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 Snow and ice applications of AVHRR in polar regions: report of a workshop held in Boulder, Colorado, 20 May 1992

1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Quality Data ◽  
Polar Regions ◽  
Data Set ◽  
Ice Surface ◽  
The Status ◽  
Ice Surface Temperature ◽  
Snow And Ice

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

scholarly journals Snow and ice applications of AVHRR in polar regions: report of a workshop held in Boulder, Colorado, 20 May 1992

1993 ◽  
Vol 17 ◽  
pp. 1-16 ◽  
Author(s):  
K. Steffen ◽  
R. Bindschadler ◽  
G. Casassa ◽  
J. Comiso ◽  
D. Eppler ◽  
...  
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Quality Data ◽  
Polar Regions ◽  
Data Set ◽  
Ice Surface ◽  
The Status ◽  
Ice Surface Temperature ◽  
Snow And Ice

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17–22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

scholarly journals C-Band Polarimetric Coherences and Ratios for Discriminating Sea Ice Roughness

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Mukesh Gupta ◽  
Randall K. Scharien ◽  
David G. Barber
Keyword(s):  
Surface Roughness ◽  
Sea Ice ◽  
Two Dimensions ◽  
The Arctic ◽  
Rapid Decline ◽  
Ice Surface ◽  
Ice Roughness ◽  
Direct Measurements ◽  
Ice Surface Roughness ◽  
Spaceborne Radar

The rapid decline of sea ice in the Arctic has resulted in a variable sea ice roughness that necessitates improved methods for efficient observation using high-resolution spaceborne radar. The utility of C-band polarimetric backscatter, coherences, and ratios as a discriminator of ice surface roughness is evaluated. An existing one-dimensional backscatter model has been modified to two-dimensions (2D) by considering deviation in the orientation (i.e., the slopes) in azimuth and range direction of surface roughness simultaneously as an improvement in the model. It is shown theoretically that the circular coherence (ρRRLL) decreases exponentially with increasing surface roughness. The crosspolarized coherence (ρHHVH) is found to be less sensitive to surface roughness, whereas the copolarized coherence (ρVVHH) decreases at far-range incidence angles for all ice types. A complete validation of the adapted 2D model using direct measurements of surface roughness is suggested as an avenue for further research.

scholarly journals Physical processes behind interactions of microplastic particles with natural ice

2022 ◽  
Author(s):  
Irina P Chubarenko
Keyword(s):  
Sea Ice ◽  
Ice Core ◽  
Ice Cores ◽  
Natural Environments ◽  
Polar Regions ◽  
Air Bubbles ◽  
Field Observations ◽  
Physical Processes ◽  
Ice Surface ◽  
Brittle Ductile Transition

Abstract Microplastic particles (MPs, <5 mm) are found in marine ice in larger quantities than in seawater, however, the distribution pattern within the ice cores is not consistent. To get insights into the most general physical processes behind interactions of ice and plastic particles in cool natural environments, information from academic and applied research is integrated and verified against available field observations. Non-polar molecules of common-market plastics are hydrophobic, so MPs are weak ice nucleators, are repelled from water and ice, and concentrate within air bubbles and brine channels. A large difference in thermal properties of ice and plastics favours concentration of MPs at the ice surface during freeze/thaw cycles. Under low environmental temperatures, falling in polar regions below the glass / brittle-ductile transition temperatures of the common-use plastics, they become brittle. This might partially explain the absence of floating macroplastics in polar waters. Freshwater freezes at the temperature well below that of its maximum density, so the water column is stably stratified, and MPs eventually concentrate at the ice surface and in air bubbles. In contrast, below growing sea ice, mechanisms of suspension freezing under conditions of (thermal plus haline) convection should permanently entangle MPs into ice. During further sea ice growth and aging, MPs are repelled from water and ice into air bubbles, brine channels, and to the upper/lower boundaries of the ice column. Sea ice permeability, especially while melting periods, can re-distribute sub-millimeter MPs through the brine channels, thus potentially introducing the variability of contamination with time. In accord with field observations, analysis reveals several competing factors that influence the distribution of MPs in sea ice. A thorough sampling of the upper ice surface, prevention of brine leakage while sampling and handling, considering the ice structure while segmenting the ice core – these steps may be advantageous for further understanding the pattern of plastic contamination in natural ice.

scholarly journals The Timing of Initial Spring Melt in the Arctic from Nimbus-7 SMMR Data (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 244-244
Author(s):  
Mark R. Anderson
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Chukchi Sea ◽  
Global Climate ◽  
Arctic Basin ◽  
Temporal Variations ◽  
The Arctic ◽  
Energy Budgets ◽  
Polar Regions ◽  
Ice Surface

The ablation of sea ice is an important feature in the global climate system. During the melt season in the Arctic, rapid changes occur in sea-ice surface conditions and areal extent of ice. These changes alter the albedo and vary the energy budgets. Understanding the spatial and temporal variations of melt is critical in the polar regions. This study investigates the spring onset of melt in the seasonal sea-ice zone of the Arctic Basin through the use of a melt signature derived by Anderson and others from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) data. The signature is recognized in the “gradient ratio” of the 18 and 37 GHz vertical brightness temperatures used to distinguish multi-year ice. A spuriously high fraction of multi-year ice appears rapidly during the initial melt of sea ice, when the snow-pack on the ice surface has started to melt. The brightness-temperature changes are a result of either enlarged snow crystals or incipient puddles forming at the snow/ice interface.The timing of these melt events varies geographically and with time. Within the Arctic Basin, the melt signatures are observed first in the Chukchi and Kara/Barents Seas. As the melt progresses, the location of the melt signature moves westward from the Chukchi Sea and eastward from the Kara/Barents Seas to the Laptev Sea region. The timing of the melt signal also varies with year. For example, the melt signature occurred first in the Chukchi Sea in 1979, while in 1980 the signature was first observed in the Kara Sea.There are also differences in the timing of melt for specific geographic locations between years. The melt signature varied almost 25 days in the Chukchi Sea region between 1979 and 1980. The other areas had changes in the 7–10 day range.The occurrence of these melt signatures can be used as an indicator of climate variability in the seasonal sea-ice zones of the Arctic. The timing of the microwave melt signature has also been examined in relation to melt observed on short-wave imagery. The melt events derived from the SMMR data are also related to the large-scale climate conditions.

scholarly journals Arctic Sea Ice Surface Roughness Derived from Multi-Angular Reflectance Satellite Imagery

2018 ◽  
Author(s):  
Anne W. Nolin
Keyword(s):  
Surface Roughness ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
Ice Age ◽  
Ice Surface ◽  
Ice Roughness ◽  
Melt Ponds ◽  
Arctic Sea ◽  
Angular Reflectance ◽  
Ice Surface Roughness

Sea ice surface roughness affects ice-atmosphere interactions, serves as an indicator of ice age, shows patterns of ice convergence and divergence, affects the spatial extent of summer melt ponds, and ice albedo. We have developed a method for mapping sea ice surface roughness using angular reflectance data from the Multi-angle Imaging SpectroRadiometer (MISR) and lidar-derived roughness measurements from the Airborne Topographic Mapper (ATM). Using an empirical data modeling approach, we derived estimates of Arctic sea ice roughness ranging from centimeters to decimeters meters within the MISR 275-m pixel size. Using independent ATM data for validation, we find that histograms of lidar and multi-angular roughness values are nearly identical for areas with roughness &lt;20 cm but that for rougher regions, the MISR-derived roughness has a narrower range of values than the ATM data. The algorithm is able to accurately identify areas that transition between smooth and rough ice. Because of its coarser spatial scale, MISR-derived roughness data have a variance of about half that ATM roughness data.

scholarly journals The Timing of Initial Spring Melt in the Arctic from Nimbus-7 SMMR Data (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 244
Author(s):  
Mark R. Anderson
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Chukchi Sea ◽  
Global Climate ◽  
Arctic Basin ◽  
Temporal Variations ◽  
The Arctic ◽  
Energy Budgets ◽  
Polar Regions ◽  
Ice Surface

The ablation of sea ice is an important feature in the global climate system. During the melt season in the Arctic, rapid changes occur in sea-ice surface conditions and areal extent of ice. These changes alter the albedo and vary the energy budgets. Understanding the spatial and temporal variations of melt is critical in the polar regions. This study investigates the spring onset of melt in the seasonal sea-ice zone of the Arctic Basin through the use of a melt signature derived by Anderson and others from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) data. The signature is recognized in the “gradient ratio” of the 18 and 37 GHz vertical brightness temperatures used to distinguish multi-year ice. A spuriously high fraction of multi-year ice appears rapidly during the initial melt of sea ice, when the snow-pack on the ice surface has started to melt. The brightness-temperature changes are a result of either enlarged snow crystals or incipient puddles forming at the snow/ice interface. The timing of these melt events varies geographically and with time. Within the Arctic Basin, the melt signatures are observed first in the Chukchi and Kara/Barents Seas. As the melt progresses, the location of the melt signature moves westward from the Chukchi Sea and eastward from the Kara/Barents Seas to the Laptev Sea region. The timing of the melt signal also varies with year. For example, the melt signature occurred first in the Chukchi Sea in 1979, while in 1980 the signature was first observed in the Kara Sea. There are also differences in the timing of melt for specific geographic locations between years. The melt signature varied almost 25 days in the Chukchi Sea region between 1979 and 1980. The other areas had changes in the 7–10 day range. The occurrence of these melt signatures can be used as an indicator of climate variability in the seasonal sea-ice zones of the Arctic. The timing of the microwave melt signature has also been examined in relation to melt observed on short-wave imagery. The melt events derived from the SMMR data are also related to the large-scale climate conditions.

scholarly journals Validation of satellite altimetry by kinematic GNSS in central East Antarctica

2017 ◽  
Vol 11 (3) ◽  
pp. 1111-1130 ◽  
Author(s):  
Ludwig Schröder ◽  
Andreas Richter ◽  
Denis V. Fedorov ◽  
Lutz Eberlein ◽  
Evgeny V. Brovkov ◽  
...  
Keyword(s):  
Satellite Altimetry ◽  
Digital Elevation Models ◽  
Surface Elevation ◽  
Data Sets ◽  
Radar Altimetry ◽  
Independent Evidence ◽  
Ice Surface ◽  
Digital Elevation ◽  
Wide Range ◽  
Elevation Data

Abstract. Ice-surface elevation profiles of more than 30 000 km in total length are derived from kinematic GNSS (GPS and the Russian GLONASS) observations on sledge convoy vehicles along traverses between Vostok Station and the East Antarctic coast. These profiles have accuracies between 4 and 9 cm. They are used to validate elevation data sets from both radar and laser satellite altimetry as well as four digital elevation models. A crossover analysis with three different processing versions of Envisat radar altimetry elevation profiles yields a clear preference for the relocation method over the direct method of slope correction and for threshold retrackers over functional fit algorithms. The validation of CryoSat-2 low-resolution mode and SARIn mode data sets documents the progress made from baseline B to C elevation products. ICESat laser altimetry data are demonstrated to be accurate to a few decimetres over a wide range of surface slopes. A crossover adjustment in the region of subglacial Lake Vostok combining ICESat elevation data with our GNSS profiles yields a new set of ICESat laser campaign biases and provides new, independent evidence for the stability of the ice-surface elevation above the lake. The evaluation of the digital elevation models reveals the benefits of combining laser and radar altimetry.

scholarly journals Arctic Sea Ice Surface Roughness Estimated from Multi-Angular Reflectance Satellite Imagery

2018 ◽  
Vol 11 (1) ◽  
pp. 50 ◽  
Author(s):  
Anne Nolin ◽  
Eugene Mar
Keyword(s):  
Surface Roughness ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
Ice Age ◽  
Ice Surface ◽  
Ice Roughness ◽  
Arctic Sea ◽  
Angular Reflectance ◽  
Ice Surface Roughness ◽  
Range Of Values

Sea ice surface roughness affects ice-atmosphere interactions, serves as an indicator of ice age, shows patterns of ice convergence and divergence, affects the spatial extent of summer meltponds, and affects ice albedo. We have developed a method for mapping sea ice surface roughness using angular reflectance data from the Multi-angle Imaging SpectroRadiometer (MISR) and lidar-derived roughness measurements from the Airborne Topographic Mapper (ATM). Using an empirical data modeling approach, we derived estimates of Arctic sea ice roughness ranging from centimeters to decimeters within the MISR 275-m pixel size. Using independent ATM data for validation, we find that histograms of lidar and multi-angular roughness values were nearly identical for areas with a roughness < 20 cm, but for rougher regions, the MISR-estimated roughness had a narrower range of values than the ATM data. The algorithm was able to accurately identify areas that transition between smooth and rough ice. Because of its coarser spatial scale, MISR-estimated roughness data have a variance about half that of ATM roughness data.

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