Measurement of the physical properties of the snowpack

Kinar, Nicholas; Pomeroy, John W.

doi:10.1002/2015rg000481

Cited by 190 publications

(218 citation statements)

References 443 publications

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“…This implies that punctual measurements may not be representative of the 10 km resolution data, even when comparing a simulation at the same elevation as the telenivometer. In addition, snow measurements always include biases from the different measuring devices (Kinar and Pomeroy, 2015). Thus, we focused on the temporal patterns of snowpack during the season.…”

Section: Validation Proceduresmentioning

confidence: 99%

Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

Alonso‐González

López‐Moreno

Gascoin

et al. 2018

Earth Syst. Sci. Data

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Abstract. We present snow observations and a validated daily gridded snowpack dataset that was simulated from downscaled reanalysis of data for the Iberian Peninsula. The Iberian Peninsula has long-lasting seasonal snowpacks in its different mountain ranges, and winter snowfall occurs in most of its area. However, there are only limited direct observations of snow depth (SD) and snow water equivalent (SWE), making it difficult to analyze snow dynamics and the spatiotemporal patterns of snowfall. We used meteorological data from downscaled reanalyses as input of a physically based snow energy balance model to simulate SWE and SD over the Iberian Peninsula from 1980 to 2014. More specifically, the ERA-Interim reanalysis was downscaled to 10 km × 10 km resolution using the Weather Research and Forecasting (WRF) model. The WRF outputs were used directly, or as input to other submodels, to obtain data needed to drive the Factorial Snow Model (FSM). We used lapse rate coefficients and hygrobarometric adjustments to simulate snow series at 100 m elevations bands for each 10 km × 10 km grid cell in the Iberian Peninsula. The snow series were validated using data from MODIS satellite sensor and ground observations. The overall simulated snow series accurately reproduced the interannual variability of snowpack and the spatial variability of snow accumulation and melting, even in very complex topographic terrains. Thus, the presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism, and risk management. The data presented here are freely available for download from Zenodo (https://doi.org/10.5281/zenodo.854618). This paper fully describes the work flow, data validation, uncertainty assessment, and possible applications and limitations of the database.

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Section: Validation Proceduresmentioning

confidence: 99%

Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

Alonso‐González

López‐Moreno

Gascoin

et al. 2018

Earth Syst. Sci. Data

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“…The snow survey equipment used in this study, i.e. the ESC30 snow coring tube (Farnes et al, 1980; dimensions also given in Kinar and Pomeroy, 2015), has a relatively large 30 cm 2 cutter area, which reportedly allows it to measure the snow density within 1 % of the true value (Farnes et al, 1983;Goodison et al, 1987). Ultimately this depends on ability to cut the snow sample and retain it in the tube, transfer cleanly to a sample bag, and accurately measure the mass.…”

Section: Uncertainty Assessmentmentioning

confidence: 99%

Field-scale water balance closure in seasonally frozen conditions

Xiong

Helgason

Ireson

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Hydrological water balance closure is a simple concept, yet in practice it is uncommon to measure every significant term independently in the field. Here we demonstrate the degree to which the field-scale water balance can be closed using only routine field observations in a seasonally frozen prairie pasture field site in Saskatchewan, Canada. Arrays of snow and soil moisture measurements were combined with a precipitation gauge and flux tower evapotranspiration estimates. We consider three hydrologically distinct periods: the snow accumulation period over the winter, the snowmelt period in spring, and the summer growing season. In each period, we attempt to quantify the residual between net precipitation (precipitation minus evaporation) and the change in field-scale storage (snow and soil moisture), while accounting for measurement uncertainties. When the residual is negligible, a simple 1-D water balance with no net drainage is adequate. When the residual is non-negligible, we must find additional processes to explain the result. We identify the hydrological fluxes which confound the 1-D water balance assumptions during different periods of the year, notably blowing snow and frozen soil moisture redistribution during the snow accumulation period, and snowmelt runoff and soil drainage during the melt period. Challenges associated with quantifying these processes, as well as uncertainties in the measurable quantities, caution against the common use of water balance residuals to estimate fluxes and constrain models in such a complex environment.

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“…Other passive radiation sensors are mounted above the surface and measure the attenuation of naturally emitted radiation from the soil as it passes through the snowpack and then relate this attenuation to SWE content Martin et al, 2008). Each of these instruments and techniques have advantages and disadvantages, which are not discussed here (see Kinar and Pomeroy, 2015b, for a more comprehensive description of snow measurement methods and related issues). Rather, this analysis assesses the use and accuracy of two instruments that were tested during the World Meteorological Organization (WMO Solid Precipitation Intercomparison Experiment (SPICE) (Nitu et al, 2012;Rasmussen et al, 2012), namely the Campbell Scientific CS725 and the Sommer Messtechnik SSG1000 snow scale.…”

Section: Introductionmentioning

confidence: 99%

An assessment of two automated snow water equivalent instruments during the WMO Solid Precipitation Intercomparison Experiment

et al. 2017

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Abstract. During the World Meteorological Organization (WMO) Solid Precipitation Intercomparison Experiment (SPICE), automated measurements of snow water equivalent (SWE) were made at the Sodankylä (Finland), Weissfluhjoch (Switzerland) and Caribou Creek (Canada) SPICE sites during the northern hemispheric winters of 2013/14 and 2014/15. Supplementary intercomparison measurements were made at Fortress Mountain (Kananaskis, Canada) during the 2013/14 winter. The objectives of this analysis are to compare automated SWE measurements with a reference, comment on their performance and, where possible, to make recommendations on how to best use the instruments and interpret their measurements. Sodankylä, Caribou Creek and Fortress Mountain hosted a Campbell Scientific CS725 passive gamma radiation SWE sensor. Sodankylä and Weissfluhjoch hosted a Sommer Messtechnik SSG1000 snow scale. The CS725 operating principle is based on measuring the attenuation of soil emitted gamma radiation by the snowpack and relating the attenuation to SWE. The SSG1000 measures the mass of the overlying snowpack directly by using a weighing platform and load cell. Manual SWE measurements were obtained at the intercomparison sites on a bi-weekly basis over the accumulation-ablation periods using bulk density samplers. These manual measurements are considered to be the reference for the intercomparison. Results from Sodankylä and Caribou Creek showed that the CS725 generally overestimates SWE as compared to manual measurements by roughly 30-35 % with correlations (r 2 ) as high as 0.99 for Sodankylä and 0.90 for Caribou Creek. The RMSE varied from 30 to 43 mm water equivalent (mm w.e.) and from 18 to 25 mm w.e. at Sodankylä and Caribou Creek, which had respective SWE maximums of approximately 200 and 120 mm w.e. The correlation at Fortress Mountain was 0.94 (RMSE of 48 mm w.e. with a maximum SWE of approximately 650 mm w.e.) with no systematic overestimation. The SSG1000 snow scale, having a different measurement principle, agreed quite closely with the manual measurements at Sodankylä and Weissfluhjoch throughout the periods when data were available (r 2 as high as 0.99 and RMSE from 8 to 24 mm w.e. at Sodankylä and from 56 to 59 mm w.e. at Weissfluhjoch, where maximum SWE was approximately 850 mm w.e.).

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Measurement of the physical properties of the snowpack

Cited by 190 publications

References 443 publications

Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

Field-scale water balance closure in seasonally frozen conditions

An assessment of two automated snow water equivalent instruments during the WMO Solid Precipitation Intercomparison Experiment

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