Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers. Issue 14 (24th May 2020)
- Record Type:
- Journal Article
- Title:
- Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers. Issue 14 (24th May 2020)
- Main Title:
- Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers
- Authors:
- López‐Moreno, J. Ignacio
Leppänen, Leena
Luks, Bartłomiej
Holko, Ladislav
Picard, Ghislain
Sanmiguel‐Vallelado, Alba
Alonso‐González, Esteban
Finger, David C.
Arslan, Ali N.
Gillemot, Katalin
Sensoy, Aynur
Sorman, Arda
Ertaş, M. Cansaran
Fassnacht, Steven R.
Fierz, Charles
Marty, Christoph - Abstract:
- Abstract: Manually collected snow data are often considered as ground truth for many applications such as climatological or hydrological studies. However, there are many sources of uncertainty that are not quantified in detail. For the determination of water equivalent of snow cover (SWE), different snow core samplers and scales are used, but they are all based on the same measurement principle. We conducted two field campaigns with 9 samplers commonly used in observational measurements and research in Europe and northern America to better quantify uncertainties when measuring depth, density and SWE with core samplers. During the first campaign, as a first approach to distinguish snow variability measured at the plot and at the point scale, repeated measurements were taken along two 20 m long snow pits. The results revealed a much higher variability of SWE at the plot scale (resulting from both natural variability and instrumental bias) compared to repeated measurements at the same spot (resulting mostly from error induced by observers or very small scale variability of snow depth). The exceptionally homogeneous snowpack found in the second campaign permitted to almost neglect the natural variability of the snowpack properties and focus on the separation between instrumental bias and error induced by observers. Reported uncertainties refer to a shallow, homogeneous tundra‐taiga snowpack less than 1 m deep (loose, mostly recrystallised snow and no wind impact). Under suchAbstract: Manually collected snow data are often considered as ground truth for many applications such as climatological or hydrological studies. However, there are many sources of uncertainty that are not quantified in detail. For the determination of water equivalent of snow cover (SWE), different snow core samplers and scales are used, but they are all based on the same measurement principle. We conducted two field campaigns with 9 samplers commonly used in observational measurements and research in Europe and northern America to better quantify uncertainties when measuring depth, density and SWE with core samplers. During the first campaign, as a first approach to distinguish snow variability measured at the plot and at the point scale, repeated measurements were taken along two 20 m long snow pits. The results revealed a much higher variability of SWE at the plot scale (resulting from both natural variability and instrumental bias) compared to repeated measurements at the same spot (resulting mostly from error induced by observers or very small scale variability of snow depth). The exceptionally homogeneous snowpack found in the second campaign permitted to almost neglect the natural variability of the snowpack properties and focus on the separation between instrumental bias and error induced by observers. Reported uncertainties refer to a shallow, homogeneous tundra‐taiga snowpack less than 1 m deep (loose, mostly recrystallised snow and no wind impact). Under such measurement conditions, the uncertainty in bulk snow density estimation is about 5% for an individual instrument and is close to 10% among different instruments. Results confirmed that instrumental bias exceeded both the natural variability and the error induced by observers, even in the case when observers were not familiar with a given snow core sampler. Abstract : Unique data set containing measurements from nine snow core samplers. Quantification of the uncertainty in measurements of density and snow water equivalent. Instrumental bias exceeds error induced by observers. … (more)
- Is Part Of:
- Hydrological processes. Volume 34:Issue 14(2020)
- Journal:
- Hydrological processes
- Issue:
- Volume 34:Issue 14(2020)
- Issue Display:
- Volume 34, Issue 14 (2020)
- Year:
- 2020
- Volume:
- 34
- Issue:
- 14
- Issue Sort Value:
- 2020-0034-0014-0000
- Page Start:
- 3120
- Page End:
- 3133
- Publication Date:
- 2020-05-24
- Subjects:
- field campaigns -- snow bulk density -- snow core sampler -- SWE -- uncertainty estimation -- water equivalent of snow cover
Hydrology -- Periodicals
Hydrology -- Research -- Periodicals
Hydrologic models -- Periodicals
Hydrological forecasting -- Periodicals
631.432 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/hyp.13785 ↗
- Languages:
- English
- ISSNs:
- 0885-6087
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4347.625600
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British Library HMNTS - ELD Digital store - Ingest File:
- 13350.xml