Articles | Volume 11, issue 2
https://doi.org/10.5194/tc-11-857-2017
https://doi.org/10.5194/tc-11-857-2017
Research article
 | 
03 Apr 2017
Research article |  | 03 Apr 2017

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

Haruko M. Wainwright, Anna K. Liljedahl, Baptiste Dafflon, Craig Ulrich, John E. Peterson, Alessio Gusmeroli, and Susan S. Hubbard

Data sets

Low-altitude remote sensing dataset of DEM and RGB mosaic for AB corridor on July 13 2013 and L2 corridor on July 21 2013 B. Dafflon, S. Hubbard, C. Ulrich, and J. E. Peterson https://doi.org/10.5440/1177858

Snow Depth and Density at End-of-Winter for NGEE Areas A, B, C and D, Barrow, Alaska, 2012–2014 A. K. Liljedahl, U. Ulrich, S. Wullshelger, and L. Hinzman https://doi.org/10.5440/1236472

Active Layer and Moisture Measurements for Intensive Site 0 and 1, Barrow, Alask J. E. Peterson, B. Dafflon, C. Ulrich, and S. Hubbard https://doi.org/10.5440/1177857

Ground Penetrating Radar, Intensive Site1 AB Oct 2012–2014 J. E. Peterson, B. Dafflon, C. Ulrich, and S. Hubbard https://doi.org/10.5440/1171723

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Short summary
Snow has a profound impact on permafrost and ecosystem functioning in the Arctic tundra. This paper aims to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. In addition, we develop a Bayesian geostatistical method to integrate multiscale observational platforms (a snow probe, ground penetrating radar, unmanned aerial system and airborne lidar) for estimating snow depth in high resolution over a large area.