Winter Arctic Sea Ice Surface Form Drag During 1999-2021: Satellite Retrieval and Spatiotemporal Variability

The neutral form drag coefficient is an important parameter when estimating surface turbulent fluxes over Arctic sea ice. The form drag caused by surface features (????) dominates the total drag in the winter, but long-term pan-Arctic records of ???? are still lacking for Arctic sea ice. In this stu...

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Main Authors: Zhang, Zhilun, Hui, Fengming, Shokr, Mohammed, Granskog, Mats A., Cheng, Bin, Vihma, Timo, Cheng, Xiao
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Language:unknown
Published: Institute of Electrical and Electronics Engineers (IEEE) 2024
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Online Access:http://dx.doi.org/10.36227/techrxiv.170491528.81011247/v1
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spelling crieeecr:10.36227/techrxiv.170491528.81011247/v1 2024-04-28T08:06:09+00:00 Winter Arctic Sea Ice Surface Form Drag During 1999-2021: Satellite Retrieval and Spatiotemporal Variability Zhang, Zhilun Hui, Fengming Shokr, Mohammed Granskog, Mats A. Cheng, Bin Vihma, Timo Cheng, Xiao 2024 http://dx.doi.org/10.36227/techrxiv.170491528.81011247/v1 unknown Institute of Electrical and Electronics Engineers (IEEE) https://creativecommons.org/licenses/by-sa/4.0/ posted-content 2024 crieeecr https://doi.org/10.36227/techrxiv.170491528.81011247/v1 2024-04-02T07:46:48Z The neutral form drag coefficient is an important parameter when estimating surface turbulent fluxes over Arctic sea ice. The form drag caused by surface features (????) dominates the total drag in the winter, but long-term pan-Arctic records of ???? are still lacking for Arctic sea ice. In this study, we first developed an improved surface feature detection algorithm and characterized the surface features (including height and spacing) over Arctic sea ice during the late winter of 2009-2019 using the full-scan laser altimeter data obtained in the Operation IceBridge mission. ???? was then estimated using an existing parameterization scheme. This was followed by applying a satellite-derived backscatter coefficient (???? ) to ???? regression model to extrapolate, for the first time, ???? to the pan-Arctic scale for the entire winter season over two decades (from 1999 to 2021). We found that the surface features have a larger height and smaller spacing over multi-year ice (1.15 ± 0.21 m and 142 ± 49 m) than over first-year ice (0.90 ± 0.16 m and 241 ± 129 m). The monthly mean ???? increases through the winter, from 0.2 × 10 −3 in November to 0.4-0.5 × 10 −3 in April. The central Arctic has the largest ???? (up to 2 × 10 −3), but experienced a drop of ~50% in the period from 2001/2002 to 2008/2009. The interannual fluctuations in ???? are strongly linked to the variability of sea ice thickness and deformation, and the latter has become increasingly important for ???? since 2009. Other/Unknown Material Arctic Sea ice IEEE Publications
institution Open Polar
collection IEEE Publications
op_collection_id crieeecr
language unknown
description The neutral form drag coefficient is an important parameter when estimating surface turbulent fluxes over Arctic sea ice. The form drag caused by surface features (????) dominates the total drag in the winter, but long-term pan-Arctic records of ???? are still lacking for Arctic sea ice. In this study, we first developed an improved surface feature detection algorithm and characterized the surface features (including height and spacing) over Arctic sea ice during the late winter of 2009-2019 using the full-scan laser altimeter data obtained in the Operation IceBridge mission. ???? was then estimated using an existing parameterization scheme. This was followed by applying a satellite-derived backscatter coefficient (???? ) to ???? regression model to extrapolate, for the first time, ???? to the pan-Arctic scale for the entire winter season over two decades (from 1999 to 2021). We found that the surface features have a larger height and smaller spacing over multi-year ice (1.15 ± 0.21 m and 142 ± 49 m) than over first-year ice (0.90 ± 0.16 m and 241 ± 129 m). The monthly mean ???? increases through the winter, from 0.2 × 10 −3 in November to 0.4-0.5 × 10 −3 in April. The central Arctic has the largest ???? (up to 2 × 10 −3), but experienced a drop of ~50% in the period from 2001/2002 to 2008/2009. The interannual fluctuations in ???? are strongly linked to the variability of sea ice thickness and deformation, and the latter has become increasingly important for ???? since 2009.
format Other/Unknown Material
author Zhang, Zhilun
Hui, Fengming
Shokr, Mohammed
Granskog, Mats A.
Cheng, Bin
Vihma, Timo
Cheng, Xiao
spellingShingle Zhang, Zhilun
Hui, Fengming
Shokr, Mohammed
Granskog, Mats A.
Cheng, Bin
Vihma, Timo
Cheng, Xiao
Winter Arctic Sea Ice Surface Form Drag During 1999-2021: Satellite Retrieval and Spatiotemporal Variability
author_facet Zhang, Zhilun
Hui, Fengming
Shokr, Mohammed
Granskog, Mats A.
Cheng, Bin
Vihma, Timo
Cheng, Xiao
author_sort Zhang, Zhilun
title Winter Arctic Sea Ice Surface Form Drag During 1999-2021: Satellite Retrieval and Spatiotemporal Variability
title_short Winter Arctic Sea Ice Surface Form Drag During 1999-2021: Satellite Retrieval and Spatiotemporal Variability
title_full Winter Arctic Sea Ice Surface Form Drag During 1999-2021: Satellite Retrieval and Spatiotemporal Variability
title_fullStr Winter Arctic Sea Ice Surface Form Drag During 1999-2021: Satellite Retrieval and Spatiotemporal Variability
title_full_unstemmed Winter Arctic Sea Ice Surface Form Drag During 1999-2021: Satellite Retrieval and Spatiotemporal Variability
title_sort winter arctic sea ice surface form drag during 1999-2021: satellite retrieval and spatiotemporal variability
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2024
url http://dx.doi.org/10.36227/techrxiv.170491528.81011247/v1
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_rights https://creativecommons.org/licenses/by-sa/4.0/
op_doi https://doi.org/10.36227/techrxiv.170491528.81011247/v1
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