Uploaded November 2021 | Updated September 2026, 10 hours ago
This virtual workshop is a continuation of the NOAA series of workshops on “Leveraging AI in Environmental Sciences.” The third event continues the successes of previous workshops and encourages participation by scientists, program managers, and leaders from the public, academic and private sectors who work in AI and environmental sciences. The theme for this year’s workshop is “Transforming Weather, Climate Services, and Blue Economy with Artificial Intelligence.” This year’s workshop is led by the NOAA Center for Artificial Intelligence (NCAI), a program in the formulation stage.
Chair: Christina Kumler
Presentations:
13:00 – Tse-Chun Chen – "Learning UFS State-Dependent Systematic Errors from the Analysis Increments"
13:20 – John S Schreck – "Accelerating Mechanistic Simulation of Organic Chemistry in Weather and Climate Models with Machine Learning"
13:32 – Marko Orescanin – "Bayesian Deep Learning for Addressing Uncertainty - Precipitation Type Detection"
13:44 – Steve Penny – "Integrating AI/ML with Data Assimilation for data-driven state estimation"
13:56 – Matthew Brothers – "Random Forest Approach for Improving Non-Convective High Wind Forecasting Across Southeast Wyoming"
This virtual workshop is a continuation of the NOAA series of workshops on “Leveraging AI in Environmental Sciences.” The third event continues the successes of previous workshops and encourages participation by scientists, program managers, and leaders from the public, academic and private sectors who work in AI and environmental sciences. The theme for this year’s workshop is “Transforming Weather, Climate Services, and Blue Economy with Artificial Intelligence.” This year’s workshop is led by the NOAA Center for Artificial Intelligence (NCAI), a program in the formulation stage.
Chair: Christina Kumler
Presentations:
13:00 – Tse-Chun Chen – "Learning UFS State-Dependent Systematic Errors from the Analysis Increments"
13:20 – John S Schreck – "Accelerating Mechanistic Simulation of Organic Chemistry in Weather and Climate Models with Machine Learning"
13:32 – Marko Orescanin – "Bayesian Deep Learning for Addressing Uncertainty - Precipitation Type Detection"
13:44 – Steve Penny – "Integrating AI/ML with Data Assimilation for data-driven state estimation"
13:56 – Matthew Brothers – "Random Forest Approach for Improving Non-Convective High Wind Forecasting Across Southeast Wyoming"
