Articles | Volume 17, issue 12
https://doi.org/10.5194/tc-17-5335-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-5335-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Dec 2023
Research article |
| 15 Dec 2023
| 15 Dec 2023
A comparison of constant false alarm rate object detection algorithms for iceberg identification in L- and C-band SAR imagery of the Labrador Sea
Laust Færch
CORRESPONDING AUTHOR
Center for Integrated Remote Sensing and Forecasting for Arctic Operations, Department of Physics and Technology, UiT – The Arctic University of Norway, 9019 Tromsø, Norway
Wolfgang Dierking
Center for Integrated Remote Sensing and Forecasting for Arctic Operations, Department of Physics and Technology, UiT – The Arctic University of Norway, 9019 Tromsø, Norway
Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bussestr. 24, 27570 Bremerhaven, Germany
Nick Hughes
Norwegian Meteorological Institute, Kirkegårdsvejen, 60, 9293 Tromsø, Norway
Anthony P. Doulgeris
Center for Integrated Remote Sensing and Forecasting for Arctic Operations, Department of Physics and Technology, UiT – The Arctic University of Norway, 9019 Tromsø, Norway
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Jean Rabault, Trygve Halsne, Ana Carrasco, Anton Korosov, Joey Voermans, Patrik Bohlinger, Jens Boldingh Debernard, Malte Müller, Øyvind Breivik, Takehiko Nose, Gaute Hope, Fabrice Collard, Sylvain Herlédan, Tsubasa Kodaira, Nick Hughes, Qin Zhang, Kai Haakon Christensen, Alexander Babanin, Lars Willas Dreyer, Cyril Palerme, Lotfi Aouf, Konstantinos Christakos, Atle Jensen, Johannes Röhrs, Aleksey Marchenko, Graig Sutherland, Trygve Kvåle Løken, and Takuji Waseda
EGUsphere, https://doi.org/10.48550/arXiv.2401.07619, https://doi.org/10.48550/arXiv.2401.07619, 2024
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We observe strongly modulated waves-in-ice significant wave height using buoys deployed East of Svalbard. We show that these observations likely cannot be explained by wave-current interaction or tide-induced modulation alone. We also demonstrate a strong correlation between the waves height modulation, and the rate of sea ice convergence. Therefore, our data suggest that the rate of sea ice convergence and divergence may modulate wave in ice energy dissipation.
Are Frode Kvanum, Cyril Palerme, Malte Müller, Jean Rabault, and Nick Hughes
EGUsphere, https://doi.org/10.5194/egusphere-2023-3107, https://doi.org/10.5194/egusphere-2023-3107, 2024
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Recent studies have shown that machine learning models are effective at predicting sea ice concentration, yet few have explored the development of such models in an operational context. In this study, we present the development of a machine learning forecasting system which can predict sea ice concentration at 1 km resolution, up to 3 days ahead using real time operational data. The developed forecasts predict the sea ice edge position with a better accuracy than physical and baseline forecasts.
Qin Zhang and Nick Hughes
The Cryosphere, 17, 5519–5537, https://doi.org/10.5194/tc-17-5519-2023, https://doi.org/10.5194/tc-17-5519-2023, 2023
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To alleviate tedious manual image annotations for training deep learning (DL) models in floe instance segmentation, we employ a classical image processing technique to automatically label floes in images. We then apply a DL semantic method for fast and adaptive floe instance segmentation from high-resolution airborne and satellite images. A post-processing algorithm is also proposed to refine the segmentation and further to derive acceptable floe size distributions at local and global scales.
Wenkai Guo, Polona Itkin, Suman Singha, Anthony P. Doulgeris, Malin Johansson, and Gunnar Spreen
The Cryosphere, 17, 1279–1297, https://doi.org/10.5194/tc-17-1279-2023, https://doi.org/10.5194/tc-17-1279-2023, 2023
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Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect and achieve good results, as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.
Wenkai Guo, Polona Itkin, Johannes Lohse, Malin Johansson, and Anthony Paul Doulgeris
The Cryosphere, 16, 237–257, https://doi.org/10.5194/tc-16-237-2022, https://doi.org/10.5194/tc-16-237-2022, 2022
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This study uses radar satellite data categorized into different sea ice types to detect ice deformation, which is significant for climate science and ship navigation. For this, we examine radar signal differences of sea ice between two similar satellite sensors and show an optimal way to apply categorization methods across sensors, so more data can be used for this purpose. This study provides a basis for future reliable and constant detection of ice deformation remotely through satellite data.
Luisa von Albedyll, Christian Haas, and Wolfgang Dierking
The Cryosphere, 15, 2167–2186, https://doi.org/10.5194/tc-15-2167-2021, https://doi.org/10.5194/tc-15-2167-2021, 2021
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Convergent sea ice motion produces a thick ice cover through ridging. We studied sea ice deformation derived from high-resolution satellite imagery and related it to the corresponding thickness change. We found that deformation explains the observed dynamic thickness change. We show that deformation can be used to model realistic ice thickness distributions. Our results revealed new relationships between thickness redistribution and deformation that could improve sea ice models.
Yu Zhang, Tingting Zhu, Gunnar Spreen, Christian Melsheimer, Marcus Huntemann, Nick Hughes, Shengkai Zhang, and Fei Li
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-85, https://doi.org/10.5194/tc-2021-85, 2021
Revised manuscript not accepted
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We developed an algorithm for ice-water classification using Sentinel-1 data during melting seasons in the Fram Strait. The proposed algorithm has the OA of nearly 90 % with STD less than 10 %. The comparison of sea ice concentration demonstrate that it can provide detailed information of sea ice with the spatial resolution of 1km. The time series shows the average June to September sea ice area does not change so much in 2015–2017 and 2019–2020, but it has a significant decrease in 2018.
Wolfgang Dierking, Harry L. Stern, and Jennifer K. Hutchings
The Cryosphere, 14, 2999–3016, https://doi.org/10.5194/tc-14-2999-2020, https://doi.org/10.5194/tc-14-2999-2020, 2020
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Monitoring deformation of sea ice is useful for studying effects of ice compression and divergent motion on the ice mass balance and ocean–ice–atmosphere interactions. In calculations of deformation parameters not only the measurement uncertainty of drift vectors has to be considered. The size of the area and the time interval used in the calculations have to be chosen within certain limits to make sure that the uncertainties of deformation parameters are smaller than their real magnitudes.
Wolfgang Dierking, Oliver Lang, and Thomas Busche
The Cryosphere, 11, 1967–1985, https://doi.org/10.5194/tc-11-1967-2017, https://doi.org/10.5194/tc-11-1967-2017, 2017
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Information on the sea ice surface topography is valuable in geophysical investigations such as studies on atmosphere–sea ice interactions or sea ice mechanics. We investigated whether space-borne radar systems can be used to measure sea ice elevation. The answer is yes, but disturbing effects have to be considered, in particular sea ice drift and certain technical constraints. With future satellite radar missions, a fast wide-coverage acquisition of sea ice topography may be possible.
Ane S. Fors, Dmitry V. Divine, Anthony P. Doulgeris, Angelika H. H. Renner, and Sebastian Gerland
The Cryosphere, 11, 755–771, https://doi.org/10.5194/tc-11-755-2017, https://doi.org/10.5194/tc-11-755-2017, 2017
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This paper investigates the signature of melt ponds in satellite-borne synthetic aperture radar (SAR) imagery. A comparison between helicopter-borne images of drifting first-year ice and polarimetric X-band SAR images shows relations between observed melt pond fraction and several polarimetric SAR features. Melt ponds strongly influence the Arctic sea ice energy budget, and the results imply prospective opportunities for expanded monitoring of melt ponds from space.
Xi Zhang, Wolfgang Dierking, Jie Zhang, Junmin Meng, and Haitao Lang
The Cryosphere, 10, 1529–1545, https://doi.org/10.5194/tc-10-1529-2016, https://doi.org/10.5194/tc-10-1529-2016, 2016
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In this work, we introduced a parameter ("CP ratio") for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric SAR images. Based on a validation using other compact polarimetric SAR images from the Labrador Sea, we found a root mean square error of 8 cm and a maximum correlation coefficient of 0.94 for the retrieval procedure when applying it to level ice between 0.1 m and 0.8 m thick.
Ane S. Fors, Camilla Brekke, Anthony P. Doulgeris, Torbjørn Eltoft, Angelika H. H. Renner, and Sebastian Gerland
The Cryosphere, 10, 401–415, https://doi.org/10.5194/tc-10-401-2016, https://doi.org/10.5194/tc-10-401-2016, 2016
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This paper demonstrates how sea ice segmentation using high-resolution multi-polarisation synthetic aperture radar (SAR) can be used to retrieve valuable information about sea ice type during late summer. It adds knowledge to how choice of SAR features influence the information gain and highlights the sea ice segmentation capability of both the C and X band in late summer. The study contributes to an increased understanding of sea ice mapping and monitoring with SAR in the melt season.
M. -A. N. Moen, A. P. Doulgeris, S. N. Anfinsen, A. H. H. Renner, N. Hughes, S. Gerland, and T. Eltoft
The Cryosphere, 7, 1693–1705, https://doi.org/10.5194/tc-7-1693-2013, https://doi.org/10.5194/tc-7-1693-2013, 2013
A. Behrendt, W. Dierking, E. Fahrbach, and H. Witte
Earth Syst. Sci. Data, 5, 209–226, https://doi.org/10.5194/essd-5-209-2013, https://doi.org/10.5194/essd-5-209-2013, 2013
Related subject area
Discipline: Other | Subject: Freshwater Ice
Measurements of frazil ice flocs in rivers
Assessment of the impact of dam reservoirs on river ice cover – an example from the Carpathians (central Europe)
Forward modelling of synthetic-aperture radar (SAR) backscatter during lake ice melt conditions using the Snow Microwave Radiative Transfer (SMRT) model
Fusion of Landsat 8 Operational Land Imager and Geostationary Ocean Color Imager for hourly monitoring surface morphology of lake ice with high resolution in Chagan Lake of Northeast China
Mechanisms and effects of under-ice warming water in Ngoring Lake of Qinghai–Tibet Plateau
Tricentennial trends in spring ice break-ups on three rivers in northern Europe
Climate warming shortens ice durations and alters freeze and break-up patterns in Swedish water bodies
Sunlight penetration dominates the thermal regime and energetics of a shallow ice-covered lake in arid climate
Dam type and lake location characterize ice-marginal lake area change in Alaska and NW Canada between 1984 and 2019
River ice phenology and thickness from satellite altimetry: potential for ice bridge road operation and climate studies
Giant ice rings in southern Baikal: multi-satellite data help to study ice cover dynamics and eddies under ice
Ice roughness estimation via remotely piloted aircraft and photogrammetry
Analyses of Peace River Shallow Water Ice Profiling Sonar data and their implications for the roles played by frazil ice and in situ anchor ice growth in a freezing river
Creep and fracture of warm columnar freshwater ice
Climate change and Northern Hemisphere lake and river ice phenology from 1931–2005
Methane pathways in winter ice of a thermokarst lake–lagoon–coastal water transect in north Siberia
Continuous in situ measurements of anchor ice formation, growth, and release
Proglacial icings as records of winter hydrological processes
Investigation of spatial and temporal variability of river ice phenology and thickness across Songhua River Basin, northeast China
Observation-derived ice growth curves show patterns and trends in maximum ice thickness and safe travel duration of Alaskan lakes and rivers
Chuankang Pei, Jiaqi Yang, Yuntong She, and Mark Loewen
The Cryosphere, 18, 4177–4196, https://doi.org/10.5194/tc-18-4177-2024, https://doi.org/10.5194/tc-18-4177-2024, 2024
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Frazil flocs are aggregates of frazil ice particles that form in supercooled water. As they grow, they rise to the river surface, contributing to ice cover formation. We measured the properties of frazil flocs in rivers for the first time using underwater imaging. We found that the floc size distributions follow a lognormal distribution and mean floc size decreases linearly as the local Reynolds number increases. Floc volume concentration has a power law correlation with the relative depth.
Maksymilian Fukś
The Cryosphere, 18, 2509–2529, https://doi.org/10.5194/tc-18-2509-2024, https://doi.org/10.5194/tc-18-2509-2024, 2024
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This paper presents a method for determining the impact of dam reservoirs on the occurrence of ice cover on rivers downstream of their location. It was found that the operation of dam reservoirs reduces the duration of ice cover and significantly affects the ice regime of rivers. Based on the results presented, it can be assumed that dam reservoirs play an important role in transforming ice conditions on rivers.
Justin Murfitt, Claude Duguay, Ghislain Picard, and Juha Lemmetyinen
The Cryosphere, 18, 869–888, https://doi.org/10.5194/tc-18-869-2024, https://doi.org/10.5194/tc-18-869-2024, 2024
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This research focuses on the interaction between microwave signals and lake ice under wet conditions. Field data collected for Lake Oulujärvi in Finland were used to model backscatter under different conditions. The results of the modelling likely indicate that a combination of increased water content and roughness of different interfaces caused backscatter to increase. These results could help to identify areas where lake ice is unsafe for winter transportation.
Qian Yang, Xiaoguang Shi, Weibang Li, Kaishan Song, Zhijun Li, Xiaohua Hao, Fei Xie, Nan Lin, Zhidan Wen, Chong Fang, and Ge Liu
The Cryosphere, 17, 959–975, https://doi.org/10.5194/tc-17-959-2023, https://doi.org/10.5194/tc-17-959-2023, 2023
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A large-scale linear structure has repeatedly appeared on satellite images of Chagan Lake in winter, which was further verified as being ice ridges in the field investigation. We extracted the length and the angle of the ice ridges from multi-source remote sensing images. The average length was 21 141.57 ± 68.36 m. The average azimuth angle was 335.48° 141.57 ± 0.23°. The evolution of surface morphology is closely associated with air temperature, wind, and shoreline geometry.
Mengxiao Wang, Lijuan Wen, Zhaoguo Li, Matti Leppäranta, Victor Stepanenko, Yixin Zhao, Ruijia Niu, Liuyiyi Yang, and Georgiy Kirillin
The Cryosphere, 16, 3635–3648, https://doi.org/10.5194/tc-16-3635-2022, https://doi.org/10.5194/tc-16-3635-2022, 2022
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The under-ice water temperature of Ngoring Lake has been rising based on in situ observations. We obtained results showing that strong downward shortwave radiation is the main meteorological factor, and precipitation, wind speed, downward longwave radiation, air temperature, ice albedo, and ice extinction coefficient have an impact on the range and rate of lake temperature rise. Once the ice breaks, the lake body releases more energy than other lakes, whose water temperature remains horizontal.
Stefan Norrgård and Samuli Helama
The Cryosphere, 16, 2881–2898, https://doi.org/10.5194/tc-16-2881-2022, https://doi.org/10.5194/tc-16-2881-2022, 2022
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We examined changes in the dates of ice break-ups in three Finnish rivers since the 1700s. The analyses show that ice break-ups nowadays occur earlier in spring than in previous centuries. The changes are pronounced in the south, and both rivers had their first recorded years without a complete ice cover in the 21st century. These events occurred during exceptionally warm winters and show that climate extremes affect the river-ice regime in southwest Finland differently than in the north.
Sofia Hallerbäck, Laurie S. Huning, Charlotte Love, Magnus Persson, Katarina Stensen, David Gustafsson, and Amir AghaKouchak
The Cryosphere, 16, 2493–2503, https://doi.org/10.5194/tc-16-2493-2022, https://doi.org/10.5194/tc-16-2493-2022, 2022
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Using unique data, some dating back to the 18th century, we show a significant trend in shorter ice duration, later freeze, and earlier break-up dates across Sweden. In recent observations, the mean ice durations have decreased by 11–28 d and the chance of years with an extremely short ice cover duration (less than 50 d) have increased by 800 %. Results show that even a 1 °C increase in air temperatures can result in a decrease in ice duration in Sweden of around 8–23 d.
Wenfeng Huang, Wen Zhao, Cheng Zhang, Matti Leppäranta, Zhijun Li, Rui Li, and Zhanjun Lin
The Cryosphere, 16, 1793–1806, https://doi.org/10.5194/tc-16-1793-2022, https://doi.org/10.5194/tc-16-1793-2022, 2022
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Thermal regimes of seasonally ice-covered lakes in an arid region like Central Asia are not well constrained despite the unique climate. We observed annual and seasonal dynamics of thermal stratification and energetics in a shallow arid-region lake. Strong penetrated solar radiation and high water-to-ice heat flux are the predominant components in water heat balance. The under-ice stratification and convection are jointly governed by the radiative penetration and salt rejection during freezing.
Brianna Rick, Daniel McGrath, William Armstrong, and Scott W. McCoy
The Cryosphere, 16, 297–314, https://doi.org/10.5194/tc-16-297-2022, https://doi.org/10.5194/tc-16-297-2022, 2022
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Glacial lakes impact societies as both resources and hazards. Lakes form, grow, and drain as glaciers thin and retreat, and understanding lake evolution is a critical first step in assessing their hazard potential. We map glacial lakes in Alaska between 1984 and 2019. Overall, lakes grew in number and area, though lakes with different damming material (ice, moraine, bedrock) behaved differently. Namely, ice-dammed lakes decreased in number and area, a trend lost if dam type is not considered.
Elena Zakharova, Svetlana Agafonova, Claude Duguay, Natalia Frolova, and Alexei Kouraev
The Cryosphere, 15, 5387–5407, https://doi.org/10.5194/tc-15-5387-2021, https://doi.org/10.5194/tc-15-5387-2021, 2021
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The paper investigates the performance of altimetric satellite instruments to detect river ice onset and melting dates and to retrieve ice thickness of the Ob River. This is a first attempt to use satellite altimetry for monitoring ice in the challenging conditions restrained by the object size. A novel approach permitted elaboration of the spatiotemporal ice thickness product for the 400 km river reach. The potential of the product for prediction of ice road operation was demonstrated.
Alexei V. Kouraev, Elena A. Zakharova, Andrey G. Kostianoy, Mikhail N. Shimaraev, Lev V. Desinov, Evgeny A. Petrov, Nicholas M. J. Hall, Frédérique Rémy, and Andrey Ya. Suknev
The Cryosphere, 15, 4501–4516, https://doi.org/10.5194/tc-15-4501-2021, https://doi.org/10.5194/tc-15-4501-2021, 2021
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Giant ice rings are a beautiful and puzzling natural phenomenon. Our data show that ice rings are generated by lens-like warm eddies below the ice. We use multi-satellite data to analyse lake ice cover in the presence of eddies in April 2020 in southern Baikal. Unusual changes in ice colour may be explained by the competing influences of atmosphere above and the warm eddy below the ice. Tracking ice floes also helps to estimate eddy currents and their influence on the upper water layer.
James Ehrman, Shawn Clark, and Alexander Wall
The Cryosphere, 15, 4031–4046, https://doi.org/10.5194/tc-15-4031-2021, https://doi.org/10.5194/tc-15-4031-2021, 2021
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This research proposes and tests new methods for the estimation of the surface roughness of newly formed river ice covers. The hypothesis sought to determine if surface ice roughness was indicative of the subsurface. Ice roughness has consequences for winter flow characteristics of rivers and can greatly impact river ice jams. Remotely piloted aircraft and photogrammetry were used, and good correlation was found between the observed surface ice roughness and estimated subsurface ice roughness.
John R. Marko and David R. Topham
The Cryosphere, 15, 2473–2489, https://doi.org/10.5194/tc-15-2473-2021, https://doi.org/10.5194/tc-15-2473-2021, 2021
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Acoustic backscattering data from Peace River frazil events are interpreted to develop a quantitative model of interactions between ice particles in the water column and riverbed ice layers. Two generic behaviours, evident in observed time variability, are linked to differences in the relative stability of in situ anchor ice layers which develop at the beginning of each frazil interval and are determined by cooling rates. Changes in these layers are shown to control water column frazil content.
Iman E. Gharamti, John P. Dempsey, Arttu Polojärvi, and Jukka Tuhkuri
The Cryosphere, 15, 2401–2413, https://doi.org/10.5194/tc-15-2401-2021, https://doi.org/10.5194/tc-15-2401-2021, 2021
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We study the creep and fracture behavior of 3 m × 6 m floating edge-cracked rectangular plates of warm columnar freshwater S2 ice under creep/cyclic-recovery loading and monotonic loading to fracture. Under the testing conditions, the ice response was elastic–viscoplastic; no significant viscoelasticity or major recovery was detected. There was no clear effect of the creep/cyclic loading on the fracture properties: failure load and crack opening displacements at crack growth initiation.
Andrew M. W. Newton and Donal J. Mullan
The Cryosphere, 15, 2211–2234, https://doi.org/10.5194/tc-15-2211-2021, https://doi.org/10.5194/tc-15-2211-2021, 2021
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This paper investigates changes in the dates of ice freeze-up and breakup for 678 Northern Hemisphere lakes and rivers from 1931–2005. From 3510 time series, the results show that breakup dates have gradually occurred earlier through time, whilst freeze-up trends have tended to be significantly more variable. These data combined show that the number of annual open-water days has increased through time for most sites, with the magnitude of change at its largest in more recent years.
Ines Spangenberg, Pier Paul Overduin, Ellen Damm, Ingeborg Bussmann, Hanno Meyer, Susanne Liebner, Michael Angelopoulos, Boris K. Biskaborn, Mikhail N. Grigoriev, and Guido Grosse
The Cryosphere, 15, 1607–1625, https://doi.org/10.5194/tc-15-1607-2021, https://doi.org/10.5194/tc-15-1607-2021, 2021
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Thermokarst lakes are common on ice-rich permafrost. Many studies have shown that they are sources of methane to the atmosphere. Although they are usually covered by ice, little is known about what happens to methane in winter. We studied how much methane is contained in the ice of a thermokarst lake, a thermokarst lagoon and offshore. Methane concentrations differed strongly, depending on water body type. Microbes can also oxidize methane in ice and lower the concentrations during winter.
Tadros R. Ghobrial and Mark R. Loewen
The Cryosphere, 15, 49–67, https://doi.org/10.5194/tc-15-49-2021, https://doi.org/10.5194/tc-15-49-2021, 2021
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Anchor ice typically forms on riverbeds during freeze-up and can alter the river ice regime. Most of the knowledge on anchor ice mechanisms has been attributed to lab experiments. This study presents for the first time insights into anchor ice initiation, growth, and release in rivers using an underwater camera system. Three stages of growth and modes of release have been identified. These results will improve modelling capabilities in predicting the effect of anchor ice on river ice regimes.
Anna Chesnokova, Michel Baraër, and Émilie Bouchard
The Cryosphere, 14, 4145–4164, https://doi.org/10.5194/tc-14-4145-2020, https://doi.org/10.5194/tc-14-4145-2020, 2020
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In the context of a ubiquitous increase in winter discharge in cold regions, our results show that icing formations can help overcome the lack of direct observations in these remote environments and provide new insights into winter runoff generation. The multi-technique approach used in this study provided important information about the water sources active during the winter season in the headwaters of glacierized catchments.
Qian Yang, Kaishan Song, Xiaohua Hao, Zhidan Wen, Yue Tan, and Weibang Li
The Cryosphere, 14, 3581–3593, https://doi.org/10.5194/tc-14-3581-2020, https://doi.org/10.5194/tc-14-3581-2020, 2020
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Using daily ice records of 156 hydrological stations across Songhua River Basin, we examined the spatial variability in the river ice phenology and river ice thickness from 2010 to 2015 and explored the role of snow depth and air temperature on the ice thickness. Snow cover correlated with ice thickness significantly and positively when the freshwater was completely frozen. Cumulative air temperature of freezing provides a better predictor than the air temperature for ice thickness modeling.
Christopher D. Arp, Jessica E. Cherry, Dana R. N. Brown, Allen C. Bondurant, and Karen L. Endres
The Cryosphere, 14, 3595–3609, https://doi.org/10.5194/tc-14-3595-2020, https://doi.org/10.5194/tc-14-3595-2020, 2020
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River and lake ice thickens at varying rates geographically and from year to year. We took a closer look at ice growth across a large geographic region experiencing rapid climate change, the State of Alaska, USA. Slower ice growth was most pronounced in northern Alaskan lakes over the last 60 years. Western and interior Alaska ice showed more variability in thickness and safe travel duration. This analysis provides a comprehensive evaluation of changing freshwater ice in Alaska.
Cited articles
Akbari, V. and Brekke, C.: Iceberg Detection in Open and Ice-Infested Waters Using C-Band Polarimetric Synthetic Aperture Radar, IEEE T. Geosci. Remote, 56, 407–421, https://doi.org/10.1109/TGRS.2017.2748394, 2018.
Anfinsen, S. N., Doulgeris, A. P., and Eltoft, T.: Estimation of the Equivalent Number of Looks in Polarimetric Synthetic Aperture Radar Imagery, IEEE T. Geosci. Remote, 47, 3795–3809, https://doi.org/10.1109/TGRS.2009.2019269, 2009.
Argenti, F., Lapini, A., Bianchi, T., and Alparone, L.: A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images, IEEE Geosci. Remote Sens. Mag., 1, 6–35, https://doi.org/10.1109/MGRS.2013.2277512, 2013.
Bailey, J. and Marino, A.: Quad-Polarimetric Multi-Scale Analysis of Icebergs in ALOS-2 SAR Data: A Comparison between Icebergs in West and East Greenland, Remote Sensing, 12, 1864, https://doi.org/10.3390/rs12111864, 2020.
Bailey, J., Marino, A., and Akbari, V.: Comparison of Target Detectors to Identify Icebergs in Quad-Polarimetric L-Band Synthetic Aperture Radar Data, Remote Sensing, 13, 1753, https://doi.org/10.3390/rs13091753, 2021.
Barbat, M. M., Rackow, T., Hellmer, H. H., Wesche, C., and Mata, M. M.: Three Years of Near-Coastal Antarctic Iceberg Distribution From a Machine Learning Approach Applied to SAR Imagery, J. Geophys. Res.-Oceans, 124, 6658–6672, https://doi.org/10.1029/2019JC015205, 2019.
Bourbigot, M., Johnson, H., and Piantanda, R.: Sentinel-1 Product Definition, ESA, https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-1-sar/document-library/-/asset_publisher/1dO7RF5fJMbd/content/sentinel-1-product-definition (last access: 6 December 2023), 2016.
Brekke, C.: Automatic ship detection based on satellite SAR, FFI, ISBN 978-82-464-1582-6, http://hdl.handle.net/20.500.12242/2139 (last access: 6 December 2023), 2009.
Brekke, C. and Anfinsen, S. N.: Ship Detection in Ice-Infested Waters Based on Dual-Polarization SAR Imagery, IEEE Geosci. Remote Sensing Lett., 8, 391–395, https://doi.org/10.1109/LGRS.2010.2078796, 2011.
Buus-Hinkler, J., Qvistgaard, K., and Krane, K. A. H.: Iceberg number density – Reaching a full picture of the Greenland waters, in: 2014 IEEE Geoscience and Remote Sensing Symposium, IGARSS 2014–2014 IEEE International Geoscience and Remote Sensing Symposium, Quebec City, QC, 270–273, https://doi.org/10.1109/IGARSS.2014.6946409, 2014.
Connetable, P., Conradsen, K., Nielsen, A. A., and Skriver, H.: Test Statistics for Reflection Symmetry: Applications to Quad-Polarimetric SAR Data for Detection of Man-Made Structures, IEEE J. Sel. Top. Appl., 15, 2877–2890, https://doi.org/10.1109/JSTARS.2022.3162670, 2022.
Conradsen, K., Nielsen, A. A., Schou, J., and Skriver, H.: A test statistic in the complex wishart distribution and its application to change detection in polarimetric SAR data, IEEE T. Geosci. Remote, 41, 4–19, https://doi.org/10.1109/TGRS.2002.808066, 2003.
Copernicus: Data Space Eco System, Copernicus [data set], https://dataspace.copernicus.eu/, last access: 6 December 2023.
Crisp, D. J.: The state-of-the-art in ship detection in synthetic aperture radar imagery, DSTO, Dept. Defense, Australian Government, Canberra, IC, Australia, 2004.
Danish Meteorological Institute: Verjarkiv, Danish Meteorological Institute [data set], https://www.dmi.dk/vejrarkiv/, last access: 14 September 2021.
Das, A., Kumar, R., and Rosen, P.: Nisar Mission Overview and Updates on ISRO Science Plan, in: 2021 IEEE International India Geoscience and Remote Sensing Symposium (InGARSS), 2021 IEEE International India Geoscience and Remote Sensing Symposium (InGARSS), Ahmedabad, India, 269–272, https://doi.org/10.1109/InGARSS51564.2021.9791979, 2021.
Davidson, M., Gebert, N., and Giulicchi, L.: ROSE-L – The L-band SAR Mission for Copernicus, in: EUSAR 2021; 13th European Conference on Synthetic Aperture Radar, Leipzig, Germany 29 March 2021–1 April 2021, https://ieeexplore.ieee.org/servlet/opac?punumber=9472486 (last access: 9 December 2023), 2021.
Denbina, M. and Collins, M. J.: Iceberg Detection Using Compact Polarimetric Synthetic Aperture Radar, Atmos. Ocean, 50, 437–446, https://doi.org/10.1080/07055900.2012.733307, 2012.
Denbina, M. and Collins, M. J.: Iceberg Detection Using Simulated Dual-Polarized Radarsat Constellation Data, Can. J. Remote Sens., 40, 165–178, https://doi.org/10.1080/07038992.2014.945517, 2014.
Dierking, W.: Sea Ice And Icebergs. Maritime Surveillance with Synthetic Aperture Radar, edited by: Di Martino, G. and Iodice, A., Institution of Engineering and Technology, 346 pp., ISBN 9781785616013, https://doi.org/10.1049/SBRA521E, 2020.
Dierking, W. and Davidson, M.: Enhanced Sea Ice Monitoring At L- and C-Bands using Rose-L and Sentinel-1, in: IGARSS 2020–2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020–2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 4059–4060, https://doi.org/10.1109/IGARSS39084.2020.9323886, 2020.
Dierking, W. and Wesche, C.: C-Band Radar Polarimetry – Useful for Detection of Icebergs in Sea Ice?, IEEE T. Geosci. Remote, 52, 25–37, https://doi.org/10.1109/TGRS.2012.2234756, 2014.
Doulgeris, A. P., Anfinsen, S. N., and Eltoft, T.: Automated non-gaussian clustering of polarimetric synthetic aperture radar images, IEEE T. Geosci. Remote, 49, 3665–3676, https://doi.org/10.1109/TGRS.2011.2140120, 2011.
El-Darymli, K., McGuire, P., Power, D., and Moloney, C.: Target detection in synthetic aperture radar imagery: a state-of-the-art survey, J. Appl. Remote Sens, 7, 071598, https://doi.org/10.1117/1.JRS.7.071598, 2013.
Færch, L.: CFAR Object Detection Library (Version v1), Zenodo [code], https://doi.org/10.5281/zenodo.10254677, 2023.
Gill, R. S.: Operational Detection of Sea Ice Edges and Icebergs Using SAR, Can. J. Remote Sens., 27, 411–432, https://doi.org/10.1080/07038992.2001.10854884, 2001.
Gillies, S. et al.: Rasterio: geospatial raster I/O for Python programmers, GitHub [code], https://github.com/rasterio/rasterio (last access: 17 November 2022), 2013.
Goodman, N. R.: Statistical Analysis Based on a Certain Multivariate Complex Gaussian Distribution (An Introduction), Ann. Math. Statist., 34, 152–177, https://doi.org/10.1214/aoms/1177704250, 1963.
Government of Canada: Environment and natural resources, Weather, Climate and Hazards, Past weather and climate, Historical Data, Government of Canada [data set], https://climate.weather.gc.ca, last access: 18 January 2023.
Gray, A. L. and Arsenault, L. D.: Time-delayed reflections in L-band synthetic aperture radar imagery of icebergs, IEEE T. Geosci. Remote, 29, 284–291, https://doi.org/10.1109/36.73670, 1991.
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585, 357–362, https://doi.org/10.1038/s41586-020-2649-2, 2020.
Howell, C., Youden, J., Lane, K., Power, D., Randell, C., and Flett, D.: Iceberg and ship discrimination with ENVISAT multi-polarization ASAR, in: IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK, USA, 2004, 113–116, https://doi.org/10.1109/IGARSS.2004.1368958, 2004.
JAXA: ALOS-2/PALSAR-2 Level 1.1/1.5/2.1/3.1 CEOS SAR Product Format Description, Rev. G, Japanese Aerospace Exploration Agency, https://www.eorc.jaxa.jp/ALOS/en/alos-2/datause/a2_format_e.htm (last access: 6 December 2023), 2012.
Karvonen, J., Gegiuc, A., Niskanen, T., Montonen, A., Buus-Hinkler, J., and Rinne, E.: Iceberg Detection in Dual-Polarized C-Band SAR Imagery by Segmentation and Nonparametric CFAR (SnP-CFAR), IEEE T. Geosci. Remote, 60, 4300812, https://doi.org/10.1109/TGRS.2021.3070312, 2022.
Kim, J.-W., Kim, D.-J., Kim, S.-H., and Hwang, B.-J.: Iceberg detection using full-polarimetric RADARSAT-2 SAR data in west antarctica, in: 3rd International Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), Seoul, Korea (South), 26–30 September 2011, 1–4, 2011.
Lam, S. K., Pitrou, A., and Seibert, S.: Numba: a LLVM-based Python JIT compiler, in: Proceedings of the Second Workshop on the LLVM Compiler Infrastructure in HPC, SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis, Austin Texas, 1–6, https://doi.org/10.1145/2833157.2833162, 2015.
Lee, J.-S. and Pottier, E.: Polarimetric Radar Imaging: From Basics to Applications, 1st edn., edited by: Lee, J.-S. and Pottier, E., CRC Press, https://doi.org/10.1201/9781420054989, 2009.
Liu, C.: A dual-polarization ship detection algorithm, DRDC-RDDC-2015-R109, Ottawa Research Centre, 2015.
Liu, C.: Method for Fitting K-Distributed Probability Density Function to Ocean Pixels in Dual-Polarization SAR, Can. J. Remote Sens., 44, 299–310, https://doi.org/10.1080/07038992.2018.1491789, 2018.
Marino, A.: Iceberg Detection with L-Band ALOS-2 Data Using the Dual-POL Ratio Anomaly Detector, in: IGARSS 2018–2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 2018, 6067–6070, https://doi.org/10.1109/IGARSS.2018.8519206, 2018.
Marino, A., Dierking, W., and Wesche, C.: A Depolarization Ratio Anomaly Detector to Identify Icebergs in Sea Ice Using Dual-Polarization SAR Images, IEEE T. Geosci. Remote, 54, 5602–5615, https://doi.org/10.1109/TGRS.2016.2569450, 2016.
Novak, L. M. and Hesse, S. R.: Optimal Polarizations for Radar Detection and Recognition of Targets in Clutter, The Record of the 1993 IEEE National Radar Conference, Lynnfield, MA, USA, 79–83, https://doi.org/10.1109/NRC.1993.270489, 1993.
Oliver, C. and Quegan, S.: Understanding synthetic aperture radar images, SciTech Publishing Inc. Raleigh, NC 27613, ISBN 1-891121-31-6, 2004.
OpenStreetMap contributors: Land Polygons, https://osmdata.openstreetmap.de/data/land-polygons.html, last access: 18 January 2023, 2015.
Park, J.-W., Won, J.-S., Korosov, A. A., Babiker, M., and Miranda, N.: Textural Noise Correction for Sentinel-1 TOPSAR Cross-Polarization Channel Images, IEEE T. Geosci. Remote, 57, 4040–4049, https://doi.org/10.1109/TGRS.2018.2889381, 2019.
Power, D., Youden, J., Lane, K., Randell, C., and Flett, D.: Iceberg Detection Capabilities of RADARSAT Synthetic Aperture Radar, Can. J. Remote Sens., 27, 476–486, https://doi.org/10.1080/07038992.2001.10854888, 2001.
Salkind, N. J.: Bonferroni test, in: Encyclopedia of Measurement and Statistics, Vol. 0, Sage Publications, Inc., 104–107, https://doi.org/10.4135/9781412952644, 2007.
Sandven, S., Babiker, M., and Kloster, K.: Iceberg observations in the Barents Sea by radar and optical satellite images, in: Proceedings of the ENVISAT Symposium, Montreux, Switzerland, 23–27 April 2007, ISBN 92-9291-200-1, 2007. 2007.
Schou, J., Skriver, H., Nielsen, A. A., and Conradsen, K.: CFAR edge detector for polarimetric SAR images, IEEE T. Geosci. Remote, 41, 20–32, https://doi.org/10.1109/TGRS.2002.808063, 2003.
Soldal, I., Dierking, W., Korosov, A., and Marino, A.: Automatic Detection of Small Icebergs in Fast Ice Using Satellite Wide-Swath SAR Images, Remote Sensing, 11, 806, https://doi.org/10.3390/rs11070806, 2019.
Tao, D., Doulgeris, A. P., and Brekke, C.: A Segmentation-Based CFAR Detection Algorithm Using Truncated Statistics, IEEE T. Geosci. Remote, 54, 2887–2898, https://doi.org/10.1109/TGRS.2015.2506822, 2016a.
Tao, D., Anfinsen, S. N., and Brekke, C.: Robust CFAR Detector Based on Truncated Statistics in Multiple-Target Situations, IEEE T. Geosci. Remote, 54, 117–134, https://doi.org/10.1109/TGRS.2015.2451311, 2016b.
Tunaley, J. K. E.: K-Distribution Algorithm, LRDC Technical Report, August, 2010.
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C. J., Polat, İ., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F., van Mulbregt, P., and SciPy 1.0 Contributors: SciPy 1.0: fundamental algorithms for scientific computing in Python, Nat. Methods, 17, 261–272, https://doi.org/10.1038/s41592-019-0686-2, 2020.
Wesche, C. and Dierking, W.: Iceberg signatures and detection in SAR images in two test regions of the Weddell Sea, Antarctica, J. Glaciol., 58, 325–339, https://doi.org/10.3189/2012J0G11J020, 2012.
Wesche, C. and Dierking, W.: Estimating iceberg paths using a wind-driven drift model, Cold Reg. Sci. Technol., 125, 31–39, https://doi.org/10.1016/j.coldregions.2016.01.008, 2016.
Willis, C. J., Macklin, J. T., Partington, K. C., Teleki, K. A., Rees, W. G., and Williams, R. G.: Iceberg detection using ERS-1 Synthetic Aperture Radar, Int. J. Remote Sens., 17, 1777–1795, https://doi.org/10.1080/01431169608948739, 1996.
Yang, W., Li, Y., Liu, W., Chen, J., Li, C., and Men, Z.: Scalloping Suppression for ScanSAR Images Based on Modified Kalman Filter With Preprocessing, IEEE T. Geosci. Remote, 59, 7535–7546, https://doi.org/10.1109/TGRS.2020.3034098, 2021.
Zakharov, I., Power, D., Howell, M., and Warren, S.: Improved detection of icebergs in sea ice with RADARSAT-2 polarimetric data, in: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 2017, 2294–2297, https://doi.org/10.1109/IGARSS.2017.8127448, 2017.
Short summary
Icebergs in open water are a risk to maritime traffic. We have compared six different constant false alarm rate (CFAR) detectors on overlapping C- and L-band synthetic aperture radar (SAR) images for the detection of icebergs in open water, with a Sentinel-2 image used for validation. The results revealed that L-band gives a slight advantage over C-band, depending on which detector is used. Additionally, the accuracy of all detectors decreased rapidly as the iceberg size decreased.
Icebergs in open water are a risk to maritime traffic. We have compared six different constant...
