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Video: Building Python-Based Operational Systems for Prediction of Atmospheric Processes

In this video from the UCAR Software Engineering Assembly, Don Morton from ARSC presents: Building Python-Based Operational Systems for Prediction of Atmospheric Processes.

In the context of atmospheric models, operational systems are those that dependably provide important, time-critical forecasts for use in decision-support systems. They are characterized by the need for rapid data acquisition and model setup, reliable execution of the model, and post-processing activities that sometimes require delivery of model output timesteps as soon as they are completed. In addition to providing the tools for decision support, operational products from Alaska are also useful in a number of “downstream” research endeavors including road weather prediction systems, aviation icing products and greenhouse gas studies. With a decade of experience in provision of operational products, often for large areas at high resolutions, we have gained a fair amount of experience and wisdom, and still have much to learn. In this presentation we discuss some of the systems we have deployed, lessons learned, and the many exciting ambitions we have.”

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