Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance

Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framewo...

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Published in:Remote sensing (Basel, Switzerland) Vol. 11; no. 4; p. 417
Main Authors: Yackel, John, Geldsetzer, Torsten, Mahmud, Mallik, Nandan, Vishnu, Howell, Stephen, Scharien, Randall, Lam, Hoi
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-02-2019
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Abstract Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framework for estimating relative snow thickness on first-year sea ice based on the variance in σ° from daily time series ASCAT and QuikSCAT scatterometer measurements during the late winter season prior to melt onset. We first describe our theoretical basis for this approach, including assumptions and conditions under which the method is ideally suited and then present observational evidence from four independent case studies to support our hypothesis. Results suggest that the approach can provide a relative measure of snow thickness prior to σ° detected melt onset at both Ku- and C-band frequencies. We observe that, during the late winter season, a thinner snow cover displays a larger variance in daily σ° compared to a thicker snow cover on first-year sea ice. This is because for a given increase in air temperature, a thinner snow cover manifests a larger increase in basal snow layer brine volume owing to its higher thermal conductivity, a larger increase in the dielectric constant and a larger increase in σ° at both Ku- and C bands. The approach does not apply when snow thickness distributions on first-year sea ice being compared are statistically similar, indicating that similar late winter σ° variances likely indicate regions of similar snow thickness.
AbstractList Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framework for estimating relative snow thickness on first-year sea ice based on the variance in σ° from daily time series ASCAT and QuikSCAT scatterometer measurements during the late winter season prior to melt onset. We first describe our theoretical basis for this approach, including assumptions and conditions under which the method is ideally suited and then present observational evidence from four independent case studies to support our hypothesis. Results suggest that the approach can provide a relative measure of snow thickness prior to σ° detected melt onset at both Ku- and C-band frequencies. We observe that, during the late winter season, a thinner snow cover displays a larger variance in daily σ° compared to a thicker snow cover on first-year sea ice. This is because for a given increase in air temperature, a thinner snow cover manifests a larger increase in basal snow layer brine volume owing to its higher thermal conductivity, a larger increase in the dielectric constant and a larger increase in σ° at both Ku- and C bands. The approach does not apply when snow thickness distributions on first-year sea ice being compared are statistically similar, indicating that similar late winter σ° variances likely indicate regions of similar snow thickness.
If such trends and increased variability persist then it is possible that we could expect enhanced variability or pronounced increases/decreases in wintertime snow accumulation in certain sectors of the Arctic Ocean [12,13,14], thereby influencing atmosphere-sea ice-ocean exchanges and sea ice growth and decay rates. [...]model-based projections of summer sea ice loss in these regions may be problematic due to unrepresentative parameterizations. High-resolution (5–100 m) synthetic aperture radar (SAR) data are available for developing such a methodology, however the temporal resolution and spatial coverage of SAR is typically inconsistent and incidence angle effects on σ° is an additional uncontrolled variable. [...]we employ spaceborne scatterometer data to determine σ° variance based on daily data, albeit at a lower, yet still improved, spatial resolution (as high as ~4.5 km). [...]the dielectric properties will also manifest a correspondingly larger (smaller) change and directly affect the amount of surface and/or volume scattering from the snow/ice system. [...]each of the case study sites has different absolute (i.e., baseline) wintertime σ°, as a function of surface roughness, scatterometer frequency and incidence angle.
Author Nandan, Vishnu
Geldsetzer, Torsten
Howell, Stephen
Lam, Hoi
Yackel, John
Mahmud, Mallik
Scharien, Randall
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  surname: Lam
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Snippet Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are...
If such trends and increased variability persist then it is possible that we could expect enhanced variability or pronounced increases/decreases in wintertime...
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SubjectTerms ASCAT
backscatter (σ°) variance
Backscattering
Decay rate
Dielectric properties
Electrical properties
first-year sea ice
Ice
Incidence angle
QuikSCAT
Remote sensing
Salinity
scatterometer
Sea ice
Seasons
Snow
Snow accumulation
snow thickness
Spatial discrimination
Spatial resolution
Summer
Surface roughness
Synthetic aperture radar
Temporal resolution
Variability
Variance
Winter
Title Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance
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