2022
DOI: 10.5194/tc-16-1125-2022
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Generating large-scale sea ice motion from Sentinel-1 and the RADARSAT Constellation Mission using the Environment and Climate Change Canada automated sea ice tracking system

Abstract: Abstract. As Arctic sea ice extent continues to decline, remote sensing observations are becoming even more vital for the monitoring and understanding of sea ice. Recently, the sea ice community has entered a new era of synthetic aperture radar (SAR) satellites operating at C-band with the launch of Sentinel-1A in 2014 and Sentinel-1B (S1) in 2016 and the RADARSAT Constellation Mission (RCM) in 2019. These missions represent five spaceborne SAR sensors that together routinely cover the pan-Arctic sea ice domai… Show more

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Cited by 13 publications
(13 citation statements)
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References 38 publications
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“…We use a widely established methodology to estimate the sea ice area flux at the aforementioned gates (Agnew et al., 2008; Howell & Brady, 2019; Howell, Wohlleben, Dabboor, et al., 2013; Kwok, 2006; Kwok et al., 2010; Moore et al., 2021). For each SAR image pair, sea ice motion was estimated using the Environment and Climate Change Canada Automated Sea Ice Tracking System (ECCC‐ASITS; Howell, Brady, & Komarov, 2022) that is based on the Komarov and Barber (2014) feature tracking algorithm. The resulting sea ice motion estimates are interpolated using inverse distance weighting to each gate with a 30 km buffer on either side and then sampled at 5 km internals across each gate.…”
Section: Methodsmentioning
confidence: 99%
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“…We use a widely established methodology to estimate the sea ice area flux at the aforementioned gates (Agnew et al., 2008; Howell & Brady, 2019; Howell, Wohlleben, Dabboor, et al., 2013; Kwok, 2006; Kwok et al., 2010; Moore et al., 2021). For each SAR image pair, sea ice motion was estimated using the Environment and Climate Change Canada Automated Sea Ice Tracking System (ECCC‐ASITS; Howell, Brady, & Komarov, 2022) that is based on the Komarov and Barber (2014) feature tracking algorithm. The resulting sea ice motion estimates are interpolated using inverse distance weighting to each gate with a 30 km buffer on either side and then sampled at 5 km internals across each gate.…”
Section: Methodsmentioning
confidence: 99%
“…Komarov and Barber (2014) estimated the feature tracking algorithm used by the ECCC‐ASITS has an σ e of 0.43 km based on buoy comparison in the Beaufort Sea during the winter. Howell, Brady, and Komarov (2022) considered all Arctic buoys above 40°N without removing any outliers or imposing any quality flags on the buoys (e.g., Lindsay & Stern, 2003) and reported an σ e of 2.78 km for the winter (dry) months and an σ e of 3.43 km for the summer (wet) months. Solving Equation with this range of σ e values indicates that σ f over the sampling interval ranges from 12 to 92 km 2 at Nares Strait, 13–103 km 2 at M’Clure Strait, and 18–148 km 2 at the QEI.…”
Section: Methodsmentioning
confidence: 99%
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“…In Parry Channel thinning is statistically significant in autumn (November and December, -20 cm/decade) and spring (April, -9 cm/decade), with more variability in mid-winter. This is relevant for shipping safety as thinning of the sea ice in November and April would lengthen the summer shipping season (Howell et al, 2022;Mudryk et al, 2021). The Arctic Ocean Periphery shows significant thinning throughout winter except January, with trends as high as 30 cm/decade despite the area continuing to be predominantly covered by MYI.…”
Section: Limitations and Potentialmentioning
confidence: 99%