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Open AccessArticle

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

1
Department of Geography, University of Calgary, Calgary, AB T2N 1N4, Canada
2
Department of Geography, University of Victoria, Victoria, BC V8P 5C2, Canada
3
Climate Research Division, Environment and Climate Change Canada, Toronto, ON K1A 0H5, Canada
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(4), 417; https://doi.org/10.3390/rs11040417
Received: 21 January 2019 / Revised: 12 February 2019 / Accepted: 13 February 2019 / Published: 18 February 2019
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. View Full-Text
Keywords: snow thickness; first-year sea ice; scatterometer; backscatter (σ°) variance; ASCAT; QuikSCAT snow thickness; first-year sea ice; scatterometer; backscatter (σ°) variance; ASCAT; QuikSCAT
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MDPI and ACS Style

Yackel, J.; Geldsetzer, T.; Mahmud, M.; Nandan, V.; Howell, S.E.L.; Scharien, R.K.; Lam, H.M. Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance. Remote Sens. 2019, 11, 417.

AMA Style

Yackel J, Geldsetzer T, Mahmud M, Nandan V, Howell SEL, Scharien RK, Lam HM. Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance. Remote Sensing. 2019; 11(4):417.

Chicago/Turabian Style

Yackel, John; Geldsetzer, Torsten; Mahmud, Mallik; Nandan, Vishnu; Howell, Stephen E.L.; Scharien, Randall K.; Lam, Hoi M. 2019. "Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance" Remote Sens. 11, no. 4: 417.

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