Landfast sea ice extent and variability in the alaskan arctic derived from SAR imagery

2004 ◽  
Author(s):  
Hajo Eicken Andy Mahoney
Keyword(s):  
Sea Ice ◽  
Sea Ice Extent ◽  
Alaskan Arctic ◽  
Sar Imagery ◽  
Landfast Sea Ice

scholarly journals Modelling landfast sea ice and its influence on ocean-ice interactions in the area of the Totten Glacier, East Antarctica

2021 ◽  
Author(s):  
Guillian Van Achter ◽  
Thierry Fichefet ◽  
Hugues Goosse ◽  
Charles Pelletier ◽  
Jean Sterlin ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Mixed Layer Depth ◽  
Global Climate Models ◽  
East Antarctica ◽  
Ice Shelf ◽  
Sea Ice Extent ◽  
Coastal Polynya ◽  
Landfast Sea Ice ◽  
The Impact

<p>The Totten Glacier in East Antarctica is of major climate interest because of the large fluctuation of its grounding line and of its potential vulnerability to climate change. The ocean above the continental shelf in front of the Totten ice shelf exhibits large extents of landfast sea ice with low interannual variability. Landfast sea ice is mostly not or sole crudely represented in current climate models. These models are potentially omitting or misrepresenting important effects related to this type of sea ice, such as its influence on coastal polynya locations. Yet, the impact of the landfast sea<br>ice on the ocean – ice shelf interactions is poorly understood. Using a series of high-resolution, regional NEMO-LIM-based experiments including an<br>explicit treatment of ocean – ice shelf interactions over the years 2001-2010, we simulate a realistic landfast sea ice extent in the area of Totten Glacier<br>through a combination of a sea ice tensile strength parameterisation and a grounded iceberg representation. We show that the presence of landfast sea<br>ice impacts seriously both the location of coastal polynyas and the ocean mixed layer depth along the coast, in addition to favouring the intrusion of<br>mixed Circumpolar Deep Water into the ice shelf cavities. Depending on the local bathymetry and the landfast sea ice distribution, landfast sea ice affects ice shelf cavities in different ways, either by increasing the ice melt (+28% for the Moscow University ice shelf) or by reducing its seasonal cycle<br>(+10% in March-May for the Totten ice shelf). This highlights the importance of including an accurate landfast sea ice representation in regional and<br>eventually global climate models</p>

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

2019 ◽  
Vol 13 (2) ◽  
pp. 557-577 ◽  
Author(s):  
Dyre O. Dammann ◽  
Leif E. B. Eriksson ◽  
Andrew R. Mahoney ◽  
Hajo Eicken ◽  
Franz J. Meyer
Keyword(s):  
Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Marginal Seas ◽  
Nares Strait ◽  
Novel Approach ◽  
Landfast Ice ◽  
Landfast Sea Ice ◽  
Fringe Patterns ◽  
The Stability

Abstract. Arctic landfast sea ice has undergone substantial changes in recent decades, affecting ice stability and including potential impacts on ice travel by coastal populations and on industry ice roads. We present a novel approach for evaluating landfast sea ice stability on a pan-Arctic scale using Synthetic Aperture Radar Interferometry (InSAR). Using Sentinel-1 images from spring 2017, we discriminate between bottomfast, stabilized, and nonstabilized landfast ice over the main marginal seas of the Arctic Ocean (Beaufort, Chukchi, East Siberian, Laptev, and Kara seas). This approach draws on the evaluation of relative changes in interferometric fringe patterns. This first comprehensive assessment of Arctic bottomfast sea ice extent has revealed that most of the bottomfast sea ice is situated around river mouths and coastal shallows. The Laptev and East Siberian seas dominate the aerial extent, covering roughly 4100 and 5100 km2, respectively. These seas also contain the largest extent of stabilized and nonstabilized landfast ice, but are subject to the largest uncertainties surrounding the mapping scheme. Even so, we demonstrate the potential for using InSAR for assessing the stability of landfast ice in several key regions around the Arctic, providing a new understanding of how stability may vary between regions. InSAR-derived stability may serve for strategic planning and tactical decision support for different uses of coastal ice. In a case study of the Nares Strait, we demonstrate that interferograms may reveal early-warning signals for the breakup of stationary sea ice.

scholarly journals Landfast sea ice stability – mapping pan-Arctic ice regimes with implications for ice use, subsea permafrost and marine habitats

2018 ◽  
Author(s):  
Dyre O. Dammann ◽  
Leif E. B. Eriksson ◽  
Andrew R. Mahoney ◽  
Hajo Eicken ◽  
Franz J. Meyer
Keyword(s):  
Sea Ice ◽  
Chukchi Sea ◽  
The Arctic ◽  
Small Scale ◽  
Sea Ice Extent ◽  
Support Tool ◽  
Marine Habitats ◽  
Landfast Ice ◽  
Landfast Sea Ice ◽  
Subsea Permafrost

Abstract. Arctic landfast sea ice has undergone substantial changes in recent decades affecting ice stability with potential impacts on ice travel by coastal populations and industry ice roads. The role of landfast ice as an important habitat has also evolved. We present a novel approach to evaluate sea ice stability on a pan-Arctic scale using Synthetic Aperture Radar Interferometry (InSAR). Using Sentinel-1 images from spring 2017, the approach discriminates between bottomfast, with critical relevance for subsea permafrost, as well as stabilized and non-stabilized floating landfast ice over the main marginal seas of the Arctic Ocean (Beaufort, Chukchi, East Siberian, Laptev and Kara Seas). The analysis draws on evaluation of small-scale lateral motion derived from relative changes in interferometric fringe patterns. This first comprehensive assessment of Arctic bottomfast sea ice extent revealed that by area most of the bottomfast sea ice is situated around river mouths and coastal shallows in the Laptev and East Siberian Seas, covering roughly 4.1 and 5.5 thousand km2 respectively. The fraction between non-stabilized and stabilized ice is lowest in the Beaufort at almost unity, and highest in the adjacent Chukchi Sea. Beyond the simple delineation of landfast ice zones, this work provides a new understanding of how stability regimes may vary between regions and over time. InSAR-derived stability data may serve as a strategic planning and tactical decision-support tool for different uses of coastal ice. Such information may also inform assessments of important sea ice habitats. In a case study, we examined an ice arch situated in Nares Strait demonstrating that interferograms may reveal early-warning signals for the break-up of stationary sea ice.

Landfast sea ice extent in the Chukchi and Beaufort Seas: The annual cycle and decadal variability

2014 ◽  
Vol 103 ◽  
pp. 41-56 ◽  
Author(s):  
Andrew R. Mahoney ◽  
Hajo Eicken ◽  
Allison G. Gaylord ◽  
Rudiger Gens
Keyword(s):  
Sea Ice ◽  
Annual Cycle ◽  
Decadal Variability ◽  
Sea Ice Extent ◽  
Landfast Sea Ice

scholarly journals InSAR Monitoring of Arctic Landfast Sea Ice Deformation Using L-Band ALOS-2, C-Band Radarsat-2 and Sentinel-1

2021 ◽  
Vol 13 (22) ◽  
pp. 4570
Author(s):  
Zhaohua Chen ◽  
Benoit Montpetit ◽  
Sarah Banks ◽  
Lori White ◽  
Amir Behnamian ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
The Arctic ◽  
Process Time ◽  
Time Interval ◽  
L Band ◽  
Sar Imagery ◽  
Landfast Sea Ice ◽  
Small Baseline ◽  
The Stability

Arctic amplification is accelerating changes in sea ice regimes in the Canadian Arctic with later freeze-up and earlier melt events, adversely affecting Arctic wildlife and communities that depend on the stability of sea ice conditions. To monitor both the rate and impact of such change, there is a need to accurately measure sea ice deformation, an important component for understanding ice motion and polar climate. The objective of this study is to determine the spatial-temporal pattern of deformation over landfast ice in the Arctic using time series SAR imagery. We present Interferometric Synthetic Aperture Radar (InSAR) monitoring of Arctic landfast sea ice deformation using C-band Radarsat-2, Sentinel-1 and L-band ALOS-2 in this paper. The small baseline subset (SBAS) approach was explored to process time series observations for retrieval of temporal deformation changes along a line-of-sight direction (LOS) over the winter. It was found that temporal and spatial patterns of deformation observed from different sensors were generally consistent. Horizontal and vertical deformations were also retrieved by a multi-dimensional SBAS technique using both ascending and descending Sentinel-1 observations. Results showed a horizontal deformation in the range of -95-85 cm, and vertical deformation in the range of -41-63 cm in Cambridge Bay, Nunavut, Canada during February-April 2019. High coherence over ice from C-band was maintained over a shorter time interval of acquisitions than L-band due to temporal decorrelation.

scholarly journals Spectral albedo of coastal landfast sea ice in Prydz Bay, Antarctica

2020 ◽  
pp. 1-11
Author(s):  
Guanghua Hao ◽  
Roberta Pirazzini ◽  
Qinghua Yang ◽  
Zhongxiang Tian ◽  
Changwei Liu
Keyword(s):  
Sea Ice ◽  
Near Infrared ◽  
Elevation Angle ◽  
Early Summer ◽  
Prydz Bay ◽  
Katabatic Wind ◽  
Surface Conditions ◽  
Zhongshan Station ◽  
Landfast Sea Ice ◽  
Two Phases

Abstract The surface spectral albedo was measured over coastal landfast sea ice in Prydz Bay (off Zhongshan Station), East Antarctica from 5 October to 26 November of 2016. The mean albedo decreased from late-spring to early-summer, mainly responding to the change in surface conditions from dry (phase I) to wet (phase II). The evolution of the albedo was strongly influenced by the surface conditions, with alternation of frequent snowfall events and katabatic wind that induce snow blowing at the surface. The two phases and day-to-day albedo variability were more pronounced in the near-infrared albedo wavelengths than in the visible ones, as the near-infrared photons are more sensitive to snow metamorphism, and to changes in the uppermost millimeters and water content of the surface. The albedo diurnal cycle during clear sky conditions was asymmetric with respect to noon, decreasing from morning to evening over full and patchy snow cover, and decreasing more rapidly in the morning over bare ice. We conclude that snow and ice metamorphism and surface melting dominated over the solar elevation angle dependency in shaping the albedo evolution. However, we realize that more detailed surface observations are needed to clarify and quantify the role of the various surface processes.

scholarly journals Sea Ice Concentration and Sea Ice Extent Mapping with L-Band Microwave Radiometry and GNSS-R Data from the FFSCat Mission Using Neural Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 1139
Author(s):  
David Llaveria ◽  
Juan Francesc Munoz-Martin ◽  
Christoph Herbert ◽  
Miriam Pablos ◽  
Hyuk Park ◽  
...  
Keyword(s):  
Sea Ice ◽  
Microwave Radiometer ◽  
Cost Effective ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Neural Network Approach ◽  
Ice Concentration ◽  
L Band ◽  
Moderate Cost

CubeSat-based Earth Observation missions have emerged in recent times, achieving scientifically valuable data at a moderate cost. FSSCat is a two 6U CubeSats mission, winner of the ESA S3 challenge and overall winner of the 2017 Copernicus Masters Competition, that was launched in September 2020. The first satellite, 3Cat-5/A, carries the FMPL-2 instrument, an L-band microwave radiometer and a GNSS-Reflectometer. This work presents a neural network approach for retrieving sea ice concentration and sea ice extent maps on the Arctic and the Antarctic oceans using FMPL-2 data. The results from the first months of operations are presented and analyzed, and the quality of the retrieved maps is assessed by comparing them with other existing sea ice concentration maps. As compared to OSI SAF products, the overall accuracy for the sea ice extent maps is greater than 97% using MWR data, and up to 99% when using combined GNSS-R and MWR data. In the case of Sea ice concentration, the absolute errors are lower than 5%, with MWR and lower than 3% combining it with the GNSS-R. The total extent area computed using this methodology is close, with 2.5% difference, to those computed by other well consolidated algorithms, such as OSI SAF or NSIDC. The approach presented for estimating sea ice extent and concentration maps is a cost-effective alternative, and using a constellation of CubeSats, it can be further improved.

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