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Understanding which cognitive factors facilitate meteorology skills is important for meteorology training and education. This study investigated aspects of cognition important to successful completion of meteorology tasks typically provided to student meteorologists. With a sample of 81 participants—spanning the range of experience from undergraduate students to professional meteorologists—we administered two spatial thinking tests, a visuospatial working memory test, a concept inventory, and an experience questionnaire. We compared the resulting scores to performance on a series of novice-level meteorology tasks. An analysis of the data suggests that meteorology knowledge along with disembedding skill (the ability to observe and recognize patterns among nonessential information) positively predicts performance on the meteorological tasks. The relationship among meteorology knowledge, disembedding skill, and performance on the meteorology tasks indicates that disembedding is an important predictor of success at both low and high levels of meteorology knowledge. Thus, our results suggest that individuals with heightened ability to identify patterns embedded in distracting background displays may be at an advantage for completing meteorology tasks of the type that we provided.

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Disembedding, or recognizing patterns in a distracting background, is a spatial thinking skill that is particularly relevant to the interpretation of meteorological surface and upper-air maps. Difficulty “seeing” patterns such as cyclonic flow, thermal ridges, or pressure gradients can make weather analysis challenging for students. In this qualitative case study, we characterize how three undergraduate meteorology students with varying disembedding skill complete a series of meteorological tasks. Videos and transcribed verbal data collected during the task, as well as participant products, were analyzed for instances of disembedding and rule-based reasoning. Results demonstrate that the student with greater disembedding skill relied on observing patterns embedded in meteorological maps in conjunction with rule-based reasoning, whereas the two students with lower disembedding skill preferred generalized application of rules. These results can aid meteorology instructors in recognizing students who struggle with disembedding data and patterns and inform the development of instructional interventions in undergraduate meteorology classrooms.