Fassnacht et al. (2026) Snow Surface Roughness at a Ski Resort During Melt

Identification

• Journal: Glacies
• Year: 2026
• Date: 2026-03-05
• Authors: S. R. Fassnacht, Javier Herrero, Jessica E. Sanow
• DOI: 10.3390/glacies3010004

Research Groups

• ESS-Watershed Science, Colorado State University, Fort Collins, CO, USA
• Cooperative Institute for Research into the Atmosphere, Colorado State University, Fort Collins, CO, USA
• Instituto Geológico y Minero de España, Ronda, Granada, Spain
• Modelling Nature, Department of Ecology, University of Granada, Beiro, Granada, Spain

Short Summary

This study quantifies the variability of snow surface roughness at a ski resort during melt, revealing substantial differences between natural (sun cups, dust) and groomed snow surfaces. These variations lead to an order-of-magnitude difference in the geometric-based aerodynamic roughness length (z0) and subsequent modeled snowpack sublimation, highlighting the inadequacy of assuming a constant z0.

Objective

• To investigate how snow surface roughness varies at a ski area.
• To determine the implications of this spatial variation in snow surface roughness on snowpack sublimation modeling.

Study Configuration

• Spatial Scale: Field site at Sierra Nevada Ski Resort, Spain (2700 m elevation). Measurements covered areas of 0.6 m (roughness boards) and 0.8 m × 1.6 m (iPad scans). The broader study area was 100 m wide by 200 m high.
• Temporal Scale: Data collected on 19 April 2024. Meteorological data were collected for four hours (10:19 to 14:32 UTC) on the same day.

Methodology and Data

• Models used:
  • Lettau [48] method for geometric-based aerodynamic roughness length (z0).
  • Bulk transfer equation [53] for estimating snowpack sublimation.
• Data sources:
  • Field Measurements:
    • Snow roughness boards: 2-dimensional profiles at 0.2 mm resolution, capturing fine details.
    • iPad Pro (4th generation) surface scanning: 3-dimensional surface geometry at 1 cm resolution.
    • Meteorological data: Vaisala WXT510 Weather Transmitter (wind speed at 0.7 m, air temperature, relative humidity at 0.6 m), Campbell Scientific 109 Temperature Probe (snow surface temperature), recorded by a Campbell Scientific CR200 datalogger.
  • Image Processing:
    • Samsung Galaxy A53 for roughness board photographs.
    • 3-D Scanner App (version 2.4.3) for iPad scans.
    • CloudCompare for point cloud clipping and outlier removal.
    • Golden SURFER program for kriging interpolation to 1 cm resolution.
  • Roughness Metrics: Random Roughness (RR), Scale Break (SB), and Fractal Dimension (D) derived from variogram analysis.

Main Results

• Four distinct snow surface forms were identified and measured: natural snow, natural snow with dust, natural snow with sun cups, and groomed snow (tracked and between tracks).
• Roughness metrics (Random Roughness, Scale Break, Fractal Dimension) showed substantial differences between these surface types. Sun cups exhibited the largest roughness and were most organized (lowest Fractal Dimension), while the groomed flat surface between tracks was the smoothest and most random.
• Both 2-D roughness boards (0.2 mm resolution) and 3-D iPad scans (1 cm resolution) yielded consistent roughness estimates for distinct surfaces, though the iPad struggled to resolve features on very flat surfaces.
• Geometric-based aerodynamic roughness length (z0) varied by an order of magnitude across the different surfaces, ranging from 0.35 mm for groomed surfaces to 9.5 mm for sun-cupped surfaces.
• This order-of-magnitude variability in z0 resulted in an order-of-magnitude difference in modeled cumulative snowpack sublimation, demonstrating the critical impact of surface roughness on energy balance.

Contributions

• Provides a novel, systematic quantification and comparison of snow surface roughness across diverse conditions (natural, dust-covered, sun-cupped, and groomed) observed at a ski resort during melt.
• Demonstrates that snow surface roughness is highly dynamic and spatially variable, challenging the common assumption of a constant aerodynamic roughness length (z0) in snowpack models.
• Quantifies the significant impact of this roughness variability on modeled sublimation, showing an order-of-magnitude difference, which has direct implications for snow water equivalent and water resource management.
• Offers insights for improved snow management strategies at ski areas and contributes to a better understanding of snow-atmosphere interactions in natural snowpacks.

Funding

• QUALIFICA Project (Modeling Nature/QUAL21-11), funded by Granada-CETURSA Sierra Nevada S.A. (UGR OTRI-6429).
• Regional Ministry of University, Research and Innovation of the Junta de Andalucía.
• Fulbright Global Scholar program (supported Steven R. Fassnacht).

Citation

@article{Fassnacht2026Snow,
  author = {Fassnacht, S. R. and Herrero, Javier and Sanow, Jessica E.},
  title = {Snow Surface Roughness at a Ski Resort During Melt},
  journal = {Glacies},
  year = {2026},
  doi = {10.3390/glacies3010004},
  url = {https://doi.org/10.3390/glacies3010004}
}