Modern snow-mapping models vs. The People

This past winter, we invited you to participate in SnowTweets and simply “measure your snow to help the planet.”

Richard_KellyRaySnowTweets is a citizen science project run by cryosphere researchers Richard Kelly (pictured far left) and Raymond Cabrera at the University of Waterloo (Canada), who sent us the following report to share with you! They’d love to hear back from you, so please feel free to post your reactions in the comments field, below.

Crowdsourcing for Weather and Climate Science: The Snowtweets Project
By Richard Kelly and Raymond Cabrera Interdisciplinary Centre on Climate Change, and Department of Geography and Environmental Management University of Waterloo
May 2011
Where in the world is the water?

Roughly 71% of the Earth’s surface is covered by water, most of which is contained in oceans, ice sheets, glaciers, lakes and rivers. Much of it is stored as seasonal snow; as much as 50% of the northern hemisphere’s land surface is covered during the year. (By springtime, the winter snow accumulation melts and finds its way into rivers that fill reservoirs or replenish the lakes and oceans.)

An accurate system for monitoring seasonal snow accumulation is important for several reasons, not the least is of which is to help policy makers in making sound decisions concerning the protection of our planet.

At the University of Waterloo, we cryosphere researchers have been studying the accuracy of global and regional snow cover extent and snow accumulation estimates which are based on observations from sensors such as NASA’s MODIS–or Moderate Resolution Imaging Spectroradiometer–a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites, and sophisticated models.  We also know that certain things can interfere with their estimation accuracy:

• Clouds, for example, can obscure snow from being observed by visible and infrared instruments aboard satellites.
• When publishing daily snow depth model estimates, both the Canadian Meteorological Centre (CMC) and the U.S. National Oceanic and Atmospheric Administration (NOAA) combine environmental variables known to control snow depth variation.
• And, while these models are available for global or national regions on a daily basis, the data are averaged over large areas typically from 1 km up to 25km wide.

To help us gather as much on-the-ground data as possible, we turned to citizen scientists and asked them (you) to monitor snow cover and snow depth by simply telling us how much snow had accumulated around them, and simply report it as depth.

Citizen scientists from around the world participated in this endeavor, which we dubbed Snowtweets because we accepted data both by using Twitter and a standard webform on

Snowtweets provided us with pinpoint measurements at specific times. We put this data right to use by comparing it to daily global and regional snow cover model estimates.

We put this data right to use by comparing it to global and regional snow cover model estimates.

How well did the citizen scientists’ data stack up against modern snow-mapping models? From the comparisons made to date, citizen scientists’ measurements, on average, match the snow cover model estimates! The differences were generally related to differences in the spatial resolution of the models compared with the pinpoint measurements of the Snowtweets data. These ground measurements, in part, verify the snow cover models, at least in regions where the snowtweets were reported. Snowtweets also complement these (daily or weekly) models by providing a sparse, yet near-real-time source of data and we are looking towards ways to incorporate them carefully once they are available.

We know we’ll need to see more frequent measurements from citizen scientists when we run this again, this winter. This will help us look for patterns and, again, compare the information against the models. With enough Snowtweets over a few seasons, we may be able to create a new snow depth product, blending and mapping satellite observations with ground measurements in real time! If you’d like to learn more about Snowtweets or our findings, please post your questions or comments in the comments field and we’ll respond as best we can. To sign up to participate in Snowtweets, go to to register or to for instructions on how to contribute via Twitter.

Thank you to all who participated. We look forward to continuing this research with you, this winter!

In the interim, consider helping researchers at the National Phenology Network as they try to solve the mystery of the changing migration patterns of the American Robin. Get started here.

Categories: Citizen Science, Climate & Weather

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About the Author

Darlene Cavalier

Darlene Cavalier

Darlene Cavalier is a Professor at Arizona State University's Center for Engagement and Training, part of the School for the Future of Innovation in Society. Cavalier is the founder of SciStarter. She is also the founder of Science Cheerleader, an organization of more than 300 current and former professional cheerleaders pursuing STEM careers, and a cofounder of ECAST: Expert and Citizen Assessment of Science and Technology, a network of universities, science centers, and think tanks that produces public deliberations to enhance science policymaking. She is a founding board member of the Citizen Science Association, a senior advisor at Discover Magazine, a member of the EPA's National Advisory Council for Environmental Policy and Technology, and was appointed to the National Academy of Sciences "Designing Citizen Science to Support Science Learning" committee. She is the author of The Science of Cheerleading and co-editor of The Rightful Place of Science: Citizen Science, published by Arizona State University. Darlene holds degrees from Temple University and the University of Pennsylvania and was a high school, college and NBA cheerleader. Darlene lives in Philadelphia with her husband and four children.