Snow Water Equivalent Measurements from Core Sampler Intercomparison Campaigns

Two field campaigns in Europe and North America collected data on snow depth, density, and water equivalent using 9 common snow core samplers. The study, led by Ignacio Lopez Moreno of the National Institute of Ecology, quantifies instrumental bias and observer-induced error in manual snow measurements. Results show uncertainty in bulk snow density estimation is about 5% for an individual instrument and close to 10% among different instruments.

Use Cases

• Quantifying measurement uncertainty in hydrological models based on snow water equivalent data.
• Calibrating automated snow sensors based on ground-truth comparisons from core sampler data.
• Assessing the impact of observer error and instrumental bias on climatological snowpack records.
• Designing field measurement protocols based on the quantified variability at plot and point scales.

Strengths

• Direct comparison of 9 different snow core samplers commonly used in Europe and North America.
• Results quantify instrumental bias as exceeding both natural variability and observer error.
• Two distinct field campaigns designed to separate natural snow variability from measurement error.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Ignacio Lopez Moreno, National Institute of Ecology

Collection Method

Two field campaigns with repeated manual measurements using 9 snow core samplers.

Geography

Europe and northern America