DURHAM â€”University of New Hampshire Ph.D. candidate Elizabeth Burakowski was awarded the 2012 Wiesnet Medal for Best Student Paper at the 69th Annual Meeting of the Eastern Snow Conference (ESC) held earlier this month in Claryville, N.Y.
She is the first UNH student to receive the award, which recognizes the best in current snow-related research being conducted by an up-and-coming student.
Burakowski's paper detailed a volunteer, citizen-science effort she leads to collect snow reflectance or "albedo" measurements throughout New Hampshire. The albedo measurements are part of her central doctoral research analyzing the relationships between land use and changes in regional climate. The ESC is a joint Canadian/U.S. organization with an international membership of scientists, engineers, snow surveyors, technicians, professors, and students working on issues related to snow and ice.
Says Burakowski, a student in the interdisciplinary Natural Resources and Earth System Science Ph.D. program, "A lot of people understand conceptually what albedo is but they don't know the term. I always use the white t-shirt analogy to explain it: if you want to stay cooler on a hot summer day you wear a white t-shirt, which reflects rather than absorbs and therefore has a high albedo." The citizen-science group making the measurements for Burakowski is part of the national Community Collaborative Rain, Hail, and Snow (CoCoRaHS) Network of volunteers that represents the largest provider of daily precipitation observations in the U.S. However, the NH contingent is the first CoCoRaHS albedo network in the US.
Burakowski's award-winning paper, "Putting the Capital "A" in CoCoRAHS: An Experimental Program to Measure Albedo," notes that despite record-breaking warm temperatures and below-average snowfall during the winter of 2012, the first pilot season of the effort successfully identified interesting relationships among albedo, snow depth, snow density, and land cover using the low-cost, volunteer approach to gathering reliable and accurate scientific data.
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