The Ground Effect: Snow, Ice, and Tundra Albedo in the Arctic

 
Poster PDF

Authors

Anika Pinzner — University of Alaska, Fairbanks *
Matthew Sturm — University of Alaska Fairbanks
Jennifer S. Delamere — University of Alaska Fairbanks
Don Perovich — Dartmouth College
Phillip Raymond Wilson — University of Alaska Fairbanks
Emalia Camryn Mayo — University of Alaska, Fairbanks
Trevor Grams — University of Alaska, Fairbanks
* presenting author

Category

ARM field campaigns – Results from recent ARM field campaigns

Description

Jennifer Delamere taking notes about snow conditions at the ARM field site during the 2019 field campaign

In winter, four basic landscapes can be found in the Alaskan and Canadian Arctic: flat polygonal tundra, rolling tundra with steeper slopes, frozen lakes, and sea ice -- all of which are covered by snow. While some differences in the early snow cover develop on these landscapes due to dates of ice freezing or microtopography, by the snow melt, progression evolves differently even in similar snow covers. These differences in melt trajectories have important ramifications for albedo and the surface energy balance. We examined the causes of these variations by monitoring the snow melt progression on two tundra sites and one site on sea ice during the winter and spring of 2019.  

 

Starting in Aril 2019 and continuing through mid-June 2019, we measured daily snow depth, stratigraphy, density, superimposed ice, and ponded water at three locations near Utqiaġvik, Alaska. Our campaign was called SALVO (Snow Albedo eVOlution). The first tundra site was located on a mosaic of ice-wedge polygons, while the second tundra site covered a slope divided by small drainage channels. The third measurement transect was set up on the ice of a coastal lagoon. Using structure-from-motion photogrammetry, we produced sequential orthomosaics at these sites, as well as digital elevation models that allow mapping of meltwater routing. Using a portable radiometer (ASD) we measured the spectral albedo of the various ground surfaces at the sites: e.g., glaze crusts on snow, granulated sea ice, superimposed ice over water, low brushes shading coarse snow grain clusters on tundra, ponded water with floating vegetation, or snow-ice at the edge of melt ponds.

 

The melt of 2019 was slow and protracted, dominated by shortwave solar radiation rather than sensible and latent heat conduction. During the melt, there was a steady and continuous loss of energy due to outgoing longwave radiation (-60 W/m2) that led to considerable refreezing of meltwater in and beneath the snow each night (super-imposed ice). However, this refreezing manifested quite differently at the three sites because of differences in local slope and the nature of the meltwater run-off systems, as well as initial snow conditions. Steeper slopes led to more rapid drainage and less freeze-back. Consequently, area-averaged albedo trajectories evinced quite different time-evolutions. Given that the albedo of snow-covered tundra can be as high as 0.9, while tundra (wet or dry) has an albedo value close to 0.1, these meltwater-driven timing differences, averaged over several weeks’ duration, had a marked impact on the local energy balance. 

Lead PI

Matthew Sturm — University of Alaska Fairbanks