Compressive Strength and Microstructure of Artificial Depth Hoar Snow Layers

92 artificially grown weak snow samples provide compressive strength measurements and CT-derived microstructural data. The dataset accompanies a publication in the Journal of Glaciology and is hosted by ENVIDAT. It was last updated in 2025.

Use Cases

• Model compressive strength from CT-derived features like specific surface area and correlation lengths.
• Analyze the relationship between snow density and anisotropy for material property prediction.
• Assess parent sample variability using the provided CT data for quality control in experimental studies.
• Study temporal evolution of artificial weak layers using the time-series CT data.
• Validate snowpack models with reference CT data from the RHOSSA and MOSAiC campaigns.

Strengths

• Contains data for 92 distinct, artificially grown snow samples.
• Provides multiple CT-derived microstructural features per sample, including density and specific surface area.
• Includes reference data from established field campaigns (RHOSSA and MOSAiC).

Limitations

• Sample size of 92 may be insufficient for complex multivariate modeling without augmentation.
• Data is limited to artificially grown samples, which may not fully represent natural snowpack conditions.
• Unknown row count and file formats for the CT image datasets.

Provenance

Source

ENVIDAT, accompanying a Journal of Glaciology publication.

Collection Method

Experimental measurements on artificially grown snow samples, with CT scanning for microstructure.

Time Range

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Freshness

Last updated in 2025.

Geography

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