Snow Surface Roughness across Spatio-Temporal Scales

Autor: Steven R. Fassnacht, Kazuyoshi Suzuki, Jessica E. Sanow, Graham A. Sexstone, Anna K. D. Pfohl, Molly E. Tedesche, Bradley M. Simms, Eric S. Thomas
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Water, Vol 15, Iss 12, p 2196 (2023)
Druh dokumentu: article
ISSN: 2073-4441
DOI: 10.3390/w15122196
Popis: The snow surface is at the interface between the atmosphere and Earth. The surface of the snowpack changes due to its interaction with precipitation, wind, humidity, short- and long-wave radiation, underlying terrain characteristics, and land cover. These connections create a dynamic snow surface that impacts the energy and mass balance of the snowpack, blowing snow potential, and other snowpack processes. Despite this, the snow surface is generally considered a constant parameter in many Earth system models. Data from the National Aeronautics and Space Administration (NASA) Cold Land Processes Experiment (CLPX) collected in 2002 and 2003 across northern Colorado were used to investigate the spatial and temporal variability of snow surface roughness. The random roughness (RR) and fractal dimension (D) metrics used in this investigation are well correlated. However, roughness is not correlated across scales, computed here from snow roughness boards at a millimeter resolution and airborne lidar at a meter resolution. Process scale differences were found based on land cover at each of the two measurement scales, as appraised through measurements in the forest and alpine.
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