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Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 20323

Special Issue Editors


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Guest Editor
Department of Physics, Shirshov Institute of Oceanology, Russian Academy of Sciences, 117997 Moscow, Russia
Interests: marine remote sensing; satellite remote sensing; aerial remote sensing; coastal waters; river plumes; ocean dynamics; inland seas; Arctic Ocean; Southern Ocean
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Remote Sensing Department, Marine Hydrophysical Institute of RAS, Sevastopol 299011, Russia
Interests: altimetry; mesoscale and submesoscale eddies; ocean dynamics; biooptical properties
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Marine Hydrophysical Institute of RAS, Sevastopol, Russia
Interests: remote sensing; SAR imaging; mesoscale and submesoscale ocean dynamics; surface currents; internal waves; eddies; fronts; Arctic Ocean
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Arctic and Antarctic oceans have been regions of unprecedented scientific interest during the last few decades due to their great influence on the ongoing climate change. The Arctic and Antarctic oceans are among the most susceptible regions to climate change in the world, experiencing drastic warming and decline of sea ice cover, processes which strongly influence global climate and global thermohaline circulation. Moreover, the Arctic and Antarctic oceans contain large continental margins with vast mineral and biological marine resources. As a result, studies of ocean and sea ice dynamics and their impact on the thermohaline structure and biological productivity in these oceans are of paramount scientific importance on a global scale.

Remote sensing studies are especially important in the poorly sampled Arctic and Antarctic region due to their remoteness and extreme weather conditions. Satellite and airborne observations can significantly substitute sparse and limited in situ data collected in the Arctic and Antarctic oceans. Joint analysis of remote sensing observations, in situ data, and results of numerical modeling is very efficient for understanding complex processes in these regions.

Different remote sensing products are used for scientific research of ocean and sea ice dynamics in the Arctic and Antarctic oceans. Ocean color in the Arctic and Antarctic oceans is governed by multiple physical, biological, and geochemical processes, including algae blooms, spreading of large river plumes, coastal erosion and coastal upwelling, eddy lateral advection, and others. Active and passive microwave measurements are widely used to detect sea ice and study its properties, dynamics, and ice cover variability on different spatial and temporal scales. Recent progress in development of sea surface salinity algorithms for the Arctic and Antarctic oceans holds promise to provide improved quantitative assessments and new insights into delivery, spreading, and transformation of freshwater discharge in these regions. Satellite altimetry data have demonstrated their effectiveness in studying geostrophic currents, large eddies, and variations of sea level in the Arctic and Antarctic oceans caused by the ongoing changes in the large-scale water balance.

In this Special Issue, we encourage submissions focusing on remote sensing of ocean and sea ice dynamics in the Arctic and Antarctic oceans, including, but not limited to:

  • Ocean circulation, currents, and waves;
  • Sea ice dynamics and ice cover variability on different spatial and temporal scales;
  • Sub-mesoscale and mesoscale dynamic processes, including eddies, internal waves, fronts and filaments;
  • Coastal erosion, coastal upwelling, and other marine processes in the coastal and shelf areas;
  • Variations of sea level and the large-scale water balance;
  • Spreading of river plumes and large-scale freshwater transport in the Arctic Ocean;
  • Impact of dynamic processes on biological characteristics and mixing properties of the Arctic and Antarctic oceans;
  • Atmosphere–ice–ocean interaction processes.

Dr. Alexander Osadchiev
Dr. Arseny Kubryakov
Dr. Igor E. Kozlov
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • satellite remote sensing
  • aerial remote sensing
  • ocean circulation
  • sea ice circulation
  • polar ice cover
  • coastal processes
  • mesoscale and sub-mesoscale ocean dynamics
  • river plumes
  • freshwater transport
  • eddies
  • fronts
  • internal waves
  • high latitudes
  • Arctic Ocean
  • Antarctic Ocean

Published Papers (8 papers)

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26 pages, 7878 KiB  
Article
Internal Solitary Waves in the White Sea: Hot-Spots, Structure, and Kinematics from Multi-Sensor Observations
by Igor E. Kozlov, Oksana A. Atadzhanova and Alexey V. Zimin
Remote Sens. 2022, 14(19), 4948; https://doi.org/10.3390/rs14194948 - 3 Oct 2022
Cited by 4 | Viewed by 1621
Abstract
A detailed picture of internal solitary waves (ISWs) in the White Sea is presented based on an analysis of historical spaceborne synthetic aperture radar (SAR) data and field measurements. The major hot-spot of ISW generation locates in the southwestern (SW) Gorlo Strait (GS), [...] Read more.
A detailed picture of internal solitary waves (ISWs) in the White Sea is presented based on an analysis of historical spaceborne synthetic aperture radar (SAR) data and field measurements. The major hot-spot of ISW generation locates in the southwestern (SW) Gorlo Strait (GS), characterized by the presence of strong tides, complex topography, and two distinct fronts. Here, pronounced high-frequency isopycnal depressions of 5–8 m were regularly observed during flood and flood/ebb slackening. Other regions of pronounced ISW activity are found near Solovetsky Islands and in the northwestern Onega Bay. The spatial and kinematic properties of the observed ISWs are linked to water depth, with larger wave trains and higher propagation speeds being observed over the deep regions. Direct estimates of ISW propagation speeds from sequential and single SAR images agree well, while theoretical ones obtained using a two-layer model overestimate the observed values by 2–3 times. This is explained by the effective modulation of ISW propagation speed during the tidal cycle by background currents that are not accounted for in the model. Enhanced values of diapycnic diffusion coefficient in the pycnocline layer were registered near the frontal zones, where intense 14–17 m high ISWs were regularly observed. Full article
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21 pages, 8563 KiB  
Article
Variability and Formation Mechanism of Polynyas in Eastern Prydz Bay, Antarctica
by Saisai Hou and Jiuxin Shi
Remote Sens. 2021, 13(24), 5089; https://doi.org/10.3390/rs13245089 - 15 Dec 2021
Cited by 4 | Viewed by 2556
Abstract
Based on satellite remote sensing, several polynyas have been found in Prydz Bay, East Antarctica. Compared with the Mackenzie Bay Polynya, the only polynya in the west, the polynyas in eastern Prydz Bay have a larger area and higher ice production, but have [...] Read more.
Based on satellite remote sensing, several polynyas have been found in Prydz Bay, East Antarctica. Compared with the Mackenzie Bay Polynya, the only polynya in the west, the polynyas in eastern Prydz Bay have a larger area and higher ice production, but have never been studied individually. In this study, four recurrent polynyas were identified in eastern Prydz Bay from sea ice concentration data during 2002–2011. Their areas generally exhibit synchronous temporal variations and have good correlation with wind speed, which indicates that they are primarily wind-driven polynyas that need at least one stationary ice barrier to block the inflow of drifting sea ice. The components of the ice barriers of these four polynyas were identified through comparison of satellite remote sensing visible images and synthetic aperture radar images. All types of fast ice, including landfast ice, offshore fast ice and ice fingers serving as ice barriers for these polynyas are anchored by an assemblage of small icebergs and have an approximately year-round period of variations that also regulates the variability of polynyas. The movement and grounding of giant icebergs near the polynyas significantly affects the development of the polynyas. The results of this study illustrate the important impact of icebergs on Antarctic wind-driven polynyas and the formation of dense shelf water. Full article
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18 pages, 4164 KiB  
Article
Large River Plumes Detection by Satellite Altimetry: Case Study of the Ob–Yenisei Plume
by Dmitry Frey and Alexander Osadchiev
Remote Sens. 2021, 13(24), 5014; https://doi.org/10.3390/rs13245014 - 10 Dec 2021
Cited by 12 | Viewed by 2653
Abstract
Satellite altimetry is an efficient instrument for detection dynamical processes in the World Ocean, including reconstruction of geostrophic currents and tracking of mesoscale eddies. Satellite altimetry has the potential to detect large river plumes, which have reduced salinity and, therefore, elevated surface level [...] Read more.
Satellite altimetry is an efficient instrument for detection dynamical processes in the World Ocean, including reconstruction of geostrophic currents and tracking of mesoscale eddies. Satellite altimetry has the potential to detect large river plumes, which have reduced salinity and, therefore, elevated surface level as compared to surrounding saline sea. In this study, we analyze applicability of satellite altimetry for detection of the Ob–Yenisei plume in the Kara Sea, which is among the largest river plumes in the World Ocean. Based on the extensive in situ data collected at the study area during oceanographic surveys in 2007–2019, we analyze the accuracy and efficiency of satellite altimetry in reproducing, first, the outer boundary of the plume and, second, the internal structure of the plume. We reveal that the value of positive level anomaly within the Ob–Yenisei plume strongly depends on the vertical plume structure and is prone to significant synoptic and seasonal variability due to wind forcing and mixing of the plume with subjacent sea. As a result, despite generally high statistical correlation between the ADT and surface salinity, straightforward usage of ADT for detection of the river plume is incorrect and produces misleading results. Satellite altimetry could provide correct information about spatial extents and shape of the Ob–Yenisei plume only if it is validated by synchronous in situ measurements. Full article
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31 pages, 3784 KiB  
Article
Marine Heatwaves in Siberian Arctic Seas and Adjacent Region
by Elena Golubeva, Marina Kraineva, Gennady Platov, Dina Iakshina and Marina Tarkhanova
Remote Sens. 2021, 13(21), 4436; https://doi.org/10.3390/rs13214436 - 4 Nov 2021
Cited by 12 | Viewed by 2599
Abstract
We used a satellite-derived global daily sea surface temperature (SST) dataset with resolution 0.25 × 0.25 to analyze interannual changes in the Arctic Shelf seas from 2000 to 2020 and to reveal extreme events in SST distribution. Results show that the second [...] Read more.
We used a satellite-derived global daily sea surface temperature (SST) dataset with resolution 0.25 × 0.25 to analyze interannual changes in the Arctic Shelf seas from 2000 to 2020 and to reveal extreme events in SST distribution. Results show that the second decade of the 21st century for the Siberian Arctic seas turned significantly warmer than the first decade, and the increase in SST in the Arctic seas could be considered in terms of marine heatwaves. Analyzing the spatial distribution of heatwaves and their characteristics, we showed that from 2018 to 2020, the surface warming extended to the northern deep-water region of the Laptev Sea 75 to 81N. To reveal the most important forcing for the northward extension of the marine heatwaves, we used three-dimensional numerical modeling of the Arctic Ocean based on a sea-ice and ocean model forced by the NCEP/NCAR Reanalysis. The simulation of the Arctic Ocean variability from 2000 to 2020 showed marine heatwaves and their increasing intensity in the northern region of the Kara and Laptev seas, closely connected to the disappearance of ice cover. A series of numerical experiments on the sensitivity of the model showed that the main factors affecting the Arctic sea-ice loss and the formation of anomalous temperature north of the Siberian Arctic seas are equally the thermal and dynamic effects of the atmosphere. Numerical modeling allows us to examine the impact of other physical mechanisms as well. Among them were the state of the ocean and winter sea ice, the formation of fast ice polynias and riverine heat influx. Full article
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20 pages, 10246 KiB  
Article
Interannual Variability of the Lena River Plume Propagation in 1993–2020 during the Ice-Free Period on the Base of Satellite Salinity, Temperature, and Altimetry Measurements
by Vladislav R. Zhuk and Arseny Alexandrovich Kubryakov
Remote Sens. 2021, 13(21), 4252; https://doi.org/10.3390/rs13214252 - 22 Oct 2021
Cited by 9 | Viewed by 1788
Abstract
The Lena River plume significantly affects the thermohaline, optical and chemical properties of the eastern Arctic seas. We use sea surface salinity (SSS), temperature (SST), and altimetry measurements to study features of the Lena plume propagation during 1993–2020. A comparison of Soil Moisture [...] Read more.
The Lena River plume significantly affects the thermohaline, optical and chemical properties of the eastern Arctic seas. We use sea surface salinity (SSS), temperature (SST), and altimetry measurements to study features of the Lena plume propagation during 1993–2020. A comparison of Soil Moisture Active Passive (SMAP) SSS measurements with in situ data obtained using the flow-through system in oceanographic surveys in 2018–2019 demonstrates good coincidence with correlation ~ 0.96 and RMSD ~ 1 psu. The SMAP data were used to reconstruct the plume evolution in 2015–2020 and to identify three main types of Lena plume propagation, which are mainly related to the variability of dominant zonal wind direction: «northern»—the plume moves to the north from the delta up to 78° N; «eastern»—the plume moves eastward along the Siberian coast up to 180° E; «mixed» between two main types. Brackish plume waters were characterized by increased temperature and sea level, which provides the opportunity for studying the Lena plume dynamics using satellite altimetry and infrared measurements. These data were analyzed to study the interannual variability of plume propagation during the ice-free period of 1993–2020. The obtained results show that the «northern» type is observed twice more often than the «eastern» one, but the «eastern» type has intensified since 2010. Full article
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19 pages, 5622 KiB  
Article
Ground-Based Radar Interferometry of Sea Ice
by Dyre Oliver Dammann, Mark A. Johnson, Emily R. Fedders, Andrew R. Mahoney, Charles L. Werner, Christopher M. Polashenski, Franz J. Meyer and Jennifer K. Hutchings
Remote Sens. 2021, 13(1), 43; https://doi.org/10.3390/rs13010043 - 24 Dec 2020
Cited by 5 | Viewed by 3467 | Correction
Abstract
In light of recent Arctic change, there is a need to better understand sea ice dynamic processes at the floe scale to evaluate sea ice stability, deformation, and fracturing. This work investigates the use of the Gamma portable radar interferometer (GPRI) to characterize [...] Read more.
In light of recent Arctic change, there is a need to better understand sea ice dynamic processes at the floe scale to evaluate sea ice stability, deformation, and fracturing. This work investigates the use of the Gamma portable radar interferometer (GPRI) to characterize sea ice displacement and surface topography. We find that the GPRI is best suited to derive lateral surface deformation due to mm-scale horizontal accuracy. We model interferometric phase signatures from sea ice displacement and evaluate possible errors related to noise and antenna motion. We compare the analysis with observations acquired during a drifting ice camp in the Beaufort Sea. We used repeat-scan and stare-mode interferometry to identify two-dimensional shear and to track continuous uni-directional convergence. This paper demonstrates the capacity of the GPRI to derive surface strain on the order of 10−7 and identify different dynamic regions based on sub-mm changes in displacement. The GPRI is thus a promising tool for sea ice applications due to its high accuracy that can potentially resolve pre- and post-fracture deformation relevant to sea ice stability and modeling. Full article
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19 pages, 6675 KiB  
Article
Classification of Ice in Lützow-Holm Bay, East Antarctica, Using Data from ASCAT and AMSR2
by Seita Hoshino, Kazutaka Tateyama and Koh Izumiyama
Remote Sens. 2020, 12(19), 3179; https://doi.org/10.3390/rs12193179 - 28 Sep 2020
Cited by 2 | Viewed by 2663
Abstract
This paper presents an ice classification algorithm based on combined active and passive microwave radiometer data in Lützow-Holm Bay (LHB), East Antarctica. The ice classification algorithm is developed based on the threshold values of an advanced scatterometer (ASCAT) and advanced microwave scanning radiometer [...] Read more.
This paper presents an ice classification algorithm based on combined active and passive microwave radiometer data in Lützow-Holm Bay (LHB), East Antarctica. The ice classification algorithm is developed based on the threshold values of an advanced scatterometer (ASCAT) and advanced microwave scanning radiometer 2 (here, AMSR2). These values are calculated via the features of various ice types, including open ice, first-year (FY) ice, multi-year (MY) ice, MY ice including icebergs (MY IB), ice shelves, coastal ice sheets, and inland ice sheets. To verify the validity of the ice classification algorithm, the algorithm results are compared with visual observation data and satellite imagery. Except for the flaw polynya and area with surface melting, the FY ice, MY ice, and the ice shelf areas estimated here using the proposed ice classification algorithm match those discernible from the verification data. Inter-annual changes in the areal extents of FY ice, MY ice, and the ice shelves are investigated here using the proposed ice classification algorithm. Investigation of MY ice and ice shelf areas revealed that the breakup of MY ice induced a breakup of an ice shelf. A comparison of the FY ice and MY ice areas showed the replacement of these ice types. The proposed ice classification algorithm can detect ice breakup events as quantitative changes in the distribution and ice type. In future work, we plan to classify sea ice in other sea ice areas, applying the proposed algorithm throughout the Antarctic region. Full article
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2 pages, 1181 KiB  
Correction
Correction: Dammann et al. Ground-Based Radar Interferometry of Sea Ice. Remote Sens. 2021, 13, 43
by Dyre Oliver Dammann, Mark A. Johnson, Emily R. Fedders, Andrew R. Mahoney, Charles L. Werner, Christopher M. Polashenski, Franz J. Meyer and Jennifer K. Hutchings
Remote Sens. 2022, 14(1), 156; https://doi.org/10.3390/rs14010156 - 30 Dec 2021
Viewed by 1497
Abstract
In the original article [...] Full article
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