Geometric methods in the study of the snow surface roughness
Date
2015
Authors
Fassnacht, Steven R., author
Oprea, Iuliana, author
Shipman, Patrick, author
Kirkpatrick, James, author
Borleske, George, author
Motta, Francis, author
Kamin, David, author
Colorado State University, publisher
Journal Title
Journal ISSN
Volume Title
Abstract
The snow surface is very dynamic, and the roughness of the snowpack surface varies spatially and temporally. The snow surface roughness influences the movement of air across the snow surface as well as the resulting transfers of energy, and is used to estimate the sensible and latent heat fluxes to and/or from the snow surface to the atmosphere. In the present work we used different metrics, including the random roughness, autocorrelation, and fractal dimension, geometric roughness length, curvature, and power spectrum density to characterize the roughness of a typical snow surface. The data for the surface come from airborne LIDAR measurements taken during from the NASA Cold Land Process Experiment in late March 2003 at the Fraser Alpine intensive study area. The surface elevation data were rotated to be parallel to the dominant wind direction and were interpolated to a 1-m resolution. We provide a comparison of methods and present their possible applicability for other datasets.
Description
2015 annual AGU hydrology days was held at Colorado State University on March 23 - March 25, 2015.
Includes bibliographical references.
Includes bibliographical references.