Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.9
5.0
Journals
Remote Sensing
Special Issues
Remote Sensing of Changing Arctic Sea Ice
remotesensing-logo
Submit to Remote Sensing Review for Remote Sensing Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Remote Sensing of Changing Arctic Sea Ice

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

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 12595

Special Issue Editors

Dr. Byongjun (Phil) Hwang

E-Mail Website
Guest Editor
Department of Biological and Geographical Sciences, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
Interests: sea ice; SAR; remote sensing; ice dynamics
Dr. Michel Tsamados

E-Mail Website
Guest Editor
Centre for Polar Observation and Modelling, Earth Science, University College London, London WC1E 6BT, UK
Interests: remote sensing; modelling sea ice; polar oceanography; rheology
Dr. Hyun-Cheol Kim

E-Mail Website
Guest Editor
Center of Remote Sensing and GIS, Korea Polar Research Institute, Incheon 21990, Korea
Interests: sea ice; ocean colour; climate change; UAV
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Arctic Ocean is undergoing a continuous, rapid transformation into a seasonal ice cover, which demands a new understanding of the physics and processes of this new Arctic. At the same time, we see an explosion of remotely sensed data generated from ground-based instruments and airborne and satellite sensors, and technological advances are being made in monitoring Arctic sea ice. Such data sets and methods are vital to enhance our understanding of the sea ice dynamic and thermodynamic processes and consequent effects on the biogeochemical properties and air–sea interactions in the Arctic marine environment. This Special Issue, “Remote Sensing of Changing Arctic Sea Ice”, invites original studies on all aspects of Arctic sea ice remote sensing, especially those involving emerging data sets and innovative methods to investigate sea ice dynamic and thermodynamic processes and research integrating remotely sensed data to examine the effects of air–sea interactions and biogeochemical processes within the changing Arctic Ocean. In what has recently been referred to as a new golden era for polar remote sensing following the successes of CryoSat-2 (celebrating its 10th anniversary), other radar altimetry missions, and the recent launch of ICESat-2, we encourage submissions highlighting key results from these missions. We also welcome contributions from all polar monitoring satellites (SAR, optical, passive microwave, etc.) including from Small and CubeSat constellations, as well as future mission concepts, looking forward to extending and expanding the monitoring of this key region of our planet into the 2020s and 30s.

Dr. Byongjun (Phil) Hwang
Dr. Michel Tsamados
Dr. Hyun-Cheol Kim
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

  • arctic sea ice
  • remote sensing
  • thermodynamic
  • dynamic
  • biogeochemical
  • air–sea interactions

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 10357 KiB  
Article
Satellite Multi-Sensor Data Analysis of Unusually Strong Polar Lows over the Chukchi and Beaufort Seas in October 2017
by Irina Gurvich, Mikhail Pichugin and Anastasiya Baranyuk
Remote Sens. 2023, 15(1), 120; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15010120 - 26 Dec 2022
Cited by 2 | Viewed by 1257
Abstract
Polar lows (PLs) are intense mesoscale weather systems that often cause severe storm winds in the Nordic Seas but were considered as being exceedingly rare in the Pacific Arctic region before sea ice decline. Here, we explore four PLs observed on 18–22 October [...] Read more.
Polar lows (PLs) are intense mesoscale weather systems that often cause severe storm winds in the Nordic Seas but were considered as being exceedingly rare in the Pacific Arctic region before sea ice decline. Here, we explore four PLs observed on 18–22 October 2017 in the Chukchi and Beaufort Seas—an area with an exceptionally sparse observation network. The study is based on the combined use of the satellite microwave measurements, as well as infrared imagery, the ERA5, MERRA-2 and NCEP-CFSv2 reanalysis data sets. An unusually strong PLs pair developed near the marginal ice zone during a marine-cold air outbreak in anomalously low sea ice extent conditions. PLs pair moved southward as a mesocyclonic system called the “merry-go-round”, under the upper-level tropospheric vortex with a cold core. Multi-sensor satellite measurements show that, in the mature stage, a PL pair had near-surface wind speeds (W) close to hurricane force—over 30 m/s. Comparison analysis of W distributions within the strongest PL showed that all reanalysis data sets reasonably reproduce the PL median wind speed but underestimate its extreme values by 15–23%. The reanalysis data sets detected only two PLs with horizontal scales of over 220 km. Tracks of identified PLs for all data sets are in good agreement with the ones obtained from satellite images capturing the main features of the mesoscale weather system propagation. For the track of the strongest PL event, ERA5 exhibited the most accordance with satellite observations with a tracking error of 50–60 km. Full article
(This article belongs to the Special Issue Remote Sensing of Changing Arctic Sea Ice)
►▼ Show Figures

Graphical abstract

25 pages, 29040 KiB  
Article
Mapping Arctic Sea-Ice Surface Roughness with Multi-Angle Imaging SpectroRadiometer
by Thomas Johnson, Michel Tsamados, Jan-Peter Muller and Julienne Stroeve
Remote Sens. 2022, 14(24), 6249; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14246249 - 09 Dec 2022
Cited by 4 | Viewed by 2455
Abstract
Sea-ice surface roughness (SIR) is a crucial parameter in climate and oceanographic studies, constraining momentum transfer between the atmosphere and ocean, providing preconditioning for summer-melt pond extent, and being related to ice age and thickness. High-resolution roughness estimates from airborne laser measurements are [...] Read more.
Sea-ice surface roughness (SIR) is a crucial parameter in climate and oceanographic studies, constraining momentum transfer between the atmosphere and ocean, providing preconditioning for summer-melt pond extent, and being related to ice age and thickness. High-resolution roughness estimates from airborne laser measurements are limited in spatial and temporal coverage while pan-Arctic satellite roughness does not extend over multi-decadal timescales. Launched on the Terra satellite in 1999, the NASA Multi-angle Imaging SpectroRadiometer (MISR) instrument acquires optical imagery from nine near-simultaneous camera view zenith angles. Extending on previous work to model surface roughness from specular anisotropy, a training dataset of cloud-free angular reflectance signatures and surface roughness, defined as the standard deviation of the within-pixel lidar elevations, from near-coincident operation IceBridge (OIB) airborne laser data is generated and is modelled using support vector regression (SVR) with a radial basis function (RBF) kernel selected. Blocked k-fold cross-validation is implemented to tune hyperparameters using grid optimisation and to assess model performance, with an R2 (coefficient of determination) of 0.43 and MAE (mean absolute error) of 0.041 m. Product performance is assessed through independent validation by comparison with unseen similarly generated surface-roughness characterisations from pre-IceBridge missions (Pearson’s r averaged over six scenes, r = 0.58, p < 0.005), and with AWI CS2-SMOS sea-ice thickness (Spearman’s rank, rs = 0.66, p < 0.001), a known roughness proxy. We present a derived sea-ice roughness product at 1.1 km resolution (2000–2020) over the seasonal period of OIB operation and a corresponding time-series analysis. Both our instantaneous swaths and pan-Arctic monthly mosaics show considerable potential in detecting surface-ice characteristics such as deformed rough ice, thin refrozen leads, and polynyas. Full article
(This article belongs to the Special Issue Remote Sensing of Changing Arctic Sea Ice)
►▼ Show Figures

Figure 1

17 pages, 13732 KiB  
Article
A 20-Year Climatology of Sea Ice Leads Detected in Infrared Satellite Imagery Using a Convolutional Neural Network
by Jay P. Hoffman, Steven A. Ackerman, Yinghui Liu and Jeffrey R. Key
Remote Sens. 2022, 14(22), 5763; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14225763 - 15 Nov 2022
Cited by 7 | Viewed by 1747
Abstract
Sea ice leads, or fractures account for a small proportion of the Arctic Ocean surface area, but play a critical role in the energy and moisture exchanges between the ocean and atmosphere. As the sea ice area and volume in the Arctic has [...] Read more.
Sea ice leads, or fractures account for a small proportion of the Arctic Ocean surface area, but play a critical role in the energy and moisture exchanges between the ocean and atmosphere. As the sea ice area and volume in the Arctic has declined over the past few decades, changes in sea ice leads have not been studied as extensively. A recently developed approach uses artificial intelligence (AI) and satellite thermal infrared window data to build a twenty-year archive of sea ice lead detects with Moderate Resolution Imaging Spectroradiometer (MODIS) and later, an archive from Visible Infrared Imaging Radiometer Suite (VIIRS). The results are now available and show significant improvement over previously published methods. The AI method results have higher detection rates and a high level detection agreement between MODIS and VIIRS. Analysis over the winter season from 2002–2003 through to the 2021–2022 archive reveals lead detections have a small decreasing trend in lead area that can be attributed to increasing cloud cover in the Arctic. This work reveals that leads are becoming increasingly difficult to detect rather than less likely to occur. Although the trend is small and on the same order of magnitude as the uncertainty, leads are likely increasing at a rate of 3700 km2 per year with a range of uncertainty of 3500 km2 after the impact of cloud cover changes are removed. Full article
(This article belongs to the Special Issue Remote Sensing of Changing Arctic Sea Ice)
►▼ Show Figures

Figure 1

22 pages, 10939 KiB  
Article
A New Perspective on Four Decades of Changes in Arctic Sea Ice from Satellite Observations
by Xuanji Wang, Yinghui Liu, Jeffrey R. Key and Richard Dworak
Remote Sens. 2022, 14(8), 1846; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14081846 - 12 Apr 2022
Cited by 8 | Viewed by 3033
Abstract
Arctic sea ice characteristics have been changing rapidly and significantly in the last few decades. Using a long-term time series of sea ice products from satellite observations—the extended AVHRR Polar Pathfinder (APP-x)—trends in sea ice concentration, ice extent, ice thickness, and ice volume [...] Read more.
Arctic sea ice characteristics have been changing rapidly and significantly in the last few decades. Using a long-term time series of sea ice products from satellite observations—the extended AVHRR Polar Pathfinder (APP-x)—trends in sea ice concentration, ice extent, ice thickness, and ice volume in the Arctic from 1982 to 2020 are investigated. Results show that the Arctic has become less ice-covered in all seasons, especially in summer and autumn. Arctic sea ice thickness has been decreasing at a rate of −3.24 cm per year, resulting in an approximate 52% reduction in thickness from 2.35 m in 1982 to 1.13 m in 2020. Arctic sea ice volume has been decreasing at a rate of −467.7 km3 per year, resulting in an approximate 63% reduction in volume, from 27,590.4 km3 in 1982 to 10,305.5 km3 in 2020. These trends are further examined from a new perspective, where the Arctic Ocean is classified into open water, perennial, and seasonal sea ice-covered areas based on sea ice persistence. The loss of the perennial sea ice-covered area is a major factor in the total sea ice loss in all seasons. If the current rates of sea ice changes in extent, concentration, and thickness continue, the Arctic is expected to have ice-free summers by the early 2060s. Full article
(This article belongs to the Special Issue Remote Sensing of Changing Arctic Sea Ice)
►▼ Show Figures

Graphical abstract

19 pages, 8043 KiB  
Article
CryoSat-2 Significant Wave Height in Polar Oceans Derived Using a Semi-Analytical Model of Synthetic Aperture Radar 2011–2019
by Harold Heorton, Michel Tsamados, Thomas Armitage, Andy Ridout and Jack Landy
Remote Sens. 2021, 13(20), 4166; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13204166 - 18 Oct 2021
Cited by 3 | Viewed by 2307
Abstract
This paper documents the retrieval of significant ocean surface wave heights in the Arctic Ocean from CryoSat-2 data. We use a semi-analytical model for an idealised synthetic aperture satellite radar or pulse-limited radar altimeter echo power. We develop a processing methodology that specifically [...] Read more.
This paper documents the retrieval of significant ocean surface wave heights in the Arctic Ocean from CryoSat-2 data. We use a semi-analytical model for an idealised synthetic aperture satellite radar or pulse-limited radar altimeter echo power. We develop a processing methodology that specifically considers both the Synthetic Aperture and Pulse Limited modes of the radar that change close to the sea ice edge within the Arctic Ocean. All CryoSat-2 echoes to date were matched by our idealised echo revealing wave heights over the period 2011–2019. Our retrieved data were contrasted to existing processing of CryoSat-2 data and wave model data, showing the improved fidelity and accuracy of the semi-analytical echo power model and the newly developed processing methods. We contrasted our data to in situ wave buoy measurements, showing improved data retrievals in seasonal sea ice covered seas. We have shown the importance of directly considering the correct satellite mode of operation in the Arctic Ocean where SAR is the dominant operating mode. Our new data are of specific use for wave model validation close to the sea ice edge and is available at the link in the data availability statement. Full article
(This article belongs to the Special Issue Remote Sensing of Changing Arctic Sea Ice)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop