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26 pages, 7878 KiB

Open AccessArticle

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 1576

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

(This article belongs to the Special Issue Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans)

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21 pages, 8563 KiB

Open AccessArticle

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 2488

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

(This article belongs to the Special Issue Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans)

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18 pages, 4164 KiB

Open AccessArticle

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 2605

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

(This article belongs to the Special Issue Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans)

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31 pages, 3784 KiB

Open AccessArticle

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 2519

Abstract

We used a satellite-derived global daily sea surface temperature (SST) dataset with resolution 0.25 × 0.25

^{\circ}

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

^{\circ}

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

^{\circ}

to 81

^{\circ}

N. 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

(This article belongs to the Special Issue Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans)

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20 pages, 10246 KiB

Open AccessArticle

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 1743

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

(This article belongs to the Special Issue Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans)

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19 pages, 5622 KiB

Open AccessArticle

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 3416 | 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

(This article belongs to the Special Issue Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans)

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19 pages, 6675 KiB

Open AccessArticle

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 2628

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

(This article belongs to the Special Issue Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans)

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Other

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2 pages, 1181 KiB

Open AccessCorrection

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 1475

Abstract

In the original article [...] Full article

(This article belongs to the Special Issue Remote Sensing of Ocean and Sea Ice Dynamics in the Arctic and Antarctic Oceans)

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