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Abstract Convection‐generated gravity waves (CGWs) transport momentum and energy, and this momentum is a dominant driver of global features of Earth's atmosphere's general circulation (e.g., the quasi‐biennial oscillation, the pole‐to‐pole mesospheric circulation). As CGWs are not generally resolved by global weather and climate models, their effects on the circulation need to be parameterized. However, quality observations of GWs are spatiotemporally sparse, limiting understanding and preventing constraints on parameterizations. Convection‐permitting or ‐resolving simulations do generate CGWs, but validation is not possible as these simulations cannot reproduce the CGW‐forcing convection at correct times, locations, and intensities. Here, realistic convective diabatic heating, learned from full‐physics convection‐permitting Weather Research and Forecasting simulations, is predicted from weather radar observations using neural networks and a previously developed look‐up table. These heating rates are then used to force an idealized GW‐resolving dynamical model. Simulated CGWs forced in this way closely resembled those observed by the Atmospheric InfraRed Sounder in the upper stratosphere. CGW drag in these validated simulations extends 100s of kilometers away from the convective sources, highlighting errors in current gravity wave drag parameterizations due to the use of the ubiquitous single‐column approximation. Such validatable simulations have significant potential to be used to further basic understanding of CGWs, improve their parameterizations physically, and provide more restrictive constraints on tuningwith confidence. 

For two days in February 2018, 17 cybersecurity ed- ucators and professionals from government and in- dustry met in a “hackathon” to refine existing draft multiple-choice test items, and to create new ones, for a Cybersecurity Concept Inventory (CCI) and Cyber- security Curriculum Assessment (CCA) being devel- oped as part of the Cybersecurity Assessment Tools (CATS) Project. We report on the results of the CATS Hackathon, discussing the methods we used to develop test items, highlighting the evolution of a sample test item through this process, and offer- ing suggestions to others who may wish to organize similar hackathons. Each test item embodies a scenario, question stem, and five answer choices. During the Hackathon, par- ticipants organized into teams to (1) Generate new scenarios and question stems, (2) Extend CCI items into CCA items, and generate new answer choices for new scenarios and stems, and (3) Review and refine draft CCA test items. The CATS Project provides rigorous evidence- based instruments for assessing and evaluating educa- tional practices; these instruments can help identify pedagogies and content that are effective in teach- ing cybersecurity. The CCI measures how well stu- dents understand basic concepts in cybersecurity— especially adversarial thinking—after a first course in the field. The CCA measures how well students understand core concepts after completing a full cy- bersecurity curriculum.