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Hosted by the AMS Board on Environment and Health (BEH) and the AMS Board on Higher Education (BHE), this short course will be a hands-on tutorial of the AI tools for weather data visualization, analysis, and environmental health applications. Specifically, the course participants will learn how to use the AI and big data tools based on the iCHARM (intelligent Cyber Hub for Analytics, Research, and Monitoring) ecosystem, such as https://icharm.app. iCHARM puts massive weather observation and model datasets at the fingertips of ALL users, ranging from businesspeople to engineers, from college students to scientists, and from schoolchildren to seniors. iCHARM can make data analysis and visualization not only without computer programming, but also many times faster than the conventional approaches. As an efficient teaching tool, iCHARM can help democratize both the weather data usage and the atmospheric/oceanic sciences.
Registration rates: (Annual Meeting attendance is not required to attend a short course. See how to register here.)
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The course participants will learn how to use the iCHARM tools to quickly access the massive amount of NOAA data, particularly more than 40 PB data in the cloud. They will master skills to not only visualize maps, time series, atmospheric and oceanic flows, but also perform statistical data analysis, such as computing anomalies, standard deviations, quantiles, seasonality, regional data statistics (max, min, and average), and spectral analysis for time series (trend, histograms, periodograms, spectrograms, and auto-correlation functions). They will be enabled to explore both the observed data from satellite remote sensing, weather stations, radars, radiosounds, Argo, and aircrafts, and the model output, such as NCEP’s atmospheric and oceanic reanalysis data. Participants will learn how to use proper data and tools to monitor significant weather events, such as the 2026/27 super El Niño, extreme precipitations, and hurricanes. The course will also demonstrate how to run different kinds of AI weather forecasting models, such as GraphCast for global forecasts, and CorrDiff for regional forecasts, using the free GPUs via the National Research Platform (NRP). This is a hands-on tutorial. Participants are required to bring their laptop computers to the class, and closely follow the instructors to visualize and analyze real weather and health data. Participants are encouraged to bring up the data science problems for their own research or teaching and try to solve their problems in the class. As an example of environmental health application, participants will apply iCHARMhealth in designing a participatory research project by focusing on framing the environmental-health issue specific to their community. Participants will be able to apply community science and participatory approaches to pressing issues in the environmental-health nexus, such as extreme heat, water quality degradation, air pollution, flooding, and more. To focus on actionable solutions and implementation science, each participant will have a chance to develop a brief, structured project scope outline of a community issue relevant to their lives.
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If you have questions regarding the course, please contact Sam Shen or Alice Lau.
NOAA
San Diego State University