Articles | Volume 17, issue 8
https://doi.org/10.5194/tc-17-3269-2023
© 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-17-3269-2023
© 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 Aug 2023
Research article |
| 15 Aug 2023
| 15 Aug 2023
A long-term proxy for sea ice thickness in the Canadian Arctic: 1996–2020
Isolde A. Glissenaar
CORRESPONDING AUTHOR
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
Jack C. Landy
Centre for Integrated Remote Sensing and Forecasting for Arctic Operations, Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
David G. Babb
Centre for Earth Observation Science, University of Manitoba, Winnipeg, MB, Canada
Geoffrey J. Dawson
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
Stephen E. L. Howell
Climate Research Division, Environment and Climate Change Canada, Toronto, ON, Canada
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The Cryosphere, 18, 2321–2333, https://doi.org/10.5194/tc-18-2321-2024, https://doi.org/10.5194/tc-18-2321-2024, 2024
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The CAA serves as both a source and a sink for sea ice from the Arctic Ocean, while also exporting sea ice into Baffin Bay. It is also an important region with respect to navigating the Northwest Passage. Here, we quantify sea ice transport and replenishment across and within the CAA from 2016 to 2022. We also provide the first estimates of the ice area and volume flux within the CAA from the Queen Elizabeth Islands to Parry Channel, which spans the central region of the Northwest Passage.
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Scientists can estimate sea ice thickness using satellites that measure surface height. To determine the sea ice thickness, we also need to know the snow depth and density. This paper shows that the chosen snow depth product has a considerable impact on the findings of sea ice thickness state and trends in Baffin Bay, showing mean thinning with some snow depth products and mean thickening with others. This shows that it is important to better understand and monitor snow depth on sea ice.
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To measure Arctic ice thickness, we often check how much ice sticks out of the water. This method depends on knowing the ice's density, which drops significantly in summer. Our study, validated with sonar and laser data, shows that these seasonal changes in density can complicate melt measurements. We stress the importance of considering these density changes for more accurate ice thickness readings.
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Scientists can estimate sea ice thickness using satellites that measure surface height. To determine the sea ice thickness, we also need to know the snow depth and density. This paper shows that the chosen snow depth product has a considerable impact on the findings of sea ice thickness state and trends in Baffin Bay, showing mean thinning with some snow depth products and mean thickening with others. This shows that it is important to better understand and monitor snow depth on sea ice.
Igor A. Dmitrenko, Denis L. Volkov, Tricia A. Stadnyk, Andrew Tefs, David G. Babb, Sergey A. Kirillov, Alex Crawford, Kevin Sydor, and David G. Barber
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Stephen E. L. Howell, Randall K. Scharien, Jack Landy, and Mike Brady
The Cryosphere, 14, 4675–4686, https://doi.org/10.5194/tc-14-4675-2020, https://doi.org/10.5194/tc-14-4675-2020, 2020
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Joshua King, Stephen Howell, Mike Brady, Peter Toose, Chris Derksen, Christian Haas, and Justin Beckers
The Cryosphere, 14, 4323–4339, https://doi.org/10.5194/tc-14-4323-2020, https://doi.org/10.5194/tc-14-4323-2020, 2020
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Physical measurements of snow on sea ice are sparse, making it difficulty to evaluate satellite estimates or model representations. Here, we introduce new measurements of snow properties on sea ice to better understand variability at distances less than 200 m. Our work shows that similarities in the snow structure are found at longer distances on younger ice than older ice.
Tian Li, Geoffrey J. Dawson, Stephen J. Chuter, and Jonathan L. Bamber
The Cryosphere, 14, 3629–3643, https://doi.org/10.5194/tc-14-3629-2020, https://doi.org/10.5194/tc-14-3629-2020, 2020
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Accurate knowledge of the Antarctic grounding zone is critical for the understanding of ice sheet instability and the evaluation of mass balance. We present a new, fully automated method to map the grounding zone from ICESat-2 laser altimetry. Our results of Larsen C Ice Shelf demonstrate the efficiency, density, and high spatial accuracy with which ICESat-2 can image complex grounding zones.
Geoffrey J. Dawson and Jonathan L. Bamber
The Cryosphere, 14, 2071–2086, https://doi.org/10.5194/tc-14-2071-2020, https://doi.org/10.5194/tc-14-2071-2020, 2020
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The grounding zone is where grounded ice begins to float and is the boundary at which the ocean has the most significant influence on the inland ice sheet. Here, we present the results of mapping the grounding zone of Antarctic ice shelves from CryoSat-2 radar altimetry. We found good agreement with previous methods that mapped the grounding zone. We also managed to map areas of Support Force Glacier and the Doake Ice Rumples (Filchner–Ronne Ice Shelf), which were previously incompletely mapped.
Marco Meloni, Jerome Bouffard, Tommaso Parrinello, Geoffrey Dawson, Florent Garnier, Veit Helm, Alessandro Di Bella, Stefan Hendricks, Robert Ricker, Erica Webb, Ben Wright, Karina Nielsen, Sanggyun Lee, Marcello Passaro, Michele Scagliola, Sebastian Bjerregaard Simonsen, Louise Sandberg Sørensen, David Brockley, Steven Baker, Sara Fleury, Jonathan Bamber, Luca Maestri, Henriette Skourup, René Forsberg, and Loretta Mizzi
The Cryosphere, 14, 1889–1907, https://doi.org/10.5194/tc-14-1889-2020, https://doi.org/10.5194/tc-14-1889-2020, 2020
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This manuscript aims to describe the evolutions which have been implemented in the new CryoSat Ice processing chain Baseline-D and the validation activities carried out in different domains such as sea ice, land ice and hydrology.
This new CryoSat processing Baseline-D will maximise the uptake and use of CryoSat data by scientific users since it offers improved capability for monitoring the complex and multiscale changes over the cryosphere.
Robbie D. C. Mallett, Isobel R. Lawrence, Julienne C. Stroeve, Jack C. Landy, and Michel Tsamados
The Cryosphere, 14, 251–260, https://doi.org/10.5194/tc-14-251-2020, https://doi.org/10.5194/tc-14-251-2020, 2020
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Soils store large carbon and are important for global warming. We do not know what factors are important for soil carbon storage in the alpine Andes and how they work. We studied how rainfall affects soil carbon storage related to soil structure. We found soil structure is not important, but soil carbon storage and stability controlled by rainfall are dependent on rocks under the soils. The results indicate that we should pay attention to the rocks when studying soil carbon storage in the Andes.
Frédéric Laliberté, Stephen E. L. Howell, Jean-François Lemieux, Frédéric Dupont, and Ji Lei
The Cryosphere, 12, 3577–3588, https://doi.org/10.5194/tc-12-3577-2018, https://doi.org/10.5194/tc-12-3577-2018, 2018
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Ice that forms over marginal seas often gets anchored and becomes landfast. Landfast ice is fundamental to the local ecosystems, is of economic importance as it leads to hazardous seafaring conditions and is also a choice hunting ground for both the local population and large predators. Using observations and climate simulations, this study shows that, especially in the Canadian Arctic, landfast ice might be more resilient to climate change than is generally thought.
Paul J. Kushner, Lawrence R. Mudryk, William Merryfield, Jaison T. Ambadan, Aaron Berg, Adéline Bichet, Ross Brown, Chris Derksen, Stephen J. Déry, Arlan Dirkson, Greg Flato, Christopher G. Fletcher, John C. Fyfe, Nathan Gillett, Christian Haas, Stephen Howell, Frédéric Laliberté, Kelly McCusker, Michael Sigmond, Reinel Sospedra-Alfonso, Neil F. Tandon, Chad Thackeray, Bruno Tremblay, and Francis W. Zwiers
The Cryosphere, 12, 1137–1156, https://doi.org/10.5194/tc-12-1137-2018, https://doi.org/10.5194/tc-12-1137-2018, 2018
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Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea ice to assess how Canada's climate model and climate prediction systems capture variability in snow, sea ice, and related climate parameters. We find that the system performs well, accounting for observational uncertainty (especially for snow), model uncertainty, and chaotic climate variability. Even for variables like sea ice, where improvement is needed, useful prediction tools can be developed.
Lawrence R. Mudryk, Chris Derksen, Stephen Howell, Fred Laliberté, Chad Thackeray, Reinel Sospedra-Alfonso, Vincent Vionnet, Paul J. Kushner, and Ross Brown
The Cryosphere, 12, 1157–1176, https://doi.org/10.5194/tc-12-1157-2018, https://doi.org/10.5194/tc-12-1157-2018, 2018
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This paper presents changes in both snow and sea ice that have occurred over Canada during the recent past and shows climate model estimates for future changes expected to occur by the year 2050. The historical changes of snow and sea ice are generally coherent and consistent with the regional history of temperature and precipitation changes. It is expected that snow and sea ice will continue to decrease in the future, declining by an additional 15–30 % from present day values by the year 2050.
Igor A. Dmitrenko, Sergey A. Kirillov, Bert Rudels, David G. Babb, Leif Toudal Pedersen, Søren Rysgaard, Yngve Kristoffersen, and David G. Barber
Ocean Sci., 13, 1045–1060, https://doi.org/10.5194/os-13-1045-2017, https://doi.org/10.5194/os-13-1045-2017, 2017
Sergei Kirillov, Igor Dmitrenko, Søren Rysgaard, David Babb, Leif Toudal Pedersen, Jens Ehn, Jørgen Bendtsen, and David Barber
Ocean Sci., 13, 947–959, https://doi.org/10.5194/os-13-947-2017, https://doi.org/10.5194/os-13-947-2017, 2017
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This paper reports the analysis of 3-week oceanographic data obtained in the front of Flade Isblink Glacier in northeast Greenland. The major focus of research is considering the changes of water dynamics and the altering of temperature and salinity vertical distribution occurring during the storm event. We discuss the mechanisms that are responsible for the formation of two-layer circulation cell and release of cold and relatively fresh sub-glacial waters into the ocean.
Ron Kwok, Nathan T. Kurtz, Ludovic Brucker, Alvaro Ivanoff, Thomas Newman, Sinead L. Farrell, Joshua King, Stephen Howell, Melinda A. Webster, John Paden, Carl Leuschen, Joseph A. MacGregor, Jacqueline Richter-Menge, Jeremy Harbeck, and Mark Tschudi
The Cryosphere, 11, 2571–2593, https://doi.org/10.5194/tc-11-2571-2017, https://doi.org/10.5194/tc-11-2571-2017, 2017
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Since 2009, the ultra-wideband snow radar on Operation IceBridge has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Existing snow depth retrieval algorithms differ in the way the air–snow and snow–ice interfaces are detected and localized in the radar returns and in how the system limitations are addressed. Here, we assess five retrieval algorithms by comparisons with field measurements, ground-based campaigns, and analyzed fields of snow depth.
Stephen E. L. Howell, Frédéric Laliberté, Ron Kwok, Chris Derksen, and Joshua King
The Cryosphere, 10, 1463–1475, https://doi.org/10.5194/tc-10-1463-2016, https://doi.org/10.5194/tc-10-1463-2016, 2016
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The Canadian Ice Service record of observed landfast ice and snow thickness represents one of the longest in the Arctic that spans over 5 decades. We analyze this record to report on long-term trends and variability of ice and snow thickness within the Canadian Arctic Archipelago (CAA). Results indicate a thinning of ice at several sites in the CAA. State-of-the-art climate models still have difficultly capturing observed ice thickness values in the CAA and should be used with caution.
N.-X. Geilfus, R. J. Galley, O. Crabeck, T. Papakyriakou, J. Landy, J.-L. Tison, and S. Rysgaard
Biogeosciences, 12, 2047–2061, https://doi.org/10.5194/bg-12-2047-2015, https://doi.org/10.5194/bg-12-2047-2015, 2015
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We investigated the evolution of inorganic carbon within landfast sea ice in Resolute Passage during the spring and summer melt period.
Low TA and TCO2 concentrations observed in sea ice and brine were associated with the percolation of meltwater from melt ponds. Meltwater was continuously supplied to the ponds which prevented melt ponds from fully equilibrating with the atmospheric CO2 concentration, promoting a continuous uptake of CO2 from the atmosphere.
S. E. L. Howell, T. Wohlleben, A. Komarov, L. Pizzolato, and C. Derksen
The Cryosphere, 7, 1753–1768, https://doi.org/10.5194/tc-7-1753-2013, https://doi.org/10.5194/tc-7-1753-2013, 2013
Related subject area
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Multidecadal Arctic sea ice thickness and volume derived from ice age
Going with the floe: tracking CESM Large Ensemble sea ice in the Arctic provides context for ship-based observations
The Arctic sea ice extent change connected to Pacific decadal variability
Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice
Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution
Benchmark seasonal prediction skill estimates based on regional indices
On the timescales and length scales of the Arctic sea ice thickness anomalies: a study based on 14 reanalyses
Past and future interannual variability in Arctic sea ice in coupled climate models
Arctic sea-ice-free season projected to extend into autumn
Definition differences and internal variability affect the simulated Arctic sea ice melt season
The potential of sea ice leads as a predictor for summer Arctic sea ice extent
Arctic climate: changes in sea ice extent outweigh changes in snow cover
Arctic Mission Benefit Analysis: impact of sea ice thickness, freeboard, and snow depth products on sea ice forecast performance
Francesco Cocetta, Lorenzo Zampieri, Julia Selivanova, and Doroteaciro Iovino
The Cryosphere, 18, 4687–4702, https://doi.org/10.5194/tc-18-4687-2024, https://doi.org/10.5194/tc-18-4687-2024, 2024
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Arctic sea ice is thinning and retreating because of global warming. Thus, the region is transitioning to a new state featuring an expansion of the marginal ice zone, a region where mobile ice interacts with waves from the open ocean. By analyzing 30 years of sea ice reconstructions that combine numerical models and observations, this paper proves that an ensemble of global ocean and sea ice reanalyses is an adequate tool for investigating the changing Arctic sea ice cover.
Joanna Davies, Kirsten Fahl, Matthias Moros, Alice Carter-Champion, Henrieka Detlef, Ruediger Stein, Christof Pearce, and Marit-Solveig Seidenkrantz
The Cryosphere, 18, 3415–3431, https://doi.org/10.5194/tc-18-3415-2024, https://doi.org/10.5194/tc-18-3415-2024, 2024
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Here, we evaluate the use of biomarkers for reconstructing sea ice between 1880 and 2017 from three sediment cores located in a transect across the Northeast Greenland continental shelf. We find that key changes, specifically the decline in sea-ice cover identified in observational records between 1971 and 1984, align with our biomarker reconstructions. This outcome supports the use of biomarkers for longer reconstructions of sea-ice cover in this region.
Nathan J. M. Laxague, Christopher J. Zappa, Andrew R. Mahoney, John Goodwin, Cyrus Harris, Robert E. Schaeffer, Roswell Schaeffer Sr., Sarah Betcher, Donna D. W. Hauser, Carson R. Witte, Jessica M. Lindsay, Ajit Subramaniam, Kate E. Turner, and Alex Whiting
The Cryosphere, 18, 3297–3313, https://doi.org/10.5194/tc-18-3297-2024, https://doi.org/10.5194/tc-18-3297-2024, 2024
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The state of sea ice strongly affects its absorption of solar energy. In May 2019, we flew uncrewed aerial vehicles (UAVs) equipped with sensors designed to quantify the sunlight that is reflected by sea ice at each wavelength over the sea ice of Kotzebue Sound, Alaska. We found that snow patches get darker (up to ~ 20 %) as they get smaller, while bare patches get darker (up to ~ 20 %) as they get larger. We believe that this difference is due to melting around the edges of small features.
Cyril Palerme, Thomas Lavergne, Jozef Rusin, Arne Melsom, Julien Brajard, Are Frode Kvanum, Atle Macdonald Sørensen, Laurent Bertino, and Malte Müller
The Cryosphere, 18, 2161–2176, https://doi.org/10.5194/tc-18-2161-2024, https://doi.org/10.5194/tc-18-2161-2024, 2024
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Sea ice forecasts are operationally produced using physically based models, but these forecasts are often not accurate enough for maritime operations. In this study, we developed a statistical correction technique using machine learning in order to improve the skill of short-term (up to 10 d) sea ice concentration forecasts produced by the TOPAZ4 model. This technique allows for the reduction of errors from the TOPAZ4 sea ice concentration forecasts by 41 % on average.
Dunwang Lu, Jianqiang Liu, Lijian Shi, Tao Zeng, Bin Cheng, Suhui Wu, and Manman Wang
The Cryosphere, 18, 1419–1441, https://doi.org/10.5194/tc-18-1419-2024, https://doi.org/10.5194/tc-18-1419-2024, 2024
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We retrieved sea ice drift in Fram Strait using the Chinese HaiYang 1D Coastal Zone Imager. The dataset is has hourly and daily intervals for analysis, and validation is performed using a synthetic aperture radar (SAR)-based product and International Arctic Buoy Programme (IABP) buoys. The differences between them are explained by investigating the spatiotemporal variability in sea ice motion. The accuracy of flow direction retrieval for sea ice drift is also related to sea ice displacement.
Ana Lúcia Lindroth Dauner, Frederik Schenk, Katherine Elizabeth Power, and Maija Heikkilä
The Cryosphere, 18, 1399–1418, https://doi.org/10.5194/tc-18-1399-2024, https://doi.org/10.5194/tc-18-1399-2024, 2024
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In this study, we analysed 14 sea-ice proxy records and compared them with the results from two different climate simulations from the Atlantic sector of the Arctic Ocean over the Common Era (last 2000 years). Both proxy and model approaches demonstrated a long-term sea-ice increase. The good correspondence suggests that the state-of-the-art sea-ice proxies are able to capture large-scale climate drivers. Short-term variability, however, was less coherent due to local-to-regional scale forcings.
Hannah Niehaus, Larysa Istomina, Marcel Nicolaus, Ran Tao, Aleksey Malinka, Eleonora Zege, and Gunnar Spreen
The Cryosphere, 18, 933–956, https://doi.org/10.5194/tc-18-933-2024, https://doi.org/10.5194/tc-18-933-2024, 2024
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Melt ponds are puddles of meltwater which form on Arctic sea ice in the summer period. They are darker than the ice cover and lead to increased absorption of solar energy. Global climate models need information about the Earth's energy budget. Thus satellite observations are used to monitor the surface fractions of melt ponds, ocean, and sea ice in the entire Arctic. We present a new physically based algorithm that can separate these three surface types with uncertainty below 10 %.
Zuzanna M. Swirad, A. Malin Johansson, and Eirik Malnes
The Cryosphere, 18, 895–910, https://doi.org/10.5194/tc-18-895-2024, https://doi.org/10.5194/tc-18-895-2024, 2024
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We used satellite images to create sea ice maps of Hornsund fjord, Svalbard, for nine seasons and calculated the percentage of the fjord that was covered by ice. On average, sea ice was present in Hornsund for 158 d per year, but it varied from year to year. April was the "iciest'" month and 2019/2020, 2021/22 and 2014/15 were the "iciest'" seasons. Our data can be used to understand sea ice conditions compared with other fjords of Svalbard and in studies of wave modelling and coastal erosion.
Miao Yu, Peng Lu, Matti Leppäranta, Bin Cheng, Ruibo Lei, Bingrui Li, Qingkai Wang, and Zhijun Li
The Cryosphere, 18, 273–288, https://doi.org/10.5194/tc-18-273-2024, https://doi.org/10.5194/tc-18-273-2024, 2024
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Variations in Arctic sea ice are related not only to its macroscale properties but also to its microstructure. Arctic ice cores in the summers of 2008 to 2016 were used to analyze variations in the ice inherent optical properties related to changes in the ice microstructure. The results reveal changing ice microstructure greatly increased the amount of solar radiation transmitted to the upper ocean even when a constant ice thickness was assumed, especially in marginal ice zones.
Geoffrey J. Dawson and Jack C. Landy
The Cryosphere, 17, 4165–4178, https://doi.org/10.5194/tc-17-4165-2023, https://doi.org/10.5194/tc-17-4165-2023, 2023
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In this study, we compared measurements from CryoSat-2 and ICESat-2 over Arctic summer sea ice to understand any possible biases between the two satellites. We found that there is a difference when we measure elevation over summer sea ice using CryoSat-2 and ICESat-2, and this is likely due to surface melt ponds. The differences we found were in good agreement with theoretical predictions, and this work will be valuable for summer sea ice thickness measurements from both altimeters.
Yanan Wang, Byongjun Hwang, Adam William Bateson, Yevgeny Aksenov, and Christopher Horvat
The Cryosphere, 17, 3575–3591, https://doi.org/10.5194/tc-17-3575-2023, https://doi.org/10.5194/tc-17-3575-2023, 2023
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Sea ice is composed of small, discrete pieces of ice called floes, whose size distribution plays a critical role in the interactions between the sea ice, ocean and atmosphere. This study provides an assessment of sea ice models using new high-resolution floe size distribution observations, revealing considerable differences between them. These findings point not only to the limitations in models but also to the need for more high-resolution observations to validate and calibrate models.
Sascha Willmes, Günther Heinemann, and Frank Schnaase
The Cryosphere, 17, 3291–3308, https://doi.org/10.5194/tc-17-3291-2023, https://doi.org/10.5194/tc-17-3291-2023, 2023
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Sea ice is an important constituent of the global climate system. We here use satellite data to identify regions in the Arctic where the sea ice breaks up in so-called leads (i.e., linear cracks) regularly during winter. This information is important because leads determine, e.g., how much heat is exchanged between the ocean and the atmosphere. We here provide first insights into the reasons for the observed patterns in sea-ice leads and their relation to ocean currents and winds.
Marion Bocquet, Sara Fleury, Fanny Piras, Eero Rinne, Heidi Sallila, Florent Garnier, and Frédérique Rémy
The Cryosphere, 17, 3013–3039, https://doi.org/10.5194/tc-17-3013-2023, https://doi.org/10.5194/tc-17-3013-2023, 2023
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Sea ice has a large interannual variability, and studying its evolution requires long time series of observations. In this paper, we propose the first method to extend Arctic sea ice thickness time series to the ERS-2 altimeter. The developed method is based on a neural network to calibrate past missions on the current one by taking advantage of their differences during the mission-overlap periods. Data are available as monthly maps for each year during the winter period between 1995 and 2021.
Ole Rieke, Marius Årthun, and Jakob Simon Dörr
The Cryosphere, 17, 1445–1456, https://doi.org/10.5194/tc-17-1445-2023, https://doi.org/10.5194/tc-17-1445-2023, 2023
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The Barents Sea is the region of most intense winter sea ice loss, and future projections show a continued decline towards ice-free conditions by the end of this century but with large fluctuations. Here we use climate model simulations to look at the occurrence and drivers of rapid ice change events in the Barents Sea that are much stronger than the average ice loss. A better understanding of these events will contribute to improved sea ice predictions in the Barents Sea.
Younjoo J. Lee, Wieslaw Maslowski, John J. Cassano, Jaclyn Clement Kinney, Anthony P. Craig, Samy Kamal, Robert Osinski, Mark W. Seefeldt, Julienne Stroeve, and Hailong Wang
The Cryosphere, 17, 233–253, https://doi.org/10.5194/tc-17-233-2023, https://doi.org/10.5194/tc-17-233-2023, 2023
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During 1979–2020, four winter polynyas occurred in December 1986 and February 2011, 2017, and 2018 north of Greenland. Instead of ice melting due to the anomalous warm air intrusion, the extreme wind forcing resulted in greater ice transport offshore. Based on the two ensemble runs, representing a 1980s thicker ice vs. a 2010s thinner ice, a dominant cause of these winter polynyas stems from internal variability of atmospheric forcing rather than from the forced response to a warming climate.
Alek A. Petty, Nicole Keeney, Alex Cabaj, Paul Kushner, and Marco Bagnardi
The Cryosphere, 17, 127–156, https://doi.org/10.5194/tc-17-127-2023, https://doi.org/10.5194/tc-17-127-2023, 2023
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We present upgrades to winter Arctic sea ice thickness estimates from NASA's ICESat-2. Our new thickness results show better agreement with independent data from ESA's CryoSat-2 compared to our first data release, as well as new, very strong comparisons with data collected by moorings in the Beaufort Sea. We analyse three winters of thickness data across the Arctic, including 50 cm thinning of the multiyear ice over this 3-year period.
John E. Walsh, Hajo Eicken, Kyle Redilla, and Mark Johnson
The Cryosphere, 16, 4617–4635, https://doi.org/10.5194/tc-16-4617-2022, https://doi.org/10.5194/tc-16-4617-2022, 2022
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Indicators for the start and end of annual breakup and freeze-up of sea ice at various coastal locations around the Arctic are developed. Relative to broader offshore areas, some of the coastal indicators show an earlier freeze-up and later breakup, especially at locations where landfast ice is prominent. However, the trends towards earlier breakup and later freeze-up are unmistakable over the post-1979 period in synthesized metrics of the coastal breakup/freeze-up indicators.
Abigail Smith, Alexandra Jahn, Clara Burgard, and Dirk Notz
The Cryosphere, 16, 3235–3248, https://doi.org/10.5194/tc-16-3235-2022, https://doi.org/10.5194/tc-16-3235-2022, 2022
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The timing of Arctic sea ice melt each year is an important metric for assessing how sea ice in climate models compares to satellite observations. Here, we utilize a new tool for creating more direct comparisons between climate model projections and satellite observations of Arctic sea ice, such that the melt onset dates are defined the same way. This tool allows us to identify climate model biases more clearly and gain more information about what the satellites are observing.
Juha Karvonen, Eero Rinne, Heidi Sallila, Petteri Uotila, and Marko Mäkynen
The Cryosphere, 16, 1821–1844, https://doi.org/10.5194/tc-16-1821-2022, https://doi.org/10.5194/tc-16-1821-2022, 2022
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We propose a method to provide sea ice thickness (SIT) estimates over a test area in the Arctic utilizing radar altimeter (RA) measurement lines and C-band SAR imagery. The RA data are from CryoSat-2, and SAR imagery is from Sentinel-1. By combining them we get a SIT grid covering the whole test area instead of only narrow measurement lines from RA. This kind of SIT estimation can be extended to cover the whole Arctic (and Antarctic) for operational SIT monitoring.
Yu Liang, Haibo Bi, Haijun Huang, Ruibo Lei, Xi Liang, Bin Cheng, and Yunhe Wang
The Cryosphere, 16, 1107–1123, https://doi.org/10.5194/tc-16-1107-2022, https://doi.org/10.5194/tc-16-1107-2022, 2022
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A record minimum July sea ice extent, since 1979, was observed in 2020. Our results reveal that an anomalously high advection of energy and water vapor prevailed during spring (April to June) 2020 over regions with noticeable sea ice retreat. The large-scale atmospheric circulation and cyclones act in concert to trigger the exceptionally warm and moist flow. The convergence of the transport changed the atmospheric characteristics and the surface energy budget, thus causing a severe sea ice melt.
Jinlei Chen, Shichang Kang, Wentao Du, Junming Guo, Min Xu, Yulan Zhang, Xinyue Zhong, Wei Zhang, and Jizu Chen
The Cryosphere, 15, 5473–5482, https://doi.org/10.5194/tc-15-5473-2021, https://doi.org/10.5194/tc-15-5473-2021, 2021
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Sea ice is retreating with rapid warming in the Arctic. It will continue and approach the worst predicted pathway released by the IPCC. The irreversible tipping point might show around 2060 when the oldest ice will have completely disappeared. It has a huge impact on human production. Ordinary merchant ships will be able to pass the Northeast Passage and Northwest Passage by the midcentury, and the opening time will advance to the next 10 years for icebreakers with moderate ice strengthening.
Qiang Wang, Sergey Danilov, Longjiang Mu, Dmitry Sidorenko, and Claudia Wekerle
The Cryosphere, 15, 4703–4725, https://doi.org/10.5194/tc-15-4703-2021, https://doi.org/10.5194/tc-15-4703-2021, 2021
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Using simulations, we found that changes in ocean freshwater content induced by wind perturbations can significantly affect the Arctic sea ice drift, thickness, concentration and deformation rates years after the wind perturbations. The impact is through changes in sea surface height and surface geostrophic currents and the most pronounced in warm seasons. Such a lasting impact might become stronger in a warming climate and implies the importance of ocean initialization in sea ice prediction.
Henrieka Detlef, Brendan Reilly, Anne Jennings, Mads Mørk Jensen, Matt O'Regan, Marianne Glasius, Jesper Olsen, Martin Jakobsson, and Christof Pearce
The Cryosphere, 15, 4357–4380, https://doi.org/10.5194/tc-15-4357-2021, https://doi.org/10.5194/tc-15-4357-2021, 2021
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Here we examine the Nares Strait sea ice dynamics over the last 7000 years and their implications for the late Holocene readvance of the floating part of Petermann Glacier. We propose that the historically observed sea ice dynamics are a relatively recent feature, while most of the mid-Holocene was marked by variable sea ice conditions in Nares Strait. Nonetheless, major advances of the Petermann ice tongue were preceded by a shift towards harsher sea ice conditions in Nares Strait.
Timothy Williams, Anton Korosov, Pierre Rampal, and Einar Ólason
The Cryosphere, 15, 3207–3227, https://doi.org/10.5194/tc-15-3207-2021, https://doi.org/10.5194/tc-15-3207-2021, 2021
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neXtSIM (neXt-generation Sea Ice Model) includes a novel and extremely realistic way of modelling sea ice dynamics – i.e. how the sea ice moves and deforms in response to the drag from winds and ocean currents. It has been developed over the last few years for a variety of applications, but this paper represents its first demonstration in a forecast context. We present results for the time period from November 2018 to June 2020 and show that it agrees well with satellite observations.
Sourav Chatterjee, Roshin P. Raj, Laurent Bertino, Sebastian H. Mernild, Meethale Puthukkottu Subeesh, Nuncio Murukesh, and Muthalagu Ravichandran
The Cryosphere, 15, 1307–1319, https://doi.org/10.5194/tc-15-1307-2021, https://doi.org/10.5194/tc-15-1307-2021, 2021
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Sea ice in the Greenland Sea (GS) is important for its climatic (fresh water), economical (shipping), and ecological contribution (light availability). The study proposes a mechanism through which sea ice concentration in GS is partly governed by the atmospheric and ocean circulation in the region. The mechanism proposed in this study can be useful for assessing the sea ice variability and its future projection in the GS.
Ruibo Lei, Mario Hoppmann, Bin Cheng, Guangyu Zuo, Dawei Gui, Qiongqiong Cai, H. Jakob Belter, and Wangxiao Yang
The Cryosphere, 15, 1321–1341, https://doi.org/10.5194/tc-15-1321-2021, https://doi.org/10.5194/tc-15-1321-2021, 2021
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Quantification of ice deformation is useful for understanding of the role of ice dynamics in climate change. Using data of 32 buoys, we characterized spatiotemporal variations in ice kinematics and deformation in the Pacific sector of Arctic Ocean for autumn–winter 2018/19. Sea ice in the south and west has stronger mobility than in the east and north, which weakens from autumn to winter. An enhanced Arctic dipole and weakened Beaufort Gyre in winter lead to an obvious turning of ice drifting.
Beena Balan-Sarojini, Steffen Tietsche, Michael Mayer, Magdalena Balmaseda, Hao Zuo, Patricia de Rosnay, Tim Stockdale, and Frederic Vitart
The Cryosphere, 15, 325–344, https://doi.org/10.5194/tc-15-325-2021, https://doi.org/10.5194/tc-15-325-2021, 2021
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Our study for the first time shows the impact of measured sea ice thickness (SIT) on seasonal forecasts of all the seasons. We prove that the long-term memory present in the Arctic winter SIT is helpful to improve summer sea ice forecasts. Our findings show that realistic SIT initial conditions to start a forecast are useful in (1) improving seasonal forecasts, (2) understanding errors in the forecast model, and (3) recognizing the need for continuous monitoring of world's ice-covered oceans.
Chao Min, Qinghua Yang, Longjiang Mu, Frank Kauker, and Robert Ricker
The Cryosphere, 15, 169–181, https://doi.org/10.5194/tc-15-169-2021, https://doi.org/10.5194/tc-15-169-2021, 2021
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An ensemble of four estimates of the sea-ice volume (SIV) variations in Baffin Bay from 2011 to 2016 is generated from the locally merged satellite observations, three modeled sea ice thickness sources (CMST, NAOSIM, and PIOMAS) and NSIDC ice drift data (V4). Results show that the net increase of the ensemble mean SIV occurs from October to April with the largest SIV increase in December, and the reduction occurs from May to September with the largest SIV decline in July.
Mohammed E. Shokr, Zihan Wang, and Tingting Liu
The Cryosphere, 14, 3611–3627, https://doi.org/10.5194/tc-14-3611-2020, https://doi.org/10.5194/tc-14-3611-2020, 2020
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This paper uses sequential daily SAR images covering the Robeson Channel to quantitatively study kinematics of individual ice floes with exploration of wind influence and the evolution of the ice arch at the entry of the channel. Results show that drift of ice floes within the Robeson Channel and the arch are both significantly influenced by wind. The study highlights the advantage of using the high-resolution daily SAR coverage in monitoring sea ice cover in narrow water passages.
Guillian Van Achter, Leandro Ponsoni, François Massonnet, Thierry Fichefet, and Vincent Legat
The Cryosphere, 14, 3479–3486, https://doi.org/10.5194/tc-14-3479-2020, https://doi.org/10.5194/tc-14-3479-2020, 2020
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We document the spatio-temporal internal variability of Arctic sea ice thickness and its changes under anthropogenic forcing, which is key to understanding, and eventually predicting, the evolution of sea ice in response to climate change.
The patterns of sea ice thickness variability remain more or less stable during pre-industrial, historical and future periods, despite non-stationarity on short timescales. These patterns start to change once Arctic summer ice-free events occur, after 2050.
Abigail Smith, Alexandra Jahn, and Muyin Wang
The Cryosphere, 14, 2977–2997, https://doi.org/10.5194/tc-14-2977-2020, https://doi.org/10.5194/tc-14-2977-2020, 2020
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The annual cycle of Arctic sea ice can be used to gain more information about how climate model simulations of sea ice compare to observations. In some models, the September sea ice area agrees with observations for the wrong reasons because biases in the timing of seasonal transitions compensate for other unrealistic sea ice characteristics. This research was done to provide new process-based metrics of Arctic sea ice using satellite observations, the CESM Large Ensemble, and CMIP6 models.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
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The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Thomas Krumpen, Florent Birrien, Frank Kauker, Thomas Rackow, Luisa von Albedyll, Michael Angelopoulos, H. Jakob Belter, Vladimir Bessonov, Ellen Damm, Klaus Dethloff, Jari Haapala, Christian Haas, Carolynn Harris, Stefan Hendricks, Jens Hoelemann, Mario Hoppmann, Lars Kaleschke, Michael Karcher, Nikolai Kolabutin, Ruibo Lei, Josefine Lenz, Anne Morgenstern, Marcel Nicolaus, Uwe Nixdorf, Tomash Petrovsky, Benjamin Rabe, Lasse Rabenstein, Markus Rex, Robert Ricker, Jan Rohde, Egor Shimanchuk, Suman Singha, Vasily Smolyanitsky, Vladimir Sokolov, Tim Stanton, Anna Timofeeva, Michel Tsamados, and Daniel Watkins
The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, https://doi.org/10.5194/tc-14-2173-2020, 2020
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In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with it on the 1-year-long MOSAiC journey through the Arctic. Here we provide historical context of the floe's evolution and initial state for upcoming studies. We show that the ice encountered on site was exceptionally thin and was formed on the shallow Siberian shelf. The analyses presented provide the initial state for the analysis and interpretation of upcoming biogeochemical and ecological studies.
Sukun Cheng, Justin Stopa, Fabrice Ardhuin, and Hayley H. Shen
The Cryosphere, 14, 2053–2069, https://doi.org/10.5194/tc-14-2053-2020, https://doi.org/10.5194/tc-14-2053-2020, 2020
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Wave states in ice in polar oceans are mostly studied near the ice edge. However, observations in the internal ice field, where ice morphology is very different from the ice edge, are rare. Recently derived wave data from satellite imagery are easier and cheaper than field studies and provide large coverage. This work presents a way of using these data to have a close view of some key features in the wave propagation over hundreds of kilometers and calibrate models for predicting wave decay.
Jutta E. Wollenburg, Morten Iversen, Christian Katlein, Thomas Krumpen, Marcel Nicolaus, Giulia Castellani, Ilka Peeken, and Hauke Flores
The Cryosphere, 14, 1795–1808, https://doi.org/10.5194/tc-14-1795-2020, https://doi.org/10.5194/tc-14-1795-2020, 2020
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Based on an observed omnipresence of gypsum crystals, we concluded that their release from melting sea ice is a general feature in the Arctic Ocean. Individual gypsum crystals sank at more than 7000 m d−1, suggesting that they are an important ballast mineral. Previous observations found gypsum inside phytoplankton aggregates at 2000 m depth, supporting gypsum as an important driver for pelagic-benthic coupling in the ice-covered Arctic Ocean.
Xiaoyong Yu, Annette Rinke, Wolfgang Dorn, Gunnar Spreen, Christof Lüpkes, Hiroshi Sumata, and Vladimir M. Gryanik
The Cryosphere, 14, 1727–1746, https://doi.org/10.5194/tc-14-1727-2020, https://doi.org/10.5194/tc-14-1727-2020, 2020
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This study presents an evaluation of Arctic sea ice drift speed for the period 2003–2014 in a state-of-the-art coupled regional model for the Arctic, called HIRHAM–NAOSIM. In particular, the dependency of the drift speed on the near-surface wind speed and sea ice conditions is presented. Effects of sea ice form drag included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice are discussed.
Yinghui Liu, Jeffrey R. Key, Xuanji Wang, and Mark Tschudi
The Cryosphere, 14, 1325–1345, https://doi.org/10.5194/tc-14-1325-2020, https://doi.org/10.5194/tc-14-1325-2020, 2020
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This study provides a consistent and accurate multi-decadal product of ice thickness and ice volume from 1984 to 2018 based on satellite-derived ice age. Sea ice volume trends from this dataset are stronger than the trends from other datasets. Changes in sea ice thickness contribute more to overall sea ice volume trends than changes in sea ice area do in all months.
Alice K. DuVivier, Patricia DeRepentigny, Marika M. Holland, Melinda Webster, Jennifer E. Kay, and Donald Perovich
The Cryosphere, 14, 1259–1271, https://doi.org/10.5194/tc-14-1259-2020, https://doi.org/10.5194/tc-14-1259-2020, 2020
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In autumn 2019, a ship will be frozen into the Arctic sea ice for a year to study system changes. We analyze climate model data from a group of experiments and follow virtual sea ice floes throughout a year. The modeled sea ice conditions along possible tracks are highly variable. Observations that sample a wide range of sea ice conditions and represent the variety and diversity in possible conditions are necessary for improving climate model parameterizations over all types of sea ice.
Xiao-Yi Yang, Guihua Wang, and Noel Keenlyside
The Cryosphere, 14, 693–708, https://doi.org/10.5194/tc-14-693-2020, https://doi.org/10.5194/tc-14-693-2020, 2020
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The post-2007 Arctic sea ice cover is characterized by a remarkable increase in annual cycle amplitude, which is attributed to multiyear variability in spring Bering sea ice extent. We demonstrated that changes of NPGO mode, by anomalous wind stress curl and Ekman pumping, trigger subsurface variability in the Bering basin. This accounts for the significant decadal oscillation of spring Bering sea ice after 2007. The study helps us to better understand the recent Arctic climate regime shift.
Adam W. Bateson, Daniel L. Feltham, David Schröder, Lucia Hosekova, Jeff K. Ridley, and Yevgeny Aksenov
The Cryosphere, 14, 403–428, https://doi.org/10.5194/tc-14-403-2020, https://doi.org/10.5194/tc-14-403-2020, 2020
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The Arctic sea ice cover has been observed to be decreasing, particularly in summer. We use numerical models to gain insight into processes controlling its seasonal and decadal evolution. Sea ice is made of pieces of ice called floes. Previous models have set these floes to be the same size, which is not supported by observations. In this study we show that accounting for variable floe size reveals the importance of sea ice regions close to the open ocean in driving seasonal retreat of sea ice.
Alex West, Mat Collins, Ed Blockley, Jeff Ridley, and Alejandro Bodas-Salcedo
The Cryosphere, 13, 2001–2022, https://doi.org/10.5194/tc-13-2001-2019, https://doi.org/10.5194/tc-13-2001-2019, 2019
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This study presents a framework for examining the causes of model errors in Arctic sea ice volume, using HadGEM2-ES as a case study. Simple models are used to estimate how much of the error in energy arriving at the ice surface is due to error in key Arctic climate variables. The method quantifies how each variable affects sea ice volume balance and shows that for HadGEM2-ES an annual mean low bias in ice thickness is likely due to errors in surface melt onset.
Caixin Wang, Robert M. Graham, Keguang Wang, Sebastian Gerland, and Mats A. Granskog
The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, https://doi.org/10.5194/tc-13-1661-2019, 2019
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A warm bias and higher total precipitation and snowfall were found in ERA5 compared with ERA-Interim (ERA-I) over Arctic sea ice. The warm bias in ERA5 was larger in the cold season when 2 m air temperature was < −25 °C and smaller in the warm season than in ERA-I. Substantial anomalous Arctic rainfall in ERA-I was reduced in ERA5, particularly in summer and autumn. When using ERA5 and ERA-I to force a 1-D sea ice model, the effects on ice growth are very small (cm) during the freezing period.
John E. Walsh, J. Scott Stewart, and Florence Fetterer
The Cryosphere, 13, 1073–1088, https://doi.org/10.5194/tc-13-1073-2019, https://doi.org/10.5194/tc-13-1073-2019, 2019
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Persistence-based statistical forecasts of a Beaufort Sea ice severity index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the trends are removed from the data. This finding is consistent with the notion of a springtime “predictability barrier” that has been found in sea ice forecasts based on more sophisticated methods.
Leandro Ponsoni, François Massonnet, Thierry Fichefet, Matthieu Chevallier, and David Docquier
The Cryosphere, 13, 521–543, https://doi.org/10.5194/tc-13-521-2019, https://doi.org/10.5194/tc-13-521-2019, 2019
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The Arctic is a main component of the Earth's climate system. It is fundamental to understand the behavior of Arctic sea ice coverage over time and in space due to many factors, e.g., shipping lanes, the travel and tourism industry, hunting and fishing activities, mineral resource extraction, and the potential impact on the weather in midlatitude regions. In this work we use observations and results from models to understand how variations in the sea ice thickness change over time and in space.
John R. Mioduszewski, Stephen Vavrus, Muyin Wang, Marika Holland, and Laura Landrum
The Cryosphere, 13, 113–124, https://doi.org/10.5194/tc-13-113-2019, https://doi.org/10.5194/tc-13-113-2019, 2019
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Arctic sea ice is projected to thin substantially in every season by the end of the 21st century with a corresponding increase in its interannual variability as the rate of ice loss peaks. This typically occurs when the mean ice thickness falls between 0.2 and 0.6 m. The high variability in both growth and melt processes is the primary factor resulting in increased ice variability. This study emphasizes the importance of short-term variations in ice cover within the mean downward trend.
Marion Lebrun, Martin Vancoppenolle, Gurvan Madec, and François Massonnet
The Cryosphere, 13, 79–96, https://doi.org/10.5194/tc-13-79-2019, https://doi.org/10.5194/tc-13-79-2019, 2019
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The present analysis shows that the increase in the Arctic ice-free season duration will be asymmetrical, with later autumn freeze-up contributing about twice as much as earlier spring retreat. This feature is robustly found in a hierarchy of climate models and is consistent with a simple mechanism: solar energy is absorbed more efficiently than it can be released in non-solar form and should emerge out of variability within the next few decades.
Abigail Smith and Alexandra Jahn
The Cryosphere, 13, 1–20, https://doi.org/10.5194/tc-13-1-2019, https://doi.org/10.5194/tc-13-1-2019, 2019
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Here we assessed how natural climate variations and different definitions impact the diagnosed and projected Arctic sea ice melt season length using model simulations. Irrespective of the definition or natural variability, the sea ice melt season is projected to lengthen, potentially by as much as 4–5 months by 2100 under the business as usual scenario. We also find that different definitions have a bigger impact on melt onset, while natural variations have a bigger impact on freeze onset.
Yuanyuan Zhang, Xiao Cheng, Jiping Liu, and Fengming Hui
The Cryosphere, 12, 3747–3757, https://doi.org/10.5194/tc-12-3747-2018, https://doi.org/10.5194/tc-12-3747-2018, 2018
Aaron Letterly, Jeffrey Key, and Yinghui Liu
The Cryosphere, 12, 3373–3382, https://doi.org/10.5194/tc-12-3373-2018, https://doi.org/10.5194/tc-12-3373-2018, 2018
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Significant reductions in Arctic sea ice and snow cover on Arctic land have led to increases in absorbed solar energy by the surface. Does one play a more important role in Arctic climate change? Using 34 years of satellite data we found that solar energy absorption increased by 10 % over the ocean, which was 3 times greater than over land. Therefore, the decreasing sea ice cover, not changes in terrestrial snow cover, has been the dominant feedback mechanism over the last few decades.
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
The Cryosphere, 12, 2569–2594, https://doi.org/10.5194/tc-12-2569-2018, https://doi.org/10.5194/tc-12-2569-2018, 2018
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We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
Cited articles
Aldenhoff, W., Heuzé, C., and Eriksson, L. E. B.: Sensitivity of radar
altimeter waveform changes in sea ice type at resolution of Synthetic
Aperture Radar, Remote Sens., 11, 22, https://doi.org/10.3390/rs11222602, 2019. a
Alexandrov, V., Sandven, S., Wahlin, J., and Johannessen, O. M.: The relation between sea ice thickness and freeboard in the Arctic, The Cryosphere, 4, 373–380, https://doi.org/10.5194/tc-4-373-2010, 2010. a
Babb, D. G., Landy, J. C., Barber, D. G., and Galley, R. J.: Winter sea ice
export from the Beaufort Sea as a preconditioning mechanism for enhanced
summer melt: a case study of 2016, J. Geophys. Res.-Oceans,
124, 6575–6600, https://doi.org/10.1029/2019JC015053, 2019. a
Babb, D. G., Landy, J. C., Lukovich, J. V., Haas, C., Hendricks, S., Barber,
D. G., and Galley, R. J.: The 2017 revarsal of the Beaufort Gyre: can
dynamic thickening of seasonal ice cover during a reversal limit summer ice
melt in the Beaufort Sea, J. Geophys. Res.-Oceans, 125, e2020JC016796,
https://doi.org/10.1029/2020JC016796, 2020. a, b
Babb, D. G., Galley, R. J., Howell, S. E. L., Landy, J. C., Stroeve, J. C., and
Barber, D. G.: Increasing multiyear sea ice loss in the Beaufort Sea: a new
export pathway for the diminishing multiyear ice cover of the Arctic Ocean,
Geophys. Res. Lett., 49, e2021GL097595, https://doi.org/10.1029/2021GL097595, 2022. a, b, c
Barber, D., Babb, D., Ehn, J., Chan, W., Matthes, L., Dalman, L., Campbell, Y.,
Harasyn, M., Firoozy, N., Theriault, N., Lukovich, J., Zagon, T.,
Papakyriakou, T., Capelle, D., Forest, A., and Gariepy, A.: Increasing
mobility of high Arctic sea ice increases marine hazards off the east coast
of Newfoundland, Geophys. Res. Lett., 45, 2370–2379,
https://doi.org/10.1002/2017GL076587, 2018. a
Belmonte Rivas, M., Otosaka, I., Stoffelen, A., and Verhoef, A.: A scatterometer record of sea ice extents and backscatter: 1992–2016, The Cryosphere, 12, 2941–2953, https://doi.org/10.5194/tc-12-2941-2018, 2018. a
Bourke, R. and Garrett, R.: Sea ice thickness distribution in the Arctic
Ocean, Cold Reg. Sci. Technol., 13, 259–280,
https://doi.org/10.1016/0165-232X(87)90007-3, 1987. a
Campbell, K., Matero, I., Bellas, C., Turpin-Jelfs, T., Anhaus, P., Graeve, M.,
Fripiat, F., Tranter, M., Landy, J. C., Sanchez-Baracaldo, P., Leu, E.,
Katlein, C., Mundy, C. J., Rysgaard, S., Tedesco, L., Haas, C., and Nicolaus,
M.: Monitoring a changing Arctic: Recent advancements in the study of sea
ice microbial communities, Ambio, 51, 318–332,
https://doi.org/10.1007/s13280-021-01658-z, 2022. a
Canadian Ice Service (CIS): Regional charts: Canadian Ice Service Ice Regime
Regions (CISIRR) and sub-regions with associated data quality indices, Tech.
rep.,
canadian Ice Service Archive Doc. Ser. 3, Gatineau, Quebec, Canada, http://ice.ec.gc.ca/IA_DOC/cisads_no_003_e.pdf (last access: 5 August 2023),
2007b. a
Dawson, J., Carter, N. A., van Luijk, N., Weber, M., and Cook, A.: Arctic
corridors and northern voices project: Methods for community-based
participatory mapping for low impact shipping corridors in Arctic Canada,
MethodsX, 7, 101064, https://doi.org/10.1016/j.mex.2020.101064, 2020. a
Derksen, C., Burgess, D., Duguay, C., Howell, S., Mudryk, L., Smith, S.,
Thackeray, C., and Kirchmeier-Young, M.: Changes in snow, ice, and permafrost
across Canada: Chapter 5, in: Canada's Changing Climate Report, edited
by: Bush, E. and Lemmen, D., Government of Canada, Ottowa, ISBN 978-0-660-30222-5, 2018. a
Early, D. and Long, D.: Image reconstruction and enhanced resolution from
irregular shape, IEEE T. Geosci. Remote, 39,
291–302, 2001. a
Fetterer, F., Savoie, M., Helfrich, S., and Clemente-Colón, P.: Multisensor
Analyzed Sea Ice Extent – Northern Hemisphere (MASIE-NH), Version 1, Boulder,
Colorado USA, National Snow and Ice Data Center [data set], https://doi.org/10.7265/N5GT5K3K, 2010. a
Fukamachi, Y., Simizu, D., Ohshima, K. I., Eicken, H., Mahoney, A. R., Iwamoto,
K., Moriya, E., and Nihashi, S.: Sea-ice thickness in the coastal
northeastern Chukchi Sea from moored ice-profiling sonar, J.
Glaciol., 63, 888–898, https://doi.org/10.1017/jog.2017.56, 2017. a
Galley, R. J., Babb, D., Ogi, M., Else, B. G. T., Geilfus, N.-X., Crabeck, O.,
Barber, D. G., and Rysgaard, S.: Replacement of multiyear sea ice and
changes in the open water season duration inthe Beaufort Sea since 2004,
J. Geophys. Res.-Oceans, 121, 1806–1823,
https://doi.org/10.1002/2016JC012132, 2016. a
Géron, A.: Hands-on machine learning with scikit-learn, Keras and
Tensorflow, O'Reilly Media, Inc., Sebastopol, USA, 2nd Edn., ISBN 978-1-492-03264-9, 2019. a
Glissenaar, I., Landy, J., Babb, D., Dawson, G., and Howell, S.:
IsoldeGlissenaar/seaiceproxy: Proxy SIT Canadian Arctic, Zenodo [code],
https://doi.org/10.5281/zenodo.7625422, 2023a. a
Glissenaar, I., Landy, J., Babb, D., Dawson, G., and Howell, S.:
IsoldeGlissenaar/CanadianSITproxy: Proxy SIT Canadian Arctic, Zenodo [data set],
https://doi.org/10.5281/zenodo.7644084, 2023b. a
Glissenaar, I. A., Landy, J. C., Petty, A. A., Kurtz, N. T., and Stroeve, J. C.: Impacts of snow data and processing methods on the interpretation of long-term changes in Baffin Bay early spring sea ice thickness, The Cryosphere, 15, 4909–4927, https://doi.org/10.5194/tc-15-4909-2021, 2021. a, b, c, d
Haas, C. and Howell, S.: Ice thickness in the Northwest Passage, Geophys.
Res. Lett., 42, 7673–7680, https://doi.org/10.1002/2015GL065704, 2015. a
Haas, C., Hendricks, S., Eicken, H., and Herber, A.: Synoptic airborne
thickness surveys reveal state of Arctic sea ice cover, Geophys.
Res. Lett., 37, L09501, https://doi.org/10.1029/2010GL042652, 2010. a
Hendricks, S. and Paul, S.: Product Users Guide & Algorithm Specification:
AWI CryoSat-2 Sea Ice Thickness (version 2.5), Zenodo,
https://doi.org/10.5281/zenodo.7416200, 2022. a
Howell, S., Tivy, A., Agnew, T., Markus, T., and Derksen, C.: Extreme low sea
ice years in the Canadian Arctic Archipelago: 1998 versus 2007, J.
Geophys. Res.-Oceans, 115, C10053, https://doi.org/10.1029/2010JC006155, 2010. a
Howell, S. E. L., Brady, M., Derksen, C., and Kelly, R. E. J.: Recent changes
in sea ice area flux through the Beaufort Sea during the summer, J.
Geophys. Res.-Oceans, 121, 2659–2672, https://doi.org/10.1002/2015JC011464,
2016. a, b
Howell, S. E. L., Brady, M., and Komarov, A. S.: Generating large-scale sea ice motion from Sentinel-1 and the RADARSAT Constellation Mission using the Environment and Climate Change Canada automated sea ice tracking system, The Cryosphere, 16, 1125–1139, https://doi.org/10.5194/tc-16-1125-2022, 2022. a, b, c
Hwang, B., Wilkinson, J., Maksym, T., Graber, H. C., Schweiger, A., Horvat, C.,
Perovich, D. K., Arntsen, A. E., Timothy, P., Ren, J., and Wadhams, P.:
Winter-to-summer transition of Arctic sea ice breakup and floe size
distribution in the Beaufort Sea, Elementa, 5, 40,
https://doi.org/10.1525/elementa.232, 2017. a
Kacimi, S. and Kwok, R.: Arctic Snow Depth, Ice Thickness, and Volume From
ICESat-2 and CryoSat-2: 2018–2021, Geophys. Res. Lett., 49, e2021GL097448,
https://doi.org/10.1029/2021GL097448, 2022. a
King, J., Howell, S., Derksen, C., Rutter, N., Toose, P., Beckers, J. F., Haas,
C., Kurtz, N., and Richter-Menge, J.: Evaluation of Operation IceBridge
quick-look snow depth estimates on sea ice, Geophys. Res. Lett.,
42, 9302–9310, https://doi.org/10.1002/2015GL066389, 2015. a, b
King, J., Howell, S., Brady, M., Toose, P., Derksen, C., Haas, C., and Beckers, J.: Local-scale variability of snow density on Arctic sea ice, The Cryosphere, 14, 4323–4339, https://doi.org/10.5194/tc-14-4323-2020, 2020. a, b
Krishfield, R. and Proshutinsky, A.: BGOS ULS Data Processing Procedure,
Tech. rep., Woods Holde Oceanographic Institution, Falmouth, MA, USA,
https://www2.whoi.edu/site/beaufortgyre/wp-content/uploads/sites/108/2020/04/BGOS_ULS_Data_Processing_Procedure_85684.pdf (last access: 7 June 2022),
2006. a, b
Krishfield, R., Proshutinsky, A., Tateyama, K., Williams, W. J., Camack, E. C.,
McLauglin, F. A., and Timmermans, M.-L.: Deterioration of perennial sea ice
in the Beaufort Gyre from 2003 to 2012 and its impact on the oceanic
freshwater cycle, J. Geophys. Res.-Oceans, 119, 1271–1305,
https://doi.org/10.1002/2013JC008999, 2014. a
Kurtz, N., Studinger, M., Harbeck, J., Onana, V., and Yi, D.: IceBridge L4 Sea
Ice Freeboard, Snow-Depth, and Thickness Version 1, National Snow and Ice Data Center [data set],
https://doi.org/10.5067/G519SHCKWQV6, 2015. a, b
Kwok, R.: Sea ice convergence along the Arctic coasts of Greenland and the
Canadian Arctic Archipelago: variability and extremes (1992–2014),
Geophys. Res. Lett., 42, 7598–7605, https://doi.org/10.1002/2015GL065462,
2015. a
Landy, J. C., Petty, A. A., Tsamados, M., and Stroeve, J. C.: Sea ice
roughness overlooked as a key source of uncertainty in CryoSat-2 ice
freeboard retrievals, J. Geophys. Res.-Oceans, 125, e2019JC015820,
https://doi.org/10.1029/2019JC015820, 2020. a, b
Landy, J. C., Dawson, G. J., Tsamados, M., Bushuk, M., Stroeve, J. C., Howell,
S. E. L., Krumpen, T., Babb, D. G., Komarov, A. S., Heorton, H. D. B. S.,
Belter, H. J., and Aksenov, Y.: A year-round satellite sea-ice thickness
record from CryoSat-2, Nature, 609, 517–522,
https://doi.org/10.1038/s41586-022-05058-5, 2022. a, b
Ledley, T. S.: A coupled energy balance climate-sea ice model: impact of sea
ice and leads on climate, J. Geophys. Res., 93,
15919–15932, https://doi.org/10.1029/jd093id12p15919, 1988. a
Lietaer, O., Fichefet, T., and Legat, V.: The effects of resolving the
Canadian Arctic Archipelago in a finite element sea ice model, Ocean
Model., 24, 140–152, https://doi.org/10.1016/j.ocemod.2008.06.002, 2008. a
Lindell, D. B. and Long, D. G.: Multiyear Arctic ice classification using
ASCAT and SSMIS, Remote Sens., 8, 5, https://doi.org/10.3390/rs8040294, 2016. a
Liston, G. E., Itkin, P., Stroeve, J., Tschudi, M., Stewart, J. S., Pedersen,
S. H., Reinking, A. K., and Elder, K.: A Langrangian snow-evolution system
for sea-ice applications (SnowModel-LG): Part I – Model Description, J. Geophys. Res.-Oceans, 125, e2019JC015913, https://doi.org/10.1029/2019JC015913, 2020. a, b
Liu, Y., Key, J. R., Wang, X., and Tschudi, M.: Multidecadal Arctic sea ice thickness and volume derived from ice age, The Cryosphere, 14, 1325–1345, https://doi.org/10.5194/tc-14-1325-2020, 2020. a
Marshall, J. and Schott, F.: Open-Ocean Convection: Observations, theory and
models, Rev. Geophys., 37, 1–64, https://doi.org/10.1029/98RG02739, 1999. a
Maslanik, J. A., Fowler, C., Stroeve, J., Drobot, S., Zwally, J., Yi, D., and
Emery, W.: A younger, thinner Arctic ice cover: Increased potential for
rapid, extensive sea-ice loss, Geophys. Res. Lett., 34, L24501,
https://doi.org/10.1029/2007GL032043, 2017. a
Melling, H.: Sea ice of the northern Canadian Arctic Archipelago, J.
Geophys. Res., 107, 3181, https://doi.org/10.1029/2001JC001102, 2002. a
Melling, H.: Thickness of multi-year sea ice on the northern Canadian polar shelf: a second look after 40 years, The Cryosphere, 16, 3181–3197, https://doi.org/10.5194/tc-16-3181-2022, 2022. a
Melling, H., Agnew, T. A., Flakner, K. K., Greenberg, D. A., Lee, C. M.,
Münchow, A., Petrie, B., Prinsenberg, S. J., Samelson, R. M., and
Woodgate, R. A.: Fresh-water fluxes via Pacific and Arctic outflows across
the Canadian Polar Shelf, in: Arctic-Subarctic Ocean Fluxes, edited by:
Dickson, R. R., Meincke, J., and Rhines, P., Springer, Dordrecht,
https://doi.org/10.1007/978-1-4020-6774-7_10, 2008. a
Melling, H., Haas, C., and Brossier, E.: Invisible polynyas: Modulation of fast
ice thickness by ocean heat flux on the Canadian polar shelf, J.
Geophys. Res.-Oceans, 120, 777–795, https://doi.org/10.1002/2014JC010404,
2015. a
Mudryk, L. R., Derksen, C., Howell, S., Laliberté, F., Thackeray, C., Sospedra-Alfonso, R., Vionnet, V., Kushner, P. J., and Brown, R.: Canadian snow and sea ice: historical trends and projections, The Cryosphere, 12, 1157–1176, https://doi.org/10.5194/tc-12-1157-2018, 2018. a
Mudryk, L. R., Dawson, J., Howell, S. E., Derksen, C., Zagon, T. A., and Brady,
M.: Impact of 1, 2 and 4 ∘C of global warming on ship navigation in
the Canadian Arctic, Nat. Clim. Change, 11, 673–679,
https://doi.org/10.1038/s41558-021-01087-6, 2021. a
Nab, C., Mallett, R., Gregory, W., Landy, J., Lawrence, I., Willatt, R.,
Stroeve, J., and Tsamados, M.: Synoptic variability in satellite
altimeter-derived radar freeboard of Arctic sea ice, Geophys. Res.
Lett., 50, e2022GL100696, https://doi.org/10.1029/2022GL100696, 2023. a
Nandan, V., Geldsetzer, T., Yackel, J., Scharien, R., Howell, S., King, J.,
Ricker, R., and Else, B.: Effect of snow salinity on CryoSat-2 Arctic
first-year sea ice freeboard measurements, Geophys. Res. Lett., 44,
10419–10426, 2017. a
Ontstott, R. G.: SAR and scatterometer signatures of sea ice, in: Microwave
Remote Sensing of Sea Ice, edited by: Carsey, F. D., vol. 68, American
Geophysical Union, Geophysical Monograph Series, Wiley, Hoboken, USA, https://doi.org/10.1029/GM068,
1992. a, b, c
Petty, A. A., Hutchings, J. K., Richter-Menge, J. A., and Tschudi, M. A.: Sea
ice circulation around the Beaufort Gyre: The changing role of wind forcing
and the sea ice state, J. Geophys. Res.-Oceans, 121, 3278–3296,
https://doi.org/10.1002/2015JC010903, 2016. a
Pizzolato, L., Howell, S., Derksen, C., Dawson, J., and Copland, L.: Changing
sea ice conditions and marine transportation activity in Canadian Arctic
waters between 1990 and 2012, Climatic Change, 123, 161–173,
https://doi.org/10.1007/s10584-013-1038-3, 2014. a
Post, E., Bhatt, U. S., Bitz, C. M., Brodie, J. F., Fulton, T. L., Hebblewhite,
M., Kerby, J., Kutz, S. J., Stirling, I., and Walker, D. A.: Ecological
Consequences of Sea-Ice Decline, Science, 341, 519–525,
https://doi.org/10.1126/science.1235225, 2013. a
Preußer, A., Heinemann, G., Willmes, S., and Paul, S.: Multi-decadal
variability of polynya characteristics and ice production in the North Water
Polynya by means of Passive Microwave and Thermal Infrared satellite
imagery, Remote Sens., 7, 15844–15867, https://doi.org/10.3390/rs71215807, 2015. a
Redmond Roche, B. H. and King, M. D.: Quantifying the effects of background concentrations of crude oil pollution on sea ice albedo, The Cryosphere, 16, 3949–3970, https://doi.org/10.5194/tc-16-3949-2022, 2022. a
Ricker, R., Hendricks, S., Helm, V., Skourup, H., and Davidson, M.: Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation, The Cryosphere, 8, 1607–1622, https://doi.org/10.5194/tc-8-1607-2014, 2014. a
Schweiger, A., Lindsay, R., Zhang, J., Steele, M., Stern, H., and Kwok, R.:
Uncertainty in modeled Arctic sea ice volume, J. Geophys.
Res.-Oceans, 116, C00D06, https://doi.org/10.1029/2011JC007084, 2011. a, b, c
Stroeve, J., Liston, G., Buzzard, S., Zhou, L., Mallett, R., Barrett, A.,
Tschudi, M., Tsamados, M., Itkin, P., and Stewart, J.: A Langrangian
snow-evolution system for sea-ice applications (SnowModel-LG): Part II –
Analyses, J. Geophys. Res.-Oceans, 125, e2019JC015913,
https://doi.org/10.1029/2019JC015913, 2020.
a
Stroeve, J., Nandan, V., Willatt, R., Dadic, R., Rostosky, P., Gallagher, M., Mallett, R., Barrett, A., Hendricks, S., Tonboe, R., McCrystall, M., Serreze, M., Thielke, L., Spreen, G., Newman, T., Yackel, J., Ricker, R., Tsamados, M., Macfarlane, A., Hannula, H.-R., and Schneebeli, M.: Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate), The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, 2022. a
Tilling, R., Ridout, A., and Shepherd, A.: Assessing the Impact of Lead and
Floe Sampling on Arctic Sea Ice Thickness Estimates from Envisat and CryoSat
– 2, J. Geophys. Res.-Oceans, 124, 7473–7485,
https://doi.org/10.1029/2019JC015232, 2019. a
Tivy, A., Howell, S. E. L., Alt, B., McCourt, S., Chagnon, R., Crocker, G.,
Carrieres, T., and Yackel, J. J.: Trends and variability in summer sea ice
cover in the Canadian Arctic based on the Canadian Ice Service Digital
Archive, 1960–2008 and 1968–2008, J. Geophys. Res.-Oceans,
116, C03007, https://doi.org/10.1029/2009JC005855, 2011. a, b, c, d, e, f, g
Tschudi, M. A., Stroeve, J. C., and Stewart, J. S.: Relating the age of Arctic
sea ice to its thickness, as measured during NASA's ICESat and IceBridge
campaigns, Remote Sens., 8, 6, https://doi.org/10.3390/rs8060457, 2016. a
Willatt, R., Laxon, S., Giles, K., Cullen, R., Haas, C., and Helm, V.: Ku-band
radar penetration into snow cover on Arctic sea ice using airborne data,
Ann. Glaciol., 52, 197–205, https://doi.org/10.3189/172756411795931589, 2011. a
Zhang, J. and Rothrock, D.: Modeling global sea ice with a thickness and
enthalpy distribution model in generalized curvilinear coordinates, Mon. Weather Rev., 131,
845–861, https://doi.org/10.1175/1520-0493(2003)131<0845:MGSIWA>2.0.CO;2, 2003. a
Zhang, Z., Yu, Y., Li, X., Hui, F., Cheng, X., and Chen, Z.: Arctic sea ice
classification using microwave scatterometer and radiometer data during
2002–2017, IEEE T. Geosci. Remote, 57,
5319–5328, https://doi.org/10.1109/TGRS.2019.2898872, 2019. a
Short summary
Observations of large-scale ice thickness have unfortunately only been available since 2003, a short record for researching trends and variability. We generated a proxy for sea ice thickness in the Canadian Arctic for 1996–2020. This is the longest available record for large-scale sea ice thickness available to date and the first record reliably covering the channels between the islands in northern Canada. The product shows that sea ice has thinned by 21 cm over the 25-year record in April.
Observations of large-scale ice thickness have unfortunately only been available since 2003, a...
