Physical and Chemical Properties of Seasonal Snow and the Impacts on Albedo in New Hampshire, USA

Monday, 15 December 2014
Alden Claire Adolph1, Mary R Albert1, Jacqueline Amante2 and Jack E Dibb2, (1)Dartmouth College, Thayer School of Engineering, Hanover, NH, United States, (2)Univ New Hampshire, Durham, NH, United States
Snow albedo is critical to surface energy budgets and thus to the timing of mid-winter and vernal melt events in seasonal snow packs. Timing of these melt events is important in predicting flooding, understanding plant and animal phenology, and the availability of winter recreational activity. The state of New Hampshire experiences large spatial and temporal variability in snow albedo as a result of differences in meteorological conditions, physical snow structure, and chemical impurities in the snow, particularly highly absorptive black carbon (BC) and dust particles. This work focuses on the winters of 2012-2013 and 2013-2014, comparing three intensive study sites. Data collected at these sites include sub-hourly meteorological data, near daily measurements of snow depth, snow density, surface IR temperature, specific surface area (SSA) from contact spectroscopy, and spectrally resolved snow albedo using an ASD FieldSpec4 throughout the winter season. Additionally, snow samples were analyzed for black carbon content and other chemical impurities including Cl-, NO3-, NH4 , K , Na , Mg2+ , Ca2+ and SO42-. For each storm event at the three intensive sites, moisture sources and paths were determined using HYPLIT back trajectory modeling to determine potential sources of black carbon and other impurities in the snow. Storms with terrestrial-based paths across the US Midwest and Canada resulted in higher BC content than storms with ocean-based paths and sources. In addition to the variable storm path between sites and between years, the second year of study was on average 2.5°C colder than the first year, impacting duration of snow cover at each site and the SSA of surface snow which is sensitive to frequency of snow events and relies on cold temperatures to reduce grain metamorphism. Combining an understanding of storm frequency and path with physical and chemical attributes of the snow allows us to investigate snow albedo sensitivities with implications for understanding the impacts of future climate change on snow albedo in the Northeastern US.