This case-based, interactive lesson teaches a process for forecasting clear air turbulence (CAT) and applies it to a case that occurred over the U.S. Information about the synoptic patterns that generate CAT and the products and indices used to identify it are woven into the case. Some of this information is presented in optional sections intended for those who are unfamiliar with the material or want a refresher. The lesson is aimed at national and international forecasters who make aviation forecasts.
February 2020: Updates to this lesson incorporate imagery from the current generation GOES-R geostationary satellites to show how GOES-R improvements can enhance the detection and analysis of atmospheric features associated with clear air turbulence.
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