scholarly journals Assessment of ICESat‐2 sea ice surface classification with Sentinel‐2 imagery: implications for freeboard and new estimates of lead and floe geometry

2021 ◽  
Author(s):  
A. A. Petty ◽  
M. Bagnardi ◽  
N. Kurtz ◽  
R. Tilling ◽  
S. Fons ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ice Surface ◽  
Surface Classification ◽  
Sentinel 2

scholarly journals Assessment of ICESat-2 sea ice surface classification with Sentinel-2 imagery: implications for freeboard and new estimates of lead and floe geometry

2020 ◽  
Author(s):  
Alek Petty ◽  
Marco Bagnardi ◽  
Nathan Kurtz ◽  
Rachel Tilling ◽  
Steven Fons ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ice Surface ◽  
Surface Classification ◽  
Sentinel 2

Collocated OLCI optical imagery and SAR radar altimetry from Sentinel3 for enhanced sea ice surface classification

2021 ◽  
Author(s):  
Dorsa Nasrollahi Shirazi ◽  
Michel Tsamados ◽  
Isobel Lawrence ◽  
Sanggyun Lee ◽  
Thomas Johnson ◽  
...  
Keyword(s):  
Sea Ice ◽  
Classification Algorithms ◽  
Polar Regions ◽  
Radar Altimetry ◽  
Imaging Spectrometer ◽  
Ice Surface ◽  
Ice Roughness ◽  
Elevation Data ◽  
Optical Imagery ◽  
Surface Classification

<p>The Copernicus operational Sentinel-3A since February 2016 and Sentinel-3B since April 2018 build on the CryoSat-2 legacy in terms of their synthetic aperture radar (SAR) mode altimetry providing high-resolution radar freeboard elevation data over the polar regions up to 81N. This technology combined with the Ocean and Land Colour Instrument (OLCI) imaging spectrometer offers the first space-time collocated optical imagery and radar altimetry dataset. We use these joint datasets for validation of several existing surface classification algorithms based on Sentinel-3 altimeter echo shapes. We also explore the potential for novel AI techniques such as convolutional neural networks (CNN) for winter and summer sea ice surface classification (i.e. melt pond fraction, lead fraction, sea ice roughness). For lead surface classification we analyse the winters of 2018/19 and 2019/20 and for summer sea ice feature classification we focus on the Sentinel-3A &3B tandem phase of the summer 2018. We compare our CNN models with other existing surface classification algorithms.</p>

scholarly journals Mapping Sea Ice Surface Topography in High Fidelity with ICESat-2

2020 ◽  
Author(s):  
Sinéad Farrell ◽  
Kyle Duncan ◽  
Ellen Buckley ◽  
Jacqueline Richter-Menge ◽  
Ruohan Li
Keyword(s):  
Sea Ice ◽  
Surface Topography ◽  
High Fidelity ◽  
Ice Surface

Physical properties and spatial distribution of the sea ice surface layer (SSL/snow) during the autumn phase of the MOSAiC expedition

2021 ◽  
Author(s):  
Ruzica Dadic ◽  
Martin Schneebeli ◽  
Henna-Reeta Hannula ◽  
Amy Macfarlane ◽  
Roberta Pirazzini
Keyword(s):  
Surface Layer ◽  
Spatial Distribution ◽  
Sea Ice ◽  
Physical Properties ◽  
Surface Scattering ◽  
Climate Feedback ◽  
Energy Fluxes ◽  
Scattering Layer ◽  
Near Surface ◽  
Ice Surface

<p>Snow cover dominates the thermal and optical properties of sea ice and the energy fluxes between the ocean and the atmosphere, yet data on the physical properties of snow and its effects on sea ice are limited. This lack of data leads to two significant problems: 1) significant biases in model representations of the sea ice cover and the processes that drive it, and 2) large uncertainties in how sea ice influences the global energy budget and the coupling of climate feedback. The  MOSAiC research initiative enabled the most extensive data collection of snow and surface scattering layer (SSL) properties over sea ice to date. During leg 5 of the MOSAiC expedition, we collected multi-scale (microscale to 100-m scale) measurements of the surface layer (snow/SSL) over first year ice (FYI) and MYI on a daily basis. The ultimate goal of our measurements is to determine the spatial distribution of physical properties of the surface layer. During leg 5 of the MOSAiC expedition, that surface layer changed from the  surface scattering layer (SSL),   characteristic for the melt season, to an early autumn snow pack. Here,  we will present data showing both a) the physical properties and the spatial distribution of the SSL during the late melt season and b) the transition of the sea ice surface from the SSL to the fresh autumn snowpack. The structural properties of this transition period are poorly documented, and this season is critical  for the initialization of sea ice and snow models. Furthermore, these data are crucial to interpret simultaneous observations of surface energy fluxes, surface optical and remote sensing data (microwave signals in particular), near-surface biochemical activity, and to understand the sea ice  processes that occur as the sea ice transitions from melting to freezing.</p>

Seasonal evolution and salt/freshwater fluxes of first-year sea ice: Comparison between pack ice and landfast sea ice 

2021 ◽  
Author(s):  
Marc Oggier ◽  
Hajo Eicken ◽  
Robert Rember ◽  
Allison Fong ◽  
Dmitry V. Divine ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ice Cores ◽  
Upper Ocean ◽  
First Year ◽  
Ice Melt ◽  
Ice Surface ◽  
Freshwater Fluxes ◽  
Exchange Processes ◽  
Bulk Salinity ◽  
Landfast Sea Ice

<p>Sea ice affects the exchange of energy and matter between the atmosphere and the ocean from local to hemispheric scales. Salt fluxes across the ice-ocean interface that drive thermohaline mixing beneath growing sea ice are important elements of upper ocean nutrient and carbon exchange. Sea-ice melt releases freshwater into the upper ocean and results in formation of melt ponds that affect gas and energy transfer across the atmosphere-ice interface. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) provided an opportunity to follow sea-ice evolution and exchange processes over a full seasonal cycle in a rapidly changing ice cover. To this end, approximately 25 sea-ice cores were collected at 2 distinct sites, representing first-year and multi-year ice, to monitor physical, biological and geochemical processes relevant to atmosphere-ice-ocean exchange processes. Here we compare the growth and decay of first-year ice in the Central Arctic during the winter 2019-2020 to that of landfast first-year ice at Utqiaġvik, Alaska, from 1998 to 2016. Ice stratigraphy was similar at both sites with about 15 cm of granular ice on top of columnar ice, with a comparable growth history with a similar maximum ice thickness of 1.6-1.7 m. We aggregated the sea-ice bulk salinity and temperature profiles using a degree-day approach, and examined brine and freshwater fluxes at lower and upper interfaces of the ice, respectively. Preliminary results show lower sea-ice bulk salinity during the growth season and greater desalination at the ice surface during the melt season at the MOSAiC floe in comparison to Utqiaġvik.</p>

scholarly journals A Field Study of Brine Drainage and Oil Entrainment in First-Year Sea Ice

1979 ◽  
Vol 22 (88) ◽  
pp. 473-502 ◽  
Author(s):  
Seelye Martin
Keyword(s):  
Sea Ice ◽  
Growth And Development ◽  
Salt Transport ◽  
First Year ◽  
Field Observations ◽  
Melt Pond ◽  
Ice Surface ◽  
Melt Ponds ◽  
Brine Channel ◽  
Horizontal Layers

AbstractFrom field observations this paper describes the growth and development of first-year sea ice and its interaction with petroleum. In particular, when sea ice initially forms, there is an upward salt transport so that the ice surface has a highly saline layer, regardless of whether the initial ice is frazil, columnar, or slush ice. When the ice warms in the spring, because of the eutectic condition, the surface salt liquifies and drains through the ice, leading to the formation of top-to-bottom brine channels and void spaces in the upper part of the ice. If oil is released beneath winter ice, then the oil becomes entrained in thin lenses within the ice. In the spring, this oil flows up to the surface through the newly-opened brine channels and distributes itself within the brine-channel feeder systems, on the ice surface, and in horizontal layers in the upper part of the ice. The paper shows that these layers probably form from the interaction of the brine drainage with the percolation of melt water from surface snow down into the ice and the rise of the oil from below. Finally in the summer, the oil on the surface leads to melt-pond formation. The solar energy absorbed by the oil on the surface of these melt ponds eventually causes the melt pond to melt through the ice, and the oil is again released into the ocean.

scholarly journals Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only

2015 ◽  
Vol 8 (10) ◽  
pp. 4025-4041 ◽  
Author(s):  
H.-J. Kang ◽  
J.-M. Yoo ◽  
M.-J. Jeong ◽  
Y.-I. Won
Keyword(s):  
Sea Ice ◽  
The Arctic ◽  
Data Sets ◽  
High Latitudes ◽  
Ice Surface ◽  
Moderate Resolution ◽  
Microwave Sounding ◽  
Polar Oceans ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Surface Temperature

Abstract. Uncertainties in the satellite-derived surface skin temperature (SST) data in the polar oceans during two periods (16–24 April and 15–23 September) 2003–2014 were investigated and the three data sets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (MODIS IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. The AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. MODIS IST was systematically warmer up to 1.65 K at the sea ice boundary and colder down to −2.04 K in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992–0.999) method was greater than that of the MODIS IST to the AIRS/AMSU (0.968–0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of −0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a less accurate GCM forecast over the seasonally varying frozen oceans than the microwave data. The three data sets (MODIS, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ~ 2.8 ± 1.9 K decade−1) in the northern high regions (70–80° N) as expected from the ice-albedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.

scholarly journals Formation of sea ice ponds from ice-shelf runoff, adjacent to the McMurdo Ice Shelf, Antarctica

2020 ◽  
Vol 61 (82) ◽  
pp. 73-77 ◽  
Author(s):  
Grant J. Macdonald ◽  
Predrag Popović ◽  
David P. Mayer
Keyword(s):  
Sea Ice ◽  
Added Mass ◽  
Surface Melting ◽  
Landsat 8 ◽  
Ice Shelf ◽  
Surface Hydrology ◽  
Ice Shelves ◽  
Arctic Ponds ◽  
Sentinel 2

AbstractPonds that form on sea ice can cause it to thin or break-up, which can promote calving from an adjacent ice shelf. Studies of sea ice ponds have predominantly focused on Arctic ponds formed by in situ melting/ponding. Our study documents another mechanism for the formation of sea ice ponds. Using Landsat 8 and Sentinel-2 images from the 2015–16 to 2018–19 austral summers, we analyze the evolution of sea ice ponds that form adjacent to the McMurdo Ice Shelf, Antarctica. We find that each summer, meltwater flows from the ice shelf onto the sea ice and forms large (up to 9 km2) ponds. These ponds decrease the sea ice's albedo, thinning it. We suggest the added mass of runoff causes the ice to flex, potentially promoting sea-ice instability by the ice-shelf front. As surface melting on ice shelves increases, we suggest that ice-shelf surface hydrology will have a greater effect on sea-ice stability.

scholarly journals Estimation of Level and Deformed First-Year Sea Ice Surface Roughness in the Canadian Arctic Archipelago from C- and L-Band Synthetic Aperture Radar

2019 ◽  
Vol 45 (3-4) ◽  
pp. 457-475 ◽  
Author(s):  
Silvie Marie Cafarella ◽  
Randall Scharien ◽  
Torsten Geldsetzer ◽  
Stephen Howell ◽  
Christian Haas ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Canadian Arctic ◽  
Synthetic Aperture ◽  
First Year ◽  
Canadian Arctic Archipelago ◽  
Ice Surface ◽  
L Band ◽  
Ice Surface Roughness

scholarly journals A reinterpretation of sea-salt records in Greenland and Antarctic ice cores?

2004 ◽  
Vol 39 ◽  
pp. 276-282 ◽  
Author(s):  
Andrew M. Rankin ◽  
Eric W. Wolff ◽  
Robert Mulvaney
Keyword(s):  
Sea Ice ◽  
Ice Core ◽  
Open Water ◽  
Weddell Sea ◽  
Sea Salt ◽  
Sea Salt Aerosol ◽  
Ice Surface ◽  
Frost Flowers ◽  
Ice Production ◽  
Ice Core Records

AbstractIt has recently been shown that much sea-salt aerosol around the coast of Antarctica is generated not from open water, but from the surface of newly formed sea ice. Previous interpretations of ice-core records have disregarded the sea-ice surface as a source of sea salt. The majority of sea-salt aerosol at Halley research station originates from frost flowers rather than open water, and the seasonal cycle of sea salt in aerosol at Halley appears to be controlled by ice production in the Weddell Sea, as well as variations in wind speed. Frost flowers are also an important source of aerosol at Siple Dome, suggesting that variations in sea-salt concentrations in the core, and other cores drilled in similar locations, may be reflecting changes in sea-ice production rather than changes in transportation patterns. For Greenland cores, and those from low-accumulation inland sites in Antarctica, it is not simple to calculate the proportion of sea salt originating from frost flowers rather than open water. However, modelling studies suggest that a sea-ice surface source contributed much of the flux of sea salt to these sites in glacial periods, suggesting that interpretations of ice-core records from these locations should also be revisited.

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