Mapping pan-Arctic landfast sea ice stability using  Sentinel-1 interferometry

Dammann, Dyre Oliver; Eriksson, Leif E. B.; Mahoney, Andrew R.; Eicken, Hajo; Meyer, Franz J.

doi:10.5194/tc-13-557-2019

Cited by 43 publications

(51 citation statements)

References 63 publications

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“…In this case, although the use of scatterometer data helps to improve the estimation of MYI concentration, it tends to misidentify young ice as MYI when backscatter from the former is high. The East Siberian Sea is one of the regions that have the most extensive coverage of landfast ice in the Arctic (Dammann et al, 2019). Figure 12 presents highly dynamic regions.…”

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confidence: 99%

Inter-comparison and evaluation of sea ice type concentration algorithms

Shokr

Aaboe

et al. 2019

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Abstract. Sea ice has been monitored in terms of concentration and types with microwave satellite observations since the late 1970s. However, it remains an open question as to which sea ice type concentration (SITC) method is most appropriate for ice type distribution and hence climate monitoring. This paper presents key results of inter-comparison and evaluation for eight SITC methods. The SITC methods were inter-compared with two sea ice age (SIA) and three sea ice type (SIT) products using microwave radiometer and scatterometer data from 2000 to 2015. Their performances were evaluated quantitatively with samples that are used for generating tie points, and qualitatively with the RADARSAT imagery. The methods that combined scatterometer and radiometer data have overall better performances on ice type discrimination. The best methods are ECICE-QSCAT-2 for the years 2000–2009 and ECICE-ASCAT for 2009–2015, both using scatterometer data along with radiometer data. Although the SIA and SIT products are fairly good datasets for delineating ice type distributions, the SITC methods are better on preserving details like varied concentration of different ice types and work better under specific sea ice conditions, for instance, homogeneous sea ice regions with little artifact for SIA algorithms to track.

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confidence: 99%

Inter-comparison and evaluation of sea ice type concentration algorithms

Shokr

Aaboe

et al. 2019

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“…The majority of the published InSAR studies focus on landfast ice, which under favorable conditions allows the use of repeat pass InSAR without complete decorrelation e.g., [18,25,[53][54][55].…”

Section: Discussionmentioning

confidence: 99%

“…Besides resulting in stable anchoring points, ridges and the ice surface morphology can hamper the use of parts of the coastal ice by inhibiting transportation. Therefore, ample studies have contributed to the understanding of landfast ice dynamics [18], ridge formation [8,11], and how ridges impact trafficability of the ice [19][20][21]. Through such work, ridge height has been measured using ground-based electromagnetic conductivity [21], helicopter-borne laser profilers [22], airborne laser scanners [23], structure-from-motion [20], and spaceborne altimeters [24].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Landfast Sea Ice Ridging near UtqiaġVik Alaska Using TanDEM-X Interferometry

et al. 2020

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Seasonal landfast sea ice stretches along most Arctic coastlines and serves as a platform for community travel and subsistence, industry operations, and as a habitat for marine mammals. Landfast ice can feature smooth ice and areas of m-scale roughness in the form of pressure ridges. Such ridges can significantly hamper trafficability, but if grounded can also serve to stabilize the shoreward ice. We investigate the use of synthetic aperture radar interferometry (InSAR) to assess the formation and movement of ridges in the landfast sea ice near Utqiaġvik, Alaska. The evaluation is based on the InSAR-derived surface elevation change between two TanDEM-X bistatic image pairs acquired during January 2012. We compare the results with backscatter intensity, coastal radar data, and SAR-derived ice drift and evaluate the utility of this approach and its relevance for evaluation of ridge properties, as well as landfast sea ice evolution, dynamics, and stability. Data Curation, M.M.; Writing-Original Draft Preparation, M.M.; Writing-Review & Editing

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“…In contrast, landfast sea ice (short: fast ice) is attached to the coast or associated geographical features, such as for example a shallow seafloor (especially in Arctic regions) or grounded icebergs, and is therefore immobile (JCOMM Expert Team on Sea Ice, 2015). Fast ice is a predominant and characteristic feature of the Arctic (Dammann et al, 2019;Yu et al, 2014) and Antarctic coasts (Fraser et al, 2012), especially in winter. Its extent may vary between just a few meters and several hundred kilometers from where it is attached to, mostly depending on the local topography and coastline morphology.…”

Section: Introductionmentioning

confidence: 99%

Seasonal and interannual variability of landfast sea ice in Atka Bay, Weddell Sea, Antarctica

Arndt¹,

Nicolaus²,

Hoppmann³

et al. 2020

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Abstract. Landfast sea ice (fast ice), attached to Antarctic coastal and near-coastal elements, is a critical element of the local physical and ecological systems. Through its direct coupling with the atmosphere and ocean, fast ice and its snow cover are also potential indicators of processes related to climate change. However, in-situ fast-ice observations in Antarctica are extremely sparse because of logistical challenges. Since 2010, a monitoring program, which is part of the Antarctic Fast Ice Network (AFIN), has been conducted on the seasonal evolution of fast ice of Atka Bay. The bay is located on the north-eastern edge of Ekström Ice Shelf in the eastern Weddell Sea, close to the German wintering station Neumayer Station III. A number of sampling sites have been regularly revisited between annual ice formation and breakup each year to obtain a continuous record of snow depth, freeboard, sea-ice- and sub-ice platelet layer thickness across the bay. Here, we present the time series of these measurements over the last nine years. Combining them with observations from the nearby meteorological observatory at Neumayer Station as well as satellite images allows to relate the seasonal and interannual fast-ice cycle to the factors that influence its evolution. On average, the annual consolidated fast-ice thickness at the end of the growth season is about two meters, with a loose platelet layer accumulation of four meters beneath and 0.70 meters snow on top. Results highlight the predominately seasonal character of the fast-ice regime in Atka Bay without a significant trend in any of the observed variables over the nine-year observation period. Also, no changes are evident when comparing with measurements in the 1980s. However, strong easterly winds in the area govern the year-round snow redistribution and also trigger the breakup event in the bay during summer months. Due to the substantial snow accumulation on the ice, a characteristic feature is frequent negative freeboard, associated flooding of the snow/ice interface and subsequent formation of snow ice. The buoyant platelet-ice layer beneath negates the snow weight to some extent, but snow thermodynamics is identified as the main driver of the energy and mass budgets for the fast-ice cover in Atka Bay. An enhanced knowledge on the seasonal and interannual variability of the fast-ice properties will improve our understanding of interactions between atmosphere, fast ice, ocean and ice shelves in one of the key regions of Antarctica.

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Mapping pan-Arctic landfast sea ice stability using Sentinel-1 interferometry

Cited by 43 publications

References 63 publications

Inter-comparison and evaluation of sea ice type concentration algorithms

Inter-comparison and evaluation of sea ice type concentration algorithms

Evaluating Landfast Sea Ice Ridging near UtqiaġVik Alaska Using TanDEM-X Interferometry

Seasonal and interannual variability of landfast sea ice in Atka Bay, Weddell Sea, Antarctica

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