Snow Fork for Field Determination of the Density and Wetness Profiles of a Snow Pack

Sihvola, Ari; Tiuri, M.

doi:10.1109/tgrs.1986.289619

Cited by 152 publications

(124 citation statements)

References 3 publications

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“…The SnowFork instrument (Toikka Ltd., Engineering, Espoo, Finland) (Sihvola and Tiuri, 1986, Fig. 3f), measures the dielectricity of snow between two metal rods.…”

Section: Liquid Water Contentmentioning

confidence: 99%

“…3f), measures the dielectricity of snow between two metal rods. The resonant frequency, attenuation and 3 dB bandwith are recorded, and inserted into equations by Sihvola and Tiuri (1986), which are used to derive density and LWC through real and imaginary parts of permittivity.…”

Section: Liquid Water Contentmentioning

confidence: 99%

“…Output values (attenuation, 3 dB bandwidth and resonant frequency) are recorded from the screen, and subsequently the instrument is ready for the next measurement. It is also possible to get density and LWC directly from the SnowFork, but the equations it uses are less accurate than the full equations by Sihvola and Tiuri (1986).…”

Section: Liquid Water Contentmentioning

confidence: 99%

See 2 more Smart Citations

Sodankylä manual snow survey program

Leppänen

Kontu

Hannula

et al. 2016

Geosci. Instrum. Method. Data Syst.

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Abstract. The manual snow survey program of the Arctic Research Centre of the Finnish Meteorological Institute (FMI-ARC) consists of numerous observations of natural seasonal taiga snowpack in Sodankylä, northern Finland. The easily accessible measurement areas represent the typical forest and soil types in the boreal forest zone. Systematic snow measurements began in 1909 with snow depth (HS) and snow water equivalent (SWE). In 2006 the manual snow survey program expanded to cover snow macro-and microstructure from regular snow pits at several sites using both traditional and novel measurement techniques. Present-day snow pit measurements include observations of HS, SWE, temperature, density, stratigraphy, grain size, specific surface area (SSA) and liquid water content (LWC). Regular snow pit measurements are performed weekly during the snow season. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack. This snow survey program is an excellent base for the future research of snow properties.

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“…The SnowFork instrument (Toikka Ltd., Engineering, Espoo, Finland) (Sihvola and Tiuri, 1986, Fig. 3f), measures the dielectricity of snow between two metal rods.…”

Section: Liquid Water Contentmentioning

confidence: 99%

Section: Liquid Water Contentmentioning

confidence: 99%

See 1 more Smart Citation

Sodankylä manual snow survey program

Leppänen

Kontu

Hannula

et al. 2016

Geosci. Instrum. Method. Data Syst.

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“…The 310-km-long transect was sampled using a snow fork (Sihvola and Tiuri, 1986). In the snow pits close to Basen nunatak, the vertical snow density profiles were measured with a steel cylinder, pushed horizontally in the snow pit wall.…”

Section: Methodsmentioning

confidence: 99%

Spatial and temporal variability in summer snow pack in Dronning Maud Land, Antarctica

et al. 2011

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Abstract.To quantify the spatial and temporal variability in the snow pack, field measurements were carried out during four summers in Dronning Maud Land, Antarctica. Data from a 310-km-long transect revealed the largest horizontal gradients in snow density, temperature, and hardness in the escarpment region. On the local scale, day-to-day temporal variability dominated the standard deviation of snow temperature, while the diurnal cycle was of second significance, and horizontal variability on the scale of 0.4 to 10 m was least important. In the uppermost 0.2 m, the snow temperature was correlated with the air temperature over the previous 6-12 h, whereas at the depths of 0.3 to 0.5 m the most important time scale was 3 days. Cloud cover and radiative fluxes affected the snow temperature in the uppermost 0.30 m and the snow density in the uppermost 0.10 m. Both on the intra-pit and transect scales, the ratio of horizontal to temporal variability increased with depth. The horizontal standard deviation of snow density increased rapidly between the scales of 0.4 and 2 m, and more gradually from 10 to 100 m. Inter-annual variations in snow temperature and density were due to interannual differences in air temperature and the timing of the precipitation events.

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“…Observations of dielectric permittivity were made using a Finnish snow fork (Sihvola and Tiuri, 1986) at 50 cm horizontal and 5 cm vertical spacing. The snow fork was inserted horizontally into the snowpack and each measurement integrated over a volume ~± 2 cm above and below the fork.…”

Section: Methodsmentioning

confidence: 99%

Observations of snowpack properties to evaluate ground-based microwave remote sensing

Rutter¹,

Marshall²,

Tape³

et al. 2010

Role of Hydrology in Managing Consequences of a Changing Global Environment

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Active microwave radar has been shown to have great potential for estimating snow water equivalent (SWE) globally from space. To help evaluate optimal active microwave sensor configurations to observe SWE, we evaluated ground-based Frequency Modulated Continuous Wave (FMCW) radar (12-18 GHz, cross-polarisation) using very high resolution in-situ observations of snowpack layering, dielectric permittivity and density over a 10 m snow trench on Toolik Lake, Alaska. Results showed that the thicknesses of layers within the 10 m trench were highly variable over short distances (< 1 m), even where total snow depth changed very little. Layer boundaries observed using NIR photography identified all bands of high radar backscatter. Although additional observations of density and dielectric permittivity helped to explain the causes of backscatter, not all snowpack properties which cause backscatter were coincident with strong vertical changes in density or permittivity. Further observations of high surface roughness in layer boundaries explained some areas of weak backscatter, nonetheless it was shown that a suite of coincident observations, rather than a single technique in isolation, were required to adequately explain the variability of backscatter and the influence of snowpack properties upon it.

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Snow Fork for Field Determination of the Density and Wetness Profiles of a Snow Pack

Cited by 152 publications

References 3 publications

Sodankylä manual snow survey program

Sodankylä manual snow survey program

Spatial and temporal variability in summer snow pack in Dronning Maud Land, Antarctica

Observations of snowpack properties to evaluate ground-based microwave remote sensing

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