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Webinar: Machine Learning Specific to Climate and Weather Applications
Thursday, 18 July 2019, 11:30
Thursday, July 18, 2019. 11:30AM. Webinar: Machine Learning Specific to Climate and Weather Applications. Imme Ebert-Uphoff, CIRA and Christina Kumler, CIRES. Sponsored by NOAA STAR. More information here.
Machine learning is becoming more and more accessible to the scientific community, with high performance computing capabilities, data collection, and increasing availability of free and highly efficient software packages. Part 1 of this talk discusses the great potential as well as some challenges of using machine learning for climate and weather applications. Challenges include the perceived lack of transparency and the potential for incorrect generalization of these methods. We then discuss strategies for overcoming these challenges, including i) leveraging physics in the AI approach and ii) utilizing visualization tools to help understand the reasoning of these algorithms. Part 2 then discusses machine learning projects that are currently ongoing within NOAA ESRL's Global System Division (GSD). GSD has several active projects applying different methods of ML to satellite data that will be covered briefly in this talk. One project in particular, a Regions of Interest (ROI) project that uses deep learning to detect cyclonic ROI from water vapor satellite data, will be highlighted at the end.