2020
DOI: 10.1029/2019jc015738
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Classification of Sea Ice Summer Melt Features in High‐Resolution IceBridge Imagery

Abstract: High-resolution observations of melt ponds (MPs) across the Arctic are lacking, yet essential for understanding the sea ice energy budget and under-ice ecology. We present a pixel-based classification scheme to identify undeformed and deformed ice, open water, and light, medium, and dark MPs in images of sea ice undergoing melt. The scheme was applied to 0.1-m resolution Operation IceBridge Digital Mapping System imagery covering an area of~4,000 km 2. Observations of both the unconsolidated, marginal ice zone… Show more

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Cited by 22 publications
(20 citation statements)
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“…But due to a >600‐km sample size, the statistics are regionally and seasonally representative. Classifying open water and ice floes in the Sentinel‐2 scene (following Buckley et al, 2020), we tagged lead and floe pixels along the ICESat‐2 track and used these for validation. Based on the results in Figure 3b, leads are identified in the ICESat‐2 data as level ice surfaces with ≥15 contiguous retrievals (~10‐m along‐track width) within 0.1 m of local reference surface with a standard deviation of ≤0.01 m. Lead retrievals accounted for 27.6% of the ICESat‐2 data, which is consistent with a regional open water fraction of 25.1% derived from Sentinel‐2.…”
Section: Fine‐scale Sea Ice Propertiesmentioning
confidence: 99%
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“…But due to a >600‐km sample size, the statistics are regionally and seasonally representative. Classifying open water and ice floes in the Sentinel‐2 scene (following Buckley et al, 2020), we tagged lead and floe pixels along the ICESat‐2 track and used these for validation. Based on the results in Figure 3b, leads are identified in the ICESat‐2 data as level ice surfaces with ≥15 contiguous retrievals (~10‐m along‐track width) within 0.1 m of local reference surface with a standard deviation of ≤0.01 m. Lead retrievals accounted for 27.6% of the ICESat‐2 data, which is consistent with a regional open water fraction of 25.1% derived from Sentinel‐2.…”
Section: Fine‐scale Sea Ice Propertiesmentioning
confidence: 99%
“…Following Buckley et al (2020), we classified open water, ponded surfaces, and ice floes in the Sentinel-2 scene (Figure 2b) and used this to validate the presence of ponds in the ICESat-2 data. By tracking the movement of 10 floes between two overlapping Sentinel-2 images acquired 50 min apart (not shown), we estimated an average ice drift rate of 9.3 cm s −1 .…”
Section: Melt Pondsmentioning
confidence: 99%
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“…We assume that most of the snow accumulated on sea ice floes over winter has melted by these midsummer dates (Kwok et al, 2020), so we can compare airborne laser scanner freeboards directly to the CryoSat-2 radar freeboards without requiring corrections for snow penetration or loading. IceBridge Airborne Topographic Mapper (ATM) returns from sea ice and leads which typically have an absolute elevation accuracy of about 10 cm, are classified with coinciding aerial photographs (Buckley et al, 2020) and used to derive a laser freeboard estimate along the flight track (details in the supplementary). We averaged all valid observations along 7 km sections of the flight track and performed a point-to-grid comparison with the CryoSat-2 freeboard grids.…”
Section: Validation Against Independent Airborne and Mooring Observationsmentioning
confidence: 99%
“…Melt ponds also increase turbulent energy exchange to the lower atmosphere (Andreas et al, 2010; Boisvert et al, 2013), influence light penetration and primary productivity in the upper ocean under sea ice (Arrigo et al, 2012; Massicotte et al, 2019), and are a key parameter for improving operational sea ice forecasts (Schröeder et al, 2014). Estimates of melt pond fraction (MPF) on summer Arctic sea ice vary between satellite observations (Rösel et al, 2012; Webster et al, 2015), field and airborne data (Buckley et al, 2020; Huang et al, 2016; Perovich et al, 2009), and models (Zhang et al, 2018), although all agree that MPF is significant.…”
Section: Introductionmentioning
confidence: 99%