Date of Award
Master of Science (MS)
Dr. Wenge Ni-Meister
Dr. Sean Ahearn
Academic Program Adviser
Dr. Sean Ahearn
This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass three distinct geographic zones: the arctic permafrost, the Brooks Range which forms its southern boundary, and continental boreal forests and highlands beyond this. Findings indicate: 1) surface temperatures warming across all regions. 2) Albedo loss occurring earlier and faster. 3) vegetation growth occurring earlier and stronger. 4) A comparison of BSA and NDVI data shows an inverse relationship between the rate of snowmelt and the texture of a surface—influenced most heavily by vegetation cover. Overall, the snow albedo feedback mechanism of northern Alaska is in precipitous decline. This is reducing the process by which the terrestrial arctic contributes to the earth’s cooling.
Reckhaus, Lucas C., "Snow-Albedo Feedback in Northern Alaska: How Vegetation Influences Snowmelt" (2020). CUNY Academic Works.
Biophysics Commons, Climate Commons, Databases and Information Systems Commons, Geographic Information Sciences Commons, Graphics and Human Computer Interfaces Commons, Hydrology Commons, Longitudinal Data Analysis and Time Series Commons, Numerical Analysis and Scientific Computing Commons, Optics Commons, Physical and Environmental Geography Commons, Programming Languages and Compilers Commons, Remote Sensing Commons, Soil Science Commons