Work Description

Title: Supporting data for the Near-Infrared Emitting and Reflectance-Monitoring Dome Open Access Deposited

http://creativecommons.org/publicdomain/zero/1.0/
Attribute Value
Methodology
  • Figure 1 - Spectral snow albedo data was generated from SNICAR-Online (Flanner et al., 2007); Figure 3 - X-ray micro-computed tomography was done at the U.S. Army Corps of Engineers Engineer Research & Development Center’s Cold Regions Research & Engineering Lab. Scans and analysis were conducted using Bruker microCT instrumentation and software; Figure 4 - Snow bidirectional reflectance factors were measured using the Near-Infrared Emitting and Reflectance Monitoring Dome. Snow specific surface area was measured using Bruker microCT instrumentation and analysis software. Snow bidirectional reflectance factors were modeled for varying ice particle radii and shape habit using the Monte-Carlo method for photon transport; Figure 5 - Snow albedo data was generated from SNICAR-Online (Flanner et al., 2007) and from Monte-Carlo modeling.; Figure 6 - Calibration curves were fit to data using least squares regression analysis.; Figure 7 - Snow bidirectional reflectance factors were measured throughout the day on February 14, 2017 and converted to snow specific surface area using an exponential calibration function.
Description
  • This dataset contains all data used to generate the figures in The Cryosphere manuscript “Measuring Snow Specific Surface Area with 1.30 and 1.55 micro-meter Bidirectional Reflectance Factors,” by Adam Schneider, Mark Flanner, and Roger De Roo. These data support the theory, calibration, and application of the Near-Infrared Emitting and Reflectance Monitoring Dome (NERD), an instrument engineered to rapidly retrieve surface snow specific surface area in the field. Note that this deposit includes a microCT scan database for natural snowfall samples collected in New Hampshire during 2015-2017, comprised of raw tiff files as well as reconstructions, binarized reconstructions, and some 3D model reconstructions.

  • Running python scripts generally require that the following packages are installed: NumPy, SciPy, Matplotlib, Pandas, and ipdb (for debugging).
Creator
Depositor
  • amschne@umich.edu
Contact information
Discipline
Funding agency
  • National Science Foundation (NSF)
ORSP grant number
  • ARC-1253154
Keyword
Date coverage
  • 2016-02-01 to 2018-04-30
Citations to related material
Resource type
Last modified
  • 11/02/2018
Published
  • 07/12/2018
Language
DOI
License
To Cite this Work:
Adam Schneider, Mark Flanner (2018). Supporting data for the Near-Infrared Emitting and Reflectance-Monitoring Dome [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/Z23F4MVC

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