NOAA Center for Satellite Applications and Research banner
Intranet • Contact • Skip navigation
National Oceanographic & Atmospheric Administration website NOAA Center for Satellite Applications and Research website

AI Workshop Brings Together Environmental Science and AI / ML Expert Communities

AI Workshop Poster sessions
Workshop Group Photo - 23 April 2019

AI Workshop - by the numbers - click to enlarge9 May 2019 - NOAA hosted the 1st Workshop on Leveraging AI in the Exploitation of Satellite Earth Observations & Numerical Weather Prediction at the NOAA Center for Weather and Climate Prediction in College Park, MD, from 23-25 April 2019. The objective of the workshop was to facilitate exchange of knowledge between experts and thought leaders in remote sensing / earth observation / NWP modeling science and artificial intelligence, to explore how to use AI to address NOAA's biggest challenges in effectively using the explosion of data from new Global Observing System sources.

The workshop was both well-attended and enthusiastically received by attendees, with over 440 registered participants and dozens of presentations and posters over the course of the workshop. Attendees represented a diverse array of government, private sector, and academic stakeholders – NOAA, NASA, Oak Ridge National Laboratory; Google, Microsoft, NVIDIA, IBM; Harvard, Johns Hopkins, UCAR, and Penn State, among numerous others. Keynote addresses by Dr. Neil Jacobs (Assistant Secretary of Commerce for Environmental Observation and Prediction, performing the duties of Under Secretary of Commerce for Oceans and Atmosphere), Dr. Stephen Volz (Assistant Administrator for NESDIS), Dr. Louis Uccellini (Assistant Administrator for NWS) and Dr. Ed Kearns (NOAA Chief Data Officer) established the framework of NOAA's priorities and plans on how AI and machine learning may be exploited to address those priorities.

Workshop Highlights and Markers for Success

Evidence was presented during the workshop that AI has a significant potential for being a 'positively disruptive' technology to support all of NOAA's missions. Workshop participants interacted throughout the week, with strong attendance at sessions and tutorials and during panel discussions. According to Sid Boukabara, chair of the workshop's science organizing committee, the most important outcome of the workshop was to catalyze sustained partnerships between NOAA science practitioners and the AI / ML expert community. This is expected to generate significant leveraging of expertise which will in turn accelerate the infusion of AI technology into the NOAA systems. Lively conversations were evident during coffee and lunch breaks and poster sessions, as presenters and participants shared their work and explored possible ways to exploit AI / ML tools and solutions in remote sensing and NWP. Workshop organizers look forward to seeing this engagement blossom in the form of collaborative partnerships between government / academic / private environmental scientists and AI/ML experts.

Next Steps

Efforts are underway to ramp up a NOAA AI Working Group. NOAA leadership expressed support and enthusiasm for AI and the workshop, and the workshop's outcomes are expected to contribute to establishing the first NOAA AI strategy. In addition, the science organizing committee will be working towards putting together a special issue of peer-reviewed articles to summarize the scientific findings of the workshop, including an overview paper that will summarize the main takeaways and conclusions of the workshop.

• Workshop website


Data, algorithms, and images presented on STAR websites are intended for experimental use only and are not supported on an operational basis.  More information

Level A conformance icon, W3C-WAI Web Content Accessibility Guidelines 1.0 and Valid HTML 4.01 IconDept. of Commerce  •  NOAA  •  NESDIS  •  Website Owner: STAR  •  Contact webmaster  •  Last revised: May 10, 2019
Privacy Policy  •  Disclaimers  •  Information Quality  •  Accessibility  •  Search  •  Customer Survey
icon: valid HTML 4.01 transitional. Level A conformance icon, W3C-WAI Web Content Accessibility Guidelines 1.0