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Whereas the evolution of snow cover across forested mountain watersheds is difficult to predict or model accurately, the presence or absence of snow cover is easily observable and these observations contribute to improved snow models. We engaged citizen scientists to collect observations of the timing of distributed snow disappearance over three snow seasons across the Pacific Northwest, U.S.A. . The primary goal of the project was to build a more spatially robust dataset documenting the influence of forest cover on the timing of snow disappearance, and public outreach was a secondary goal. Each year's effort utilized a different strategy, building on the lessons of the previous year. We began by soliciting our professional networks to contribute observations via electronic or paper forms, moved to a public outreach effort to collect geotagged photographs, and finally settled on close collaboration with an outdoor science school that was well-positioned to collect the needed data. Whereas the outreach efforts garnered abundant enthusiasm and publicity, the resulting datasets were sparse. In contrast, direct collaboration with an outdoor science school that was already sending students to make weekly snow observations proved fruitful in both data collection and educational outreach. From a data collection standpoint, the shift to an educational collaboration was successful because it essentially traded wide spatial coverage combined with sparse temporal coverage for dense temporal coverage at a single, but important location. From a public engagement standpoint, the partnership allowed for more intensive participation by more people and enhanced the science curriculum at the collaborating school. Abstract Citizen science; Science education Keywords ContextThe spatial pattern of snow cover across a forested mountain watershed is easily observed by outdoor enthusiasts who readily make note of snow disappearance patterns at a range of scales when they avoid skiing into tree well, change a hiking route after encountering a snow field, or capture a photograph of patchy snow across a valley. Whereas these patterns are obvious to an observer, reproducing such a pattern via a computer model is an ongoing research challenge [Essery et al., ArticleJournal of Science Communication 15(01)(2016)A01 1

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