and High-Impact Weather Research and Operations/NOAA National Severe Storms Laboratory), Peter Veals (University of Utah), and Tiantian Yang (University of Oklahoma) will share their recent and upcoming work on snow, rain, and watershed hydrology.
- April 18, 1-2pm ET: Wildfires
Scientists Siyuan Wang (Cooperative Institute for Research in Environmental Sciences, NOAA Chemical Sciences Laboratory) and Laura Thapa (Colorado State University) will discuss their experience using machine learning techniques in wildfire research.
Hosted by the NOAA Climate Program Office (CPO) and NOAA Center for Artificial Intelligence (NCAI).
This event is part of the annual NOAA AI workshop series to foster a community around AI research and applications that are relevant to NOAA missions. In 2025, NCAI will host a series of virtual and hybrid public workshops focused on GenAI development for environmental science applications. This year’s NOAA AI Workshop will host virtual events in March and June. Each event will focus on different aspects of GenAI. The series concludes with a 2-day hybrid event with panels and sessions spanning topics around GenAI for environmental sciences.
March 3, 2025: Generative Modeling for Earth and Space Sciences- June 9, 2025 (11:00-16:30 ET, virtual): Generative AI for Information Services (register)
- September 16-17, 2025 (Boulder, Colorado and virtual - with an optional Sept 15 hands-on tutorial): Generative AI Applications in Environmental Sciences
Navigating the Depths: Advancing Hierarchical Classification of Ocean Life
Join the FathomNet Kaggle Competition to show how to develop a model that can accurately classify varying taxonomic ranks. Developing these solutions for ocean research will enable scientists to process and explore ocean data more efficiently. Hierarchical classification—architectures that structure data to capture relationships across taxonomic ranks (e.g., from broad categories like families to specific species)—can significantly improve classification accuracy, as demonstrated by recent advances in machine learning.
Competition will close on May 26, 2025.
The AI Weather Quest, organised by the European Centre for Medium-Range Weather Forecasts (ECMWF), is an ambitious international competition designed to harness AI/ML in advancing weather forecasting. It challenges participants to produce and submit sub-seasonal weather forecasts – covering the critical weeks between medium-range and seasonal predictions – using AI/ML models. The competition starts in March 2025 and will unfold in two phases:
- Initial Training Phase (March–August 2025): Participants will refine their models and familiarise themselves with the competition’s submission and evaluation process in a non-competitive environment.
- Competition Phase (August 2025–September 2026): Participants will submit weekly, real-time forecasts over four 13-week periods. They will be evaluated based on the Ranked Probability Skill Score (RPSS), comparing their forecasts to established benchmarks.
AI at NOAA: Highlighting Innovation in Practice
Artificial intelligence (AI) can help scientists better understand the environment and its management. NOAA has a long history of using AI in weather forecasting, climate modeling, and environmental monitoring and has established the NOAA Center for Artificial Intelligence to support new and ongoing projects that span from the bottom of the ocean to the outer atmosphere. Learn how we use AI across NOAA in this ESRI StoryMap offsite link, or scroll through it below.
1133
Number of CoP Members
Communities of Practice members can focus on sharing best practices and creating new knowledge to advance AI and machine learning.
20
Industry Sectors Supported
NOAA data directly support every sector in the North American Industry Classification System (NAICS) of the U.S. Census Bureau.
NOAA AI-related news
