- About
- Editorial board
- Articles
- Special issues
- Highlight articles
- Manuscript tracking
- Subscribe to alerts
- Peer review
- For authors
- For reviewers
- EGU publications
Journal cover
Journal topic
The Cryosphere
An interactive open-access journal of the European Geosciences Union
Journal topic
- About
- Editorial board
- Articles
- Special issues
- Highlight articles
- Manuscript tracking
- Subscribe to alerts
- Peer review
- For authors
- For reviewers
- EGU publications
Journal metrics
Journal metrics
IF 4.713
4.927CiteScore
8.0SNIP 1.425
SJR 2.353
index 71h5-index 53
Abstracted/indexed
Abstracted/indexed
Volume 8, issue 5
The Cryosphere, 8, 1839–1854, 2014
https://doi.org/10.5194/tc-8-1839-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-8-1839-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 8, 1839–1854, 2014
https://doi.org/10.5194/tc-8-1839-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-8-1839-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article 10 Oct 2014
Research article | 10 Oct 2014
Using records from submarine, aircraft and satellites to evaluate climate model simulations of Arctic sea ice thickness
J. Stroeve et al.
Related authors
Rasmus T. Tonboe, Vishnu Nandan, John Yackel, Stefan Kern, Leif Toudal Pedersen, and Julienne Stroeve
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-196, https://doi.org/10.5194/tc-2020-196, 2020
Preprint under review for TC
Short summary
Short summary
A relationship between the Ku-band radar scattering horizon and snow depth is found using a radar scattering model. This relationship has implications for 1) the use of snow climatology in the conversion of satellite radar freeboard into sea ice thickness and 2) the impact of variability in measured snow depth on the derived ice thickness. For both 1 and 2, the impact of using a snow climatology versus the actual snow depth is relatively small.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, Robbie Mallett, and Michel Tsamados
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-151, https://doi.org/10.5194/tc-2020-151, 2020
Preprint under review for TC
Short summary
Short summary
This study provides the first look of the data collected by a new dual frequency Ka/Ku-band in situ radar over winter sea ice in the Arctic Ocean. Instrument shows potential to use both bands to retrieve snow depth over sea ice, as well as sensitivity of the measurements to changing snow and atmospheric conditions.
Lu Zhou, Julienne Stroeve, Shiming Xu, Alek Petty, Rachel Tilling, Mai Winstrup, Philip Rostosky, Isobel R. Lawrence, Glen E. Liston, Andy Ridout, Michel Tsamados, and Vishnu Nandan
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-65, https://doi.org/10.5194/tc-2020-65, 2020
Preprint under review for TC
Short summary
Short summary
Snow on sea ice plays an important role in the Arctic climate system. Large spatial and temporal discrepancies among the eight snow depth products are analyzed together with their seasonal variability and long-term trends. These snow products are further compared against various ground-truth observations. More analysis on representation error of sea ice parameters are needed for systematic comparison and fusion of airborne, in-situ and remote sensing observations.
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
Short summary
Short summary
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.
Masa Kageyama, Louise C. Sime, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, David Schroeder, Ruediger Stein, Irene Malmierca-Vallet, Ayako Abe-Ouchi, Cecilia Bitz, Pascale Braconnot, Esther Brady, Matthew A. Chamberlain, Danny Feltham, Chuncheng Guo, Gerrit Lohmann, Katrin Meissner, Laurie Menviel, Polina Morozova, Kerim H. Nisancioglu, Bette Otto-Bliesner, Ryouta O'ishi, Sam Sherriff-Tadano, Julienne Stroeve, Xiaoxu Shi, Bo Sun, Evgeny Volodin, Nicholas Yeung, Qiong Zhang, Zhongshi Zhang, and Tilo Ziehn
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-165, https://doi.org/10.5194/cp-2019-165, 2020
Preprint under review for CP
Short summary
Short summary
The Last interglacial (ca. 127000 years ago) is a period with increased summer insolation at high northern latitudes, resulting in a strong reduction in Arctic sea ice. The latest PMIP4-CMIP6 models all simulate this decrease, consistent with reconstructions. However, neither the models nor the reconstructions agree on the possibility of an seasonally ice free Arctic. Work to clarifying the reasons of model divergence and of conflicting interpretations of the records will therefore be needed.
Isobel R. Lawrence, Michel C. Tsamados, Julienne C. Stroeve, Thomas W. K. Armitage, and Andy L. Ridout
The Cryosphere, 12, 3551–3564, https://doi.org/10.5194/tc-12-3551-2018, https://doi.org/10.5194/tc-12-3551-2018, 2018
Short summary
Short summary
In this paper we estimate the thickness of snow cover on Arctic sea ice from space. We use data from two radar altimeter satellites, AltiKa and CryoSat-2, that have been operating synchronously since 2013. We produce maps of monthly average snow depth for the four growth seasons (October to April): 2012–2013, 2013–2014, 2014–2015, and 2015–2016. Snow depth estimates are essential for the accurate retrieval of sea ice thickness from satellite altimetry.
Julienne C. Stroeve, David Schroder, Michel Tsamados, and Daniel Feltham
The Cryosphere, 12, 1791–1809, https://doi.org/10.5194/tc-12-1791-2018, https://doi.org/10.5194/tc-12-1791-2018, 2018
Short summary
Short summary
This paper looks at the impact of the warm winter and anomalously low number of total freezing degree days during winter 2016/2017 on thermodynamic ice growth and overall thickness anomalies. The approach relies on evaluation of satellite data (CryoSat-2) and model output. While there is a negative feedback between rapid ice growth for thin ice, with thermodynamic ice growth increasing over time, since 2012 that relationship is changing, in part because the freeze-up is happening later.
Alek A. Petty, Julienne C. Stroeve, Paul R. Holland, Linette N. Boisvert, Angela C. Bliss, Noriaki Kimura, and Walter N. Meier
The Cryosphere, 12, 433–452, https://doi.org/10.5194/tc-12-433-2018, https://doi.org/10.5194/tc-12-433-2018, 2018
Short summary
Short summary
There was significant scientific and media attention surrounding Arctic sea ice in 2016, due primarily to the record-warm air temperatures and low sea ice conditions observed at the start of the year. Here we quantify and assess the record-low monthly sea ice cover in winter, spring and fall, and the lack of record-low sea ice conditions in summer. We explore the primary drivers of these monthly sea ice states and explore the implications for improved summer sea ice forecasting.
Julienne C. Stroeve, John R. Mioduszewski, Asa Rennermalm, Linette N. Boisvert, Marco Tedesco, and David Robinson
The Cryosphere, 11, 2363–2381, https://doi.org/10.5194/tc-11-2363-2017, https://doi.org/10.5194/tc-11-2363-2017, 2017
Short summary
Short summary
As the sea ice has declined strongly in recent years there has been a corresponding increase in Greenland melting. While both are likely a result of changes in atmospheric circulation patterns that favor summer melt, this study evaluates whether or not sea ice reductions around the Greenland ice sheet are having an influence on Greenland summer melt through enhanced sensible and latent heat transport from open water areas onto the ice sheet.
Lars H. Smedsrud, Mari H. Halvorsen, Julienne C. Stroeve, Rong Zhang, and Kjell Kloster
The Cryosphere, 11, 65–79, https://doi.org/10.5194/tc-11-65-2017, https://doi.org/10.5194/tc-11-65-2017, 2017
Short summary
Short summary
Export of Arctic sea ice area southwards through the Fram Strait from 1935 to 2014 is calculated based on satellite radar images and surface pressure observations. The annual mean export is 880 000 km2, representing 10 % of the Arctic sea ice area. In recent years the export has been above 1 million km2, and there are positive trends over the last 30 years. Increased ice export during spring and summer contributes to more open water in September, and this correlations has increased over time.
Dirk Notz, Alexandra Jahn, Marika Holland, Elizabeth Hunke, François Massonnet, Julienne Stroeve, Bruno Tremblay, and Martin Vancoppenolle
Geosci. Model Dev., 9, 3427–3446, https://doi.org/10.5194/gmd-9-3427-2016, https://doi.org/10.5194/gmd-9-3427-2016, 2016
Short summary
Short summary
The large-scale evolution of sea ice is both an indicator and a driver of climate changes. Hence, a realistic simulation of sea ice is key for a realistic simulation of the climate system of our planet. To assess and to improve the realism of sea-ice simulations, we present here a new protocol for climate-model output that allows for an in-depth analysis of the simulated evolution of sea ice.
Julienne C. Stroeve, Stephanie Jenouvrier, G. Garrett Campbell, Christophe Barbraud, and Karine Delord
The Cryosphere, 10, 1823–1843, https://doi.org/10.5194/tc-10-1823-2016, https://doi.org/10.5194/tc-10-1823-2016, 2016
Short summary
Short summary
Sea ice variability within the marginal ice zone and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore mapping their spatial extent as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Assessments are complicated, however, by which sea ice algorithm is used, with impacts on interpretations on seabird populations.
Marco Tedesco, Sarah Doherty, Xavier Fettweis, Patrick Alexander, Jeyavinoth Jeyaratnam, and Julienne Stroeve
The Cryosphere, 10, 477–496, https://doi.org/10.5194/tc-10-477-2016, https://doi.org/10.5194/tc-10-477-2016, 2016
Short summary
Short summary
Summer surface albedo over Greenland decreased at a rate of 0.02 per decade between 1996 and 2012. The decrease is due to snow grain growth, the expansion of bare ice areas, and trends in light-absorbing impurities on snow and ice surfaces. Neither aerosol models nor in situ observations indicate increasing trends in impurities in the atmosphere over Greenland. Albedo projections through to the end of the century under different warming scenarios consistently point to continued darkening.
Rasmus T. Tonboe, Vishnu Nandan, John Yackel, Stefan Kern, Leif Toudal Pedersen, and Julienne Stroeve
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-196, https://doi.org/10.5194/tc-2020-196, 2020
Preprint under review for TC
Short summary
Short summary
A relationship between the Ku-band radar scattering horizon and snow depth is found using a radar scattering model. This relationship has implications for 1) the use of snow climatology in the conversion of satellite radar freeboard into sea ice thickness and 2) the impact of variability in measured snow depth on the derived ice thickness. For both 1 and 2, the impact of using a snow climatology versus the actual snow depth is relatively small.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, Robbie Mallett, and Michel Tsamados
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-151, https://doi.org/10.5194/tc-2020-151, 2020
Preprint under review for TC
Short summary
Short summary
This study provides the first look of the data collected by a new dual frequency Ka/Ku-band in situ radar over winter sea ice in the Arctic Ocean. Instrument shows potential to use both bands to retrieve snow depth over sea ice, as well as sensitivity of the measurements to changing snow and atmospheric conditions.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killik, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-255, https://doi.org/10.5194/essd-2019-255, 2020
Preprint under review for ESSD
Short summary
Short summary
Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory over the period 1960–2018.
Lu Zhou, Julienne Stroeve, Shiming Xu, Alek Petty, Rachel Tilling, Mai Winstrup, Philip Rostosky, Isobel R. Lawrence, Glen E. Liston, Andy Ridout, Michel Tsamados, and Vishnu Nandan
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-65, https://doi.org/10.5194/tc-2020-65, 2020
Preprint under review for TC
Short summary
Short summary
Snow on sea ice plays an important role in the Arctic climate system. Large spatial and temporal discrepancies among the eight snow depth products are analyzed together with their seasonal variability and long-term trends. These snow products are further compared against various ground-truth observations. More analysis on representation error of sea ice parameters are needed for systematic comparison and fusion of airborne, in-situ and remote sensing observations.
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
Short summary
Short summary
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.
Masa Kageyama, Louise C. Sime, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, David Schroeder, Ruediger Stein, Irene Malmierca-Vallet, Ayako Abe-Ouchi, Cecilia Bitz, Pascale Braconnot, Esther Brady, Matthew A. Chamberlain, Danny Feltham, Chuncheng Guo, Gerrit Lohmann, Katrin Meissner, Laurie Menviel, Polina Morozova, Kerim H. Nisancioglu, Bette Otto-Bliesner, Ryouta O'ishi, Sam Sherriff-Tadano, Julienne Stroeve, Xiaoxu Shi, Bo Sun, Evgeny Volodin, Nicholas Yeung, Qiong Zhang, Zhongshi Zhang, and Tilo Ziehn
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-165, https://doi.org/10.5194/cp-2019-165, 2020
Preprint under review for CP
Short summary
Short summary
The Last interglacial (ca. 127000 years ago) is a period with increased summer insolation at high northern latitudes, resulting in a strong reduction in Arctic sea ice. The latest PMIP4-CMIP6 models all simulate this decrease, consistent with reconstructions. However, neither the models nor the reconstructions agree on the possibility of an seasonally ice free Arctic. Work to clarifying the reasons of model divergence and of conflicting interpretations of the records will therefore be needed.
Isobel R. Lawrence, Michel C. Tsamados, Julienne C. Stroeve, Thomas W. K. Armitage, and Andy L. Ridout
The Cryosphere, 12, 3551–3564, https://doi.org/10.5194/tc-12-3551-2018, https://doi.org/10.5194/tc-12-3551-2018, 2018
Short summary
Short summary
In this paper we estimate the thickness of snow cover on Arctic sea ice from space. We use data from two radar altimeter satellites, AltiKa and CryoSat-2, that have been operating synchronously since 2013. We produce maps of monthly average snow depth for the four growth seasons (October to April): 2012–2013, 2013–2014, 2014–2015, and 2015–2016. Snow depth estimates are essential for the accurate retrieval of sea ice thickness from satellite altimetry.
Julienne C. Stroeve, David Schroder, Michel Tsamados, and Daniel Feltham
The Cryosphere, 12, 1791–1809, https://doi.org/10.5194/tc-12-1791-2018, https://doi.org/10.5194/tc-12-1791-2018, 2018
Short summary
Short summary
This paper looks at the impact of the warm winter and anomalously low number of total freezing degree days during winter 2016/2017 on thermodynamic ice growth and overall thickness anomalies. The approach relies on evaluation of satellite data (CryoSat-2) and model output. While there is a negative feedback between rapid ice growth for thin ice, with thermodynamic ice growth increasing over time, since 2012 that relationship is changing, in part because the freeze-up is happening later.
Alek A. Petty, Julienne C. Stroeve, Paul R. Holland, Linette N. Boisvert, Angela C. Bliss, Noriaki Kimura, and Walter N. Meier
The Cryosphere, 12, 433–452, https://doi.org/10.5194/tc-12-433-2018, https://doi.org/10.5194/tc-12-433-2018, 2018
Short summary
Short summary
There was significant scientific and media attention surrounding Arctic sea ice in 2016, due primarily to the record-warm air temperatures and low sea ice conditions observed at the start of the year. Here we quantify and assess the record-low monthly sea ice cover in winter, spring and fall, and the lack of record-low sea ice conditions in summer. We explore the primary drivers of these monthly sea ice states and explore the implications for improved summer sea ice forecasting.
Julienne C. Stroeve, John R. Mioduszewski, Asa Rennermalm, Linette N. Boisvert, Marco Tedesco, and David Robinson
The Cryosphere, 11, 2363–2381, https://doi.org/10.5194/tc-11-2363-2017, https://doi.org/10.5194/tc-11-2363-2017, 2017
Short summary
Short summary
As the sea ice has declined strongly in recent years there has been a corresponding increase in Greenland melting. While both are likely a result of changes in atmospheric circulation patterns that favor summer melt, this study evaluates whether or not sea ice reductions around the Greenland ice sheet are having an influence on Greenland summer melt through enhanced sensible and latent heat transport from open water areas onto the ice sheet.
Lars H. Smedsrud, Mari H. Halvorsen, Julienne C. Stroeve, Rong Zhang, and Kjell Kloster
The Cryosphere, 11, 65–79, https://doi.org/10.5194/tc-11-65-2017, https://doi.org/10.5194/tc-11-65-2017, 2017
Short summary
Short summary
Export of Arctic sea ice area southwards through the Fram Strait from 1935 to 2014 is calculated based on satellite radar images and surface pressure observations. The annual mean export is 880 000 km2, representing 10 % of the Arctic sea ice area. In recent years the export has been above 1 million km2, and there are positive trends over the last 30 years. Increased ice export during spring and summer contributes to more open water in September, and this correlations has increased over time.
Dirk Notz, Alexandra Jahn, Marika Holland, Elizabeth Hunke, François Massonnet, Julienne Stroeve, Bruno Tremblay, and Martin Vancoppenolle
Geosci. Model Dev., 9, 3427–3446, https://doi.org/10.5194/gmd-9-3427-2016, https://doi.org/10.5194/gmd-9-3427-2016, 2016
Short summary
Short summary
The large-scale evolution of sea ice is both an indicator and a driver of climate changes. Hence, a realistic simulation of sea ice is key for a realistic simulation of the climate system of our planet. To assess and to improve the realism of sea-ice simulations, we present here a new protocol for climate-model output that allows for an in-depth analysis of the simulated evolution of sea ice.
Julienne C. Stroeve, Stephanie Jenouvrier, G. Garrett Campbell, Christophe Barbraud, and Karine Delord
The Cryosphere, 10, 1823–1843, https://doi.org/10.5194/tc-10-1823-2016, https://doi.org/10.5194/tc-10-1823-2016, 2016
Short summary
Short summary
Sea ice variability within the marginal ice zone and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore mapping their spatial extent as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Assessments are complicated, however, by which sea ice algorithm is used, with impacts on interpretations on seabird populations.
Marco Tedesco, Sarah Doherty, Xavier Fettweis, Patrick Alexander, Jeyavinoth Jeyaratnam, and Julienne Stroeve
The Cryosphere, 10, 477–496, https://doi.org/10.5194/tc-10-477-2016, https://doi.org/10.5194/tc-10-477-2016, 2016
Short summary
Short summary
Summer surface albedo over Greenland decreased at a rate of 0.02 per decade between 1996 and 2012. The decrease is due to snow grain growth, the expansion of bare ice areas, and trends in light-absorbing impurities on snow and ice surfaces. Neither aerosol models nor in situ observations indicate increasing trends in impurities in the atmosphere over Greenland. Albedo projections through to the end of the century under different warming scenarios consistently point to continued darkening.
Related subject area
Sea Ice
Statistical predictability of the Arctic sea ice volume anomaly: identifying predictors and optimal sampling locations
Satellite-based sea ice thickness changes in the Laptev Sea from 2002 to 2017: comparison to mooring observations
Modeling the annual cycle of daily Antarctic sea ice extent
Changes of the Arctic marginal ice zone during the satellite era
An enhancement to sea ice motion and age products at the National Snow and Ice Data Center (NSIDC)
Accuracy and inter-analyst agreement of visually estimated sea ice concentrations in Canadian Ice Service ice charts using single-polarization RADARSAT-2
Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks
Variability scaling and consistency in airborne and satellite altimetry measurements of Arctic sea ice
Sea ice volume variability and water temperature in the Greenland Sea
Sea ice export through the Fram Strait derived from a combined model and satellite data set
Estimating early-winter Antarctic sea ice thickness from deformed ice morphology
On the multi-fractal scaling properties of sea ice deformation
Brief communication: Pancake ice floe size distribution during the winter expansion of the Antarctic marginal ice zone
What historical landfast ice observations tell us about projected ice conditions in Arctic archipelagoes and marginal seas under anthropogenic forcing
Interannual sea ice thickness variability in the Bay of Bothnia
Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness
Brief communication: Solar radiation management not as effective as CO2 mitigation for Arctic sea ice loss in hitting the 1.5 and 2 °C COP climate targets
Reflective properties of melt ponds on sea ice
The color of melt ponds on Arctic sea ice
On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data
A network model for characterizing brine channels in sea ice
Impact of rheology on probabilistic forecasts of sea ice trajectories: application for search and rescue operations in the Arctic
Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models
Mechanisms influencing seasonal to inter-annual prediction skill of sea ice extent in the Arctic Ocean in MIROC
Floe-size distributions in laboratory ice broken by waves
The Arctic sea ice cover of 2016: a year of record-low highs and higher-than-expected lows
Consistent biases in Antarctic sea ice concentration simulated by climate models
Frazil-ice growth rate and dynamics in mixed layers and sub-ice-shelf plumes
How much should we believe correlations between Arctic cyclones and sea ice extent?
Optical properties of sea ice doped with black carbon – an experimental and radiative-transfer modelling comparison
Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6
Wave-induced stress and breaking of sea ice in a coupled hydrodynamic discrete-element wave–ice model
Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge
Winter sea ice export from the Laptev Sea preconditions the local summer sea ice cover and fast ice decay
Sea ice assimilation into a coupled ocean–sea ice model using its adjoint
Modelling radiative transfer through ponded first-year Arctic sea ice with a plane-parallel model
Brief communication: Increasing shortwave absorption over the Arctic Ocean is not balanced by trends in the Antarctic
Wave–ice interactions in the neXtSIM sea-ice model
Ice bridges and ridges in the Maxwell-EB sea ice rheology
Comparison of CryoSat-2 and ENVISAT radar freeboard over Arctic sea ice: toward an improved Envisat freeboard retrieval
Open-source sea ice drift algorithm for Sentinel-1 SAR imagery using a combination of feature tracking and pattern matching
Method to characterize directional changes in Arctic sea ice drift and associated deformation due to synoptic atmospheric variations using Lagrangian dispersion statistics
A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data
Sea-ice deformation in a coupled ocean–sea-ice model and in satellite remote sensing data
Impacts of freshwater changes on Antarctic sea ice in an eddy-permitting sea-ice–ocean model
A simple model for the evolution of melt pond coverage on permeable Arctic sea ice
Brief communication: Impacts of ocean-wave-induced breakup of Antarctic sea ice via thermodynamics in a stand-alone version of the CICE sea-ice model
Interactions between Antarctic sea ice and large-scale atmospheric modes in CMIP5 models
Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years
Operational algorithm for ice–water classification on dual-polarized RADARSAT-2 images
Leandro Ponsoni, François Massonnet, David Docquier, Guillian Van Achter, and Thierry Fichefet
The Cryosphere, 14, 2409–2428, https://doi.org/10.5194/tc-14-2409-2020, https://doi.org/10.5194/tc-14-2409-2020, 2020
Short summary
Short summary
The continuous melting of the Arctic sea ice observed in the last decades has a significant impact at global and regional scales. To understand the amplitude and consequences of this impact, the monitoring of the total sea ice volume is crucial. However, in situ monitoring in such a harsh environment is hard to perform and far too expensive. This study shows that four well-placed sampling locations are sufficient to explain about 70 % of the inter-annual changes in the pan-Arctic sea ice volume.
H. Jakob Belter, Thomas Krumpen, Stefan Hendricks, Jens Hoelemann, Markus A. Janout, Robert Ricker, and Christian Haas
The Cryosphere, 14, 2189–2203, https://doi.org/10.5194/tc-14-2189-2020, https://doi.org/10.5194/tc-14-2189-2020, 2020
Short summary
Short summary
The validation of satellite sea ice thickness (SIT) climate data records with newly acquired moored sonar SIT data shows that satellite products provide modal rather than mean SIT in the Laptev Sea region. This tendency of satellite-based SIT products to underestimate mean SIT needs to be considered for investigations of sea ice volume transports. Validation of satellite SIT in the first-year-ice-dominated Laptev Sea will support algorithm development for more reliable SIT records in the Arctic.
Mark S. Handcock and Marilyn N. Raphael
The Cryosphere, 14, 2159–2172, https://doi.org/10.5194/tc-14-2159-2020, https://doi.org/10.5194/tc-14-2159-2020, 2020
Short summary
Short summary
Traditional methods of calculating the annual cycle of sea ice extent disguise the variation of amplitude and timing (phase) of the advance and retreat of the ice. We present a multiscale model that explicitly allows them to vary, resulting in a much improved representation of the cycle. We show that phase is the dominant contributor to the variability in the cycle and that the anomalous decay of Antarctic sea ice in 2016 was due largely to a change of phase.
Rebecca J. Rolph, Daniel L. Feltham, and David Schröder
The Cryosphere, 14, 1971–1984, https://doi.org/10.5194/tc-14-1971-2020, https://doi.org/10.5194/tc-14-1971-2020, 2020
Short summary
Short summary
It is well known that the Arctic sea ice extent is declining, and it is often assumed that the marginal ice zone (MIZ), the area of partial sea ice cover, is consequently increasing. However, we find no trend in the MIZ extent during the last 40 years from observations that is consistent with a widening of the MIZ as it moves northward. Differences of MIZ extent between different satellite retrievals are too large to provide a robust basis to verify model simulations of MIZ extent.
Mark A. Tschudi, Walter N. Meier, and J. Scott Stewart
The Cryosphere, 14, 1519–1536, https://doi.org/10.5194/tc-14-1519-2020, https://doi.org/10.5194/tc-14-1519-2020, 2020
Short summary
Short summary
A new version of a set of data products that contain the velocity of sea ice and the age of this ice has been developed. We provide a history of the product development and discuss the improvements to the algorithms that create these products. We find that changes in sea ice motion and age show a significant shift in the Arctic ice cover, from a pack with a high concentration of older ice to a sea ice cover dominated by younger ice, which is more susceptible to summer melt.
Angela Cheng, Barbara Casati, Adrienne Tivy, Tom Zagon, Jean-François Lemieux, and L. Bruno Tremblay
The Cryosphere, 14, 1289–1310, https://doi.org/10.5194/tc-14-1289-2020, https://doi.org/10.5194/tc-14-1289-2020, 2020
Short summary
Short summary
Sea ice charts by the Canadian Ice Service (CIS) contain visually estimated ice concentration produced by analysts. The accuracy of manually derived ice concentrations is not well understood. The subsequent uncertainty of ice charts results in downstream uncertainties for ice charts users, such as models and climatology studies, and when used as a verification source for automated sea ice classifiers. This study quantifies the level of accuracy and inter-analyst agreement for ice charts by CIS.
Young Jun Kim, Hyun-Cheol Kim, Daehyeon Han, Sanggyun Lee, and Jungho Im
The Cryosphere, 14, 1083–1104, https://doi.org/10.5194/tc-14-1083-2020, https://doi.org/10.5194/tc-14-1083-2020, 2020
Short summary
Short summary
In this study, we proposed a novel 1-month sea ice concentration (SIC) prediction model with eight predictors using a deep-learning approach, convolutional neural networks (CNNs). The proposed CNN model was evaluated and compared with the two baseline approaches, random-forest and simple-regression models, resulting in better performance. This study also examined SIC predictions for two extreme cases in 2007 and 2012 in detail and the influencing factors through a sensitivity analysis.
Shiming Xu, Lu Zhou, and Bin Wang
The Cryosphere, 14, 751–767, https://doi.org/10.5194/tc-14-751-2020, https://doi.org/10.5194/tc-14-751-2020, 2020
Short summary
Short summary
Sea ice thickness parameters are key to polar climate change studies and forecasts. Airborne and satellite measurements provide complementary observational capabilities. The study analyzes the variability in freeboard and snow depth measurements and its changes with scale in Operation IceBridge, CryoVEx, CryoSat-2 and ICESat. Consistency between airborne and satellite data is checked. Analysis calls for process-oriented attribution of variability and covariability features of these parameters.
Valeria Selyuzhenok, Igor Bashmachnikov, Robert Ricker, Anna Vesman, and Leonid Bobylev
The Cryosphere, 14, 477–495, https://doi.org/10.5194/tc-14-477-2020, https://doi.org/10.5194/tc-14-477-2020, 2020
Short summary
Short summary
This study explores a link between the long-term variations in the integral sea ice volume in the Greenland Sea and oceanic processes. We link the changes in the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) regional sea ice volume with the mixed layer, depth and upper-ocean heat content derived using the ARMOR dataset.
Chao Min, Longjiang Mu, Qinghua Yang, Robert Ricker, Qian Shi, Bo Han, Renhao Wu, and Jiping Liu
The Cryosphere, 13, 3209–3224, https://doi.org/10.5194/tc-13-3209-2019, https://doi.org/10.5194/tc-13-3209-2019, 2019
Short summary
Short summary
Sea ice volume export through the Fram Strait has been studied using varied methods, however, mostly in winter months. Here we report sea ice volume estimates that extend over summer seasons. A recent developed sea ice thickness dataset, in which CryoSat-2 and SMOS sea ice thickness together with SSMI/SSMIS sea ice concentration are assimilated, is used and evaluated in the paper. Results show our estimate is more reasonable than that calculated by satellite data only.
M. Jeffrey Mei, Ted Maksym, Blake Weissling, and Hanumant Singh
The Cryosphere, 13, 2915–2934, https://doi.org/10.5194/tc-13-2915-2019, https://doi.org/10.5194/tc-13-2915-2019, 2019
Short summary
Short summary
Sea ice thickness is hard to measure directly, and current datasets are very limited to sporadically conducted drill lines. However, surface elevation is much easier to measure. Converting surface elevation to ice thickness requires making assumptions about snow depth and density, which leads to large errors (and may not generalize to new datasets). A deep learning method is presented that uses the surface morphology as a direct predictor of sea ice thickness, with testing errors of < 20 %.
Pierre Rampal, Véronique Dansereau, Einar Olason, Sylvain Bouillon, Timothy Williams, Anton Korosov, and Abdoulaye Samaké
The Cryosphere, 13, 2457–2474, https://doi.org/10.5194/tc-13-2457-2019, https://doi.org/10.5194/tc-13-2457-2019, 2019
Short summary
Short summary
In this article, we look at how the Arctic sea ice cover, as a solid body, behaves on different temporal and spatial scales. We show that the numerical model neXtSIM uses a new approach to simulate the mechanics of sea ice and reproduce the characteristics of how sea ice deforms, as observed by satellite. We discuss the importance of this model performance in the context of simulating climate processes taking place in polar regions, like the exchange of energy between the ocean and atmosphere.
Alberto Alberello, Miguel Onorato, Luke Bennetts, Marcello Vichi, Clare Eayrs, Keith MacHutchon, and Alessandro Toffoli
The Cryosphere, 13, 41–48, https://doi.org/10.5194/tc-13-41-2019, https://doi.org/10.5194/tc-13-41-2019, 2019
Short summary
Short summary
Existing observations do not provide quantitative descriptions of the floe size distribution for pancake ice floes. This is important during the Antarctic winter sea ice expansion, when hundreds of kilometres of ice cover around the Antarctic continent are composed of pancake floes (D = 0.3–3 m). Here, a new set of images from the Antarctic marginal ice zone is used to measure the shape of individual pancakes for the first time and to infer their size distribution.
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
Short summary
Short summary
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.
Iina Ronkainen, Jonni Lehtiranta, Mikko Lensu, Eero Rinne, Jari Haapala, and Christian Haas
The Cryosphere, 12, 3459–3476, https://doi.org/10.5194/tc-12-3459-2018, https://doi.org/10.5194/tc-12-3459-2018, 2018
Short summary
Short summary
We quantify the sea ice thickness variability in the Bay of Bothnia using various observational data sets. For the first time we use helicopter and shipborne electromagnetic soundings to study changes in drift ice of the Bay of Bothnia. Our results show that the interannual variability of ice thickness is larger in the drift ice zone than in the fast ice zone. Furthermore, the mean thickness of heavily ridged ice near the coast can be several times larger than that of fast ice.
Edward W. Blockley and K. Andrew Peterson
The Cryosphere, 12, 3419–3438, https://doi.org/10.5194/tc-12-3419-2018, https://doi.org/10.5194/tc-12-3419-2018, 2018
Short summary
Short summary
Arctic sea-ice prediction on seasonal time scales is becoming increasingly more relevant to society but the predictive capability of forecasting systems is low. Several studies suggest initialization of sea-ice thickness (SIT) could improve the skill of seasonal prediction systems. Here for the first time we test the impact of SIT initialization in the Met Office's GloSea coupled prediction system using CryoSat-2 data. We show significant improvements to Arctic extent and ice edge location.
Jeff K. Ridley and Edward W. Blockley
The Cryosphere, 12, 3355–3360, https://doi.org/10.5194/tc-12-3355-2018, https://doi.org/10.5194/tc-12-3355-2018, 2018
Short summary
Short summary
The climate change conference held in Paris in 2016 made a commitment to limiting global-mean warming since the pre-industrial era to well below 2 °C and to pursue efforts to limit the warming to 1.5 °C. Since global warming is already at 1 °C, the 1.5 °C can only be achieved at considerable cost. It is thus important to assess the risks associated with the higher target. This paper shows that the decline of Arctic sea ice, and associated impacts, can only be halted with the 1.5 °C target.
Aleksey Malinka, Eleonora Zege, Larysa Istomina, Georg Heygster, Gunnar Spreen, Donald Perovich, and Chris Polashenski
The Cryosphere, 12, 1921–1937, https://doi.org/10.5194/tc-12-1921-2018, https://doi.org/10.5194/tc-12-1921-2018, 2018
Short summary
Short summary
Melt ponds occupy a large part of the Arctic sea ice in summer and strongly affect the radiative budget of the atmosphere–ice–ocean system. The melt pond reflectance is modeled in the framework of the radiative transfer theory and validated with field observations. It improves understanding of melting sea ice and enables better parameterization of the surface in Arctic atmospheric remote sensing (clouds, aerosols, trace gases) and re-evaluating Arctic climatic feedbacks at a new accuracy level.
Peng Lu, Matti Leppäranta, Bin Cheng, Zhijun Li, Larysa Istomina, and Georg Heygster
The Cryosphere, 12, 1331–1345, https://doi.org/10.5194/tc-12-1331-2018, https://doi.org/10.5194/tc-12-1331-2018, 2018
Short summary
Short summary
It is the first time that the color of melt ponds on Arctic sea ice was quantitatively and thoroughly investigated. We answer the question of why the color of melt ponds can change and what the physical and optical reasons are that lead to such changes. More importantly, melt-pond color was provided as potential data in determining ice thickness, especially under the summer conditions when other methods such as remote sensing are unavailable.
Lu Zhou, Shiming Xu, Jiping Liu, and Bin Wang
The Cryosphere, 12, 993–1012, https://doi.org/10.5194/tc-12-993-2018, https://doi.org/10.5194/tc-12-993-2018, 2018
Short summary
Short summary
This work proposes a new data synergy method for the retrieval of sea ice thickness and snow depth by using colocating L-band passive remote sensing and active laser altimetry. Physical models are adopted for the retrieval, including L-band radiation model and buoyancy relationship. Covariability of snow depth and total freeboard is further utilized to mitigate resolution differences and improve retrievability. The method can be applied to future campaigns including ICESat-2 and WCOM.
Ross M. Lieblappen, Deip D. Kumar, Scott D. Pauls, and Rachel W. Obbard
The Cryosphere, 12, 1013–1026, https://doi.org/10.5194/tc-12-1013-2018, https://doi.org/10.5194/tc-12-1013-2018, 2018
Short summary
Short summary
We imaged first-year sea ice using micro-computed tomography to visualize, capture, and quantify the 3-D complex structure of salt water channels weaving through sea ice. From these data, we then built a mathematical network to better understand the pathways transporting heat, gases, and salts between the ocean and the atmosphere. Powered with this structural knowledge, we can create new modeled brine channels for a given sea ice depth and temperature that accurately mimic field conditions.
Matthias Rabatel, Pierre Rampal, Alberto Carrassi, Laurent Bertino, and Christopher K. R. T. Jones
The Cryosphere, 12, 935–953, https://doi.org/10.5194/tc-12-935-2018, https://doi.org/10.5194/tc-12-935-2018, 2018
Short summary
Short summary
Large deviations still exist between sea ice forecasts and observations because of both missing physics in models and uncertainties on model inputs. We investigate how the new sea ice model neXtSIM is sensitive to uncertainties in the winds. We highlight and quantify the role of the internal forces in the ice on this sensitivity and show that neXtSIM is better at predicting sea ice drift than a free-drift (without internal forces) ice model and is a skilful tool for search and rescue operations.
Friedrich Richter, Matthias Drusch, Lars Kaleschke, Nina Maaß, Xiangshan Tian-Kunze, and Susanne Mecklenburg
The Cryosphere, 12, 921–933, https://doi.org/10.5194/tc-12-921-2018, https://doi.org/10.5194/tc-12-921-2018, 2018
Short summary
Short summary
L-band (1.4 GHz) brightness temperatures from ESA's Soil Moisture and Ocean Salinity SMOS mission have been used to derive thin sea ice thickness. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems reducing the data latency and providing a more consistent first guess. We studied the forward (observation) operator that translates geophysical sea ice parameters from the ECMWF Ocean ReAnalysis Pilot 5 (ORAP5) into brightness temperatures.
Jun Ono, Hiroaki Tatebe, Yoshiki Komuro, Masato I. Nodzu, and Masayoshi Ishii
The Cryosphere, 12, 675–683, https://doi.org/10.5194/tc-12-675-2018, https://doi.org/10.5194/tc-12-675-2018, 2018
Short summary
Short summary
Sea ice in the Arctic Ocean has experienced rapid decline since the beginning of satellite observations. To assess the predictability of sea ice extent (SIE) in the Arctic Ocean and to clarify the underlying physical processes, we conducted prediction experiments using an initialized climate model (MIROC5). The present study suggests that subsurface ocean heat content originating from the North Atlantic contributes to the skillful prediction of winter SIE at lead times up to 11 months.
Agnieszka Herman, Karl-Ulrich Evers, and Nils Reimer
The Cryosphere, 12, 685–699, https://doi.org/10.5194/tc-12-685-2018, https://doi.org/10.5194/tc-12-685-2018, 2018
Short summary
Short summary
In regions close to the ice edge, sea ice is composed of many separate ice floes of different sizes and shapes. Strong fragmentation is caused mainly by ice breaking by waves coming from the open ocean. At present, this process, although recognized as important for many other physical processes, is not well understood. In this study we present results of a laboratory study of ice breaking by waves, and we provide interpretation of those results that may guide analysis of other similar datasets.
Alek A. Petty, Julienne C. Stroeve, Paul R. Holland, Linette N. Boisvert, Angela C. Bliss, Noriaki Kimura, and Walter N. Meier
The Cryosphere, 12, 433–452, https://doi.org/10.5194/tc-12-433-2018, https://doi.org/10.5194/tc-12-433-2018, 2018
Short summary
Short summary
There was significant scientific and media attention surrounding Arctic sea ice in 2016, due primarily to the record-warm air temperatures and low sea ice conditions observed at the start of the year. Here we quantify and assess the record-low monthly sea ice cover in winter, spring and fall, and the lack of record-low sea ice conditions in summer. We explore the primary drivers of these monthly sea ice states and explore the implications for improved summer sea ice forecasting.
Lettie A. Roach, Samuel M. Dean, and James A. Renwick
The Cryosphere, 12, 365–383, https://doi.org/10.5194/tc-12-365-2018, https://doi.org/10.5194/tc-12-365-2018, 2018
Short summary
Short summary
This paper evaluates Antarctic sea ice simulated by global climate models against satellite observations. We find biases in high-concentration and low-concentration sea ice that are consistent across the population of 40 models, in spite of the differences in physics between different models. Targeted model experiments show that biases in low-concentration sea ice can be significantly reduced by enhanced lateral melt, a result that may be valuable for sea ice model development.
David W. Rees Jones and Andrew J. Wells
The Cryosphere, 12, 25–38, https://doi.org/10.5194/tc-12-25-2018, https://doi.org/10.5194/tc-12-25-2018, 2018
Short summary
Short summary
Frazil or granular ice grows rapidly from turbulent water cooled beneath its freezing temperature. We analyse numerical models of a population of ice crystals to provide insight into the treatment of frazil ice in large-scale models and hence in the environment. We determine critical conditions for explosively rapid frazil growth. We show that frazil-ice processes impact whether a plume of ice shelf water beneath an Antarctic ice shelf intrudes at depth or reaches the end of the shelf.
Jamie G. L. Rae, Alexander D. Todd, Edward W. Blockley, and Jeff K. Ridley
The Cryosphere, 11, 3023–3034, https://doi.org/10.5194/tc-11-3023-2017, https://doi.org/10.5194/tc-11-3023-2017, 2017
Short summary
Short summary
Several studies have highlighted links between Arctic summer storms and September sea ice extent in observations. Here we use model and reanalysis data to investigate the sensitivity of such links to the analytical methods used, in order to determine their robustness. The links were found to depend on the resolution of the model and dataset, the method used to identify storms and the time period used in the analysis. We therefore recommend caution when interpreting the results of such studies.
Amelia A. Marks, Maxim L. Lamare, and Martin D. King
The Cryosphere, 11, 2867–2881, https://doi.org/10.5194/tc-11-2867-2017, https://doi.org/10.5194/tc-11-2867-2017, 2017
Short summary
Short summary
Arctic sea ice extent is declining rapidly. Prediction of sea ice trends relies on sea ice models that need to be evaluated with real data. A realistic sea ice environment is created in a laboratory by the Royal Holloway sea ice simulator and is used to show a sea ice model can replicate measured properties of sea ice, e.g. reflectance. Black carbon, a component of soot found in atmospheric pollution, is also experimentally shown to reduce the sea ice reflectance, which could exacerbate melting.
David Docquier, François Massonnet, Antoine Barthélemy, Neil F. Tandon, Olivier Lecomte, and Thierry Fichefet
The Cryosphere, 11, 2829–2846, https://doi.org/10.5194/tc-11-2829-2017, https://doi.org/10.5194/tc-11-2829-2017, 2017
Short summary
Short summary
Our study provides a new way to evaluate the performance of a climate model regarding the interplay between sea ice motion, area and thickness in the Arctic against different observation datasets. We show that the NEMO-LIM model is good in that respect and that the relationships between the different sea ice variables are complex. The metrics we developed can be used in the framework of the Coupled Model Intercomparison Project 6 (CMIP6), which will feed the next IPCC report.
Agnieszka Herman
The Cryosphere, 11, 2711–2725, https://doi.org/10.5194/tc-11-2711-2017, https://doi.org/10.5194/tc-11-2711-2017, 2017
Short summary
Short summary
It is often assumed that ocean waves break sea ice into floes with sizes depending on wavelength. The results of this modeling study (in agreement with some earlier observations and models) suggest that this is not the case; instead the sizes of ice floes produced by wave breaking depend only on ice thickness and mechanical properties. This may have important consequences for predicting sea ice response to oceanic and atmospheric forcing in regions where sea ice is influenced by waves.
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
Short summary
Short summary
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.
Polona Itkin and Thomas Krumpen
The Cryosphere, 11, 2383–2391, https://doi.org/10.5194/tc-11-2383-2017, https://doi.org/10.5194/tc-11-2383-2017, 2017
Short summary
Short summary
By means of airborne sea ice thickness surveys, remote sensing data and results from a numerical model, we show that winter ice dynamic in the Laptev Sea has a preconditioning effect on local summer ice extent in addition to atmospheric processes acting on the ice cover between May and September. We conclude that the observed tendency towards an increased ice export further accelerates pack ice retreat in summer and fast ice decay.
Nikolay V. Koldunov, Armin Köhl, Nuno Serra, and Detlef Stammer
The Cryosphere, 11, 2265–2281, https://doi.org/10.5194/tc-11-2265-2017, https://doi.org/10.5194/tc-11-2265-2017, 2017
Short summary
Short summary
The paper describes one of the first attempts to use the so-called adjoint data assimilation method to bring Arctic Ocean model simulations closer to observation, especially in terms of the sea ice. It is shown that after assimilation the model bias in simulating the Arctic sea ice is considerably reduced. There is also additional improvement in the sea ice thickens representation that is not assimilated directly.
Torbjørn Taskjelle, Stephen R. Hudson, Mats A. Granskog, and Børge Hamre
The Cryosphere, 11, 2137–2148, https://doi.org/10.5194/tc-11-2137-2017, https://doi.org/10.5194/tc-11-2137-2017, 2017
Christian Katlein, Stefan Hendricks, and Jeffrey Key
The Cryosphere, 11, 2111–2116, https://doi.org/10.5194/tc-11-2111-2017, https://doi.org/10.5194/tc-11-2111-2017, 2017
Short summary
Short summary
In the public debate, increasing sea ice extent in the Antarctic is often highlighted as counter-indicative of global warming. Here we show that the slight increases in Antarctic sea ice extent are not able to counter Arctic losses. Using bipolar satellite observations, we demonstrate that even in the Antarctic polar ocean solar shortwave energy absorption is increasing in accordance with strongly increasing shortwave energy absorption in the Arctic Ocean rather than compensating Arctic losses.
Timothy D. Williams, Pierre Rampal, and Sylvain Bouillon
The Cryosphere, 11, 2117–2135, https://doi.org/10.5194/tc-11-2117-2017, https://doi.org/10.5194/tc-11-2117-2017, 2017
Short summary
Short summary
As the Arctic sea ice extent drops, more ship traffic seeks to take advantage of this, and a need for better wave and sea ice forecasts arises. One aspect of this is the location of the sea ice edge. The waves here can be quite large, but they die away as they travel into the ice. This causes momentum to be transferred from the waves to the ice, causing ice drift. However, our study found that the effect of the wind drag had more impact on the ice edge position than the waves.
Véronique Dansereau, Jérôme Weiss, Pierre Saramito, Philippe Lattes, and Edmond Coche
The Cryosphere, 11, 2033–2058, https://doi.org/10.5194/tc-11-2033-2017, https://doi.org/10.5194/tc-11-2033-2017, 2017
Short summary
Short summary
A new mechanical framework is used to model the drift of sea ice in a narrow channel between Greenland and Ellesmere Island. It is able to reproduce its main features : curved cracks, ice “bridges” that stop the flow of ice for several months of the year and some thick, strongly localized ridged ice. The simulations suggest that a mechanical weakening of the sea ice cover can shorten the lifespan of ice bridges and result in an increased export of ice through the narrow channels of the Arctic.
Kevin Guerreiro, Sara Fleury, Elena Zakharova, Alexei Kouraev, Frédérique Rémy, and Philippe Maisongrande
The Cryosphere, 11, 2059–2073, https://doi.org/10.5194/tc-11-2059-2017, https://doi.org/10.5194/tc-11-2059-2017, 2017
Short summary
Short summary
We analyse CryoSat-2 and Envisat freeboard height discrepancy over Arctic sea ice and we study the potential role of ice roughness.
Based on our results, we build a CryoSat-2-like version of Envisat freeboard height. The improved Envisat freeboard is converted to sea ice draught and compared to in situ mooring observations to demonstrate the potential of our methodology to produce accurate ice thickness estimates over the 2002–2012 period.
Stefan Muckenhuber and Stein Sandven
The Cryosphere, 11, 1835–1850, https://doi.org/10.5194/tc-11-1835-2017, https://doi.org/10.5194/tc-11-1835-2017, 2017
Short summary
Short summary
Sea ice drift has a strong impact on sea ice distribution on different temporal and spatial scales. An open-source sea ice drift algorithm for Sentinel-1 satellite imagery is introduced based on the combination of feature tracking and pattern matching. The algorithm is designed to utilise the respective advantages of the two approaches and allows drift calculation at user-defined locations.
Jennifer V. Lukovich, Cathleen A. Geiger, and David G. Barber
The Cryosphere, 11, 1707–1731, https://doi.org/10.5194/tc-11-1707-2017, https://doi.org/10.5194/tc-11-1707-2017, 2017
Short summary
Short summary
In this study we develop a framework to characterize directional changes in sea ice drift and associated deformation in response to atmospheric forcing. Lagrangian dispersion statistics applied to ice beacons deployed in a triangular configuration in the Beaufort Sea capture a shift in ice dynamical regimes and local differences in deformation. This framework contributes to diagnostic development relevant for ice hazard assessments and forecasting required by indigenous communities and industry.
Robert Ricker, Stefan Hendricks, Lars Kaleschke, Xiangshan Tian-Kunze, Jennifer King, and Christian Haas
The Cryosphere, 11, 1607–1623, https://doi.org/10.5194/tc-11-1607-2017, https://doi.org/10.5194/tc-11-1607-2017, 2017
Short summary
Short summary
We developed the first merging of CryoSat-2 and SMOS sea-ice thickness retrievals. ESA’s Earth Explorer SMOS satellite can detect thin sea ice, whereas its companion CryoSat-2, designed to observe thicker perennial sea ice, lacks sensitivity. Using these satellite missions together completes the picture of the changing Arctic sea ice and provides a more accurate and comprehensive view on the actual state of Arctic sea-ice thickness.
Gunnar Spreen, Ron Kwok, Dimitris Menemenlis, and An T. Nguyen
The Cryosphere, 11, 1553–1573, https://doi.org/10.5194/tc-11-1553-2017, https://doi.org/10.5194/tc-11-1553-2017, 2017
Verena Haid, Doroteaciro Iovino, and Simona Masina
The Cryosphere, 11, 1387–1402, https://doi.org/10.5194/tc-11-1387-2017, https://doi.org/10.5194/tc-11-1387-2017, 2017
Short summary
Short summary
Since the Antarctic sea ice extent shows a recent increase, we investigate the sea ice response to changed amount and distribution of surface freshwater addition in the Southern Ocean with the ocean–sea ice model NEMO/LIM2. We find that freshwater addition within the range of current estimates increases the ice extent, but higher amounts could have an opposing effect. The freshwater distribution is of great influence on the ice dynamics and the ice thickness is strongly influenced by it.
Predrag Popović and Dorian Abbot
The Cryosphere, 11, 1149–1172, https://doi.org/10.5194/tc-11-1149-2017, https://doi.org/10.5194/tc-11-1149-2017, 2017
Short summary
Short summary
During summer, a large portion of sea ice in the Arctic is typically covered with meltwater. We present a simple model for the evolution of melt ponds on permeable sea ice that both fits observations and allows us to understand the behavior of melt ponds in a way that is often not possible with more complex models. We use this model to show that pond coverage will increase under global warming. This work is important as melt ponds affect the overall reflectance of sea ice.
Luke G. Bennetts, Siobhan O'Farrell, and Petteri Uotila
The Cryosphere, 11, 1035–1040, https://doi.org/10.5194/tc-11-1035-2017, https://doi.org/10.5194/tc-11-1035-2017, 2017
Short summary
Short summary
A numerical model is used to investigate how Antarctic sea ice concentration and volume are affected by increased melting caused by ocean-wave breakup of the ice. When temperatures are high enough to melt the ice, concentration and volume are reduced for ~ 100 km into the ice-covered ocean. When temperatures are low enough for ice growth, the concentration recovers, but the reduced volume persists.
Serena Schroeter, Will Hobbs, and Nathaniel L. Bindoff
The Cryosphere, 11, 789–803, https://doi.org/10.5194/tc-11-789-2017, https://doi.org/10.5194/tc-11-789-2017, 2017
Short summary
Short summary
Observed trends of Antarctic sea ice are not reproduced by global climate models. We examine observed and simulated interactions between sea ice and large-scale atmospheric variability, showing that global climate models generally capture observed interactions during the season of sea ice advance, but not during sea ice retreat. Most models overestimate the zonally symmetric influence of the dominant atmospheric mode on sea ice, while the importance of tropical variability is underestimated.
Lars H. Smedsrud, Mari H. Halvorsen, Julienne C. Stroeve, Rong Zhang, and Kjell Kloster
The Cryosphere, 11, 65–79, https://doi.org/10.5194/tc-11-65-2017, https://doi.org/10.5194/tc-11-65-2017, 2017
Short summary
Short summary
Export of Arctic sea ice area southwards through the Fram Strait from 1935 to 2014 is calculated based on satellite radar images and surface pressure observations. The annual mean export is 880 000 km2, representing 10 % of the Arctic sea ice area. In recent years the export has been above 1 million km2, and there are positive trends over the last 30 years. Increased ice export during spring and summer contributes to more open water in September, and this correlations has increased over time.
Natalia Zakhvatkina, Anton Korosov, Stefan Muckenhuber, Stein Sandven, and Mohamed Babiker
The Cryosphere, 11, 33–46, https://doi.org/10.5194/tc-11-33-2017, https://doi.org/10.5194/tc-11-33-2017, 2017
Short summary
Short summary
The presented fully automated algorithm distinguishes open water (rough/calm) and sea ice based on dual-polarized RS2 SAR images. Texture features are used for Support Vector Machines supervised image classification. The algorithm includes pre-processing and validation procedures. More than 2700 scenes were processed and the results show the good discrimination between open water and sea ice areas with accuracy 91 % compared with ice charts produced by MET Norway service.
Cited articles
Boe, J., Hall, A., and Qu, X.: September sea-ice cover in the Arctic ocean projected to vanish by 2100, Nat. Geosci., 2, 341–343, https://doi.org/10.1038/ngeo467, 2009.
Brodzik, M. J. and Knowles, K.: EASE-Grid: a versatile set of equal-area projections and grids, in: Discrete Global Grids, edited by: Goodchild, M. and Kimerling, A. J., Santa Barbara, CA, USA, 2002.
Brodzik, M. J., Billingsley, B., Haran, T., Raup, B., and Savoie, M. H.: EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets, ISPRS Int. J. Geo-Inf., 1, 32–45, https://doi.org/10.3390/ijgi1010032, 2012.
Day, J. J., Hargreaves, J. C., Annan, J. D., and Abe-Ouchi, A.: Sources of multi-decadal variability in Arctic sea ice extent, Environ. Res. Lett., 7, 034011, https://doi.org/10.1088/1748-9326/7/3/034011, 2012.
Fetterer, F., Knowles, K., Meier, W., and Savoie, M.: updated daily, Sea Ice Index, Boulder, Colorado USA: National Snow and Ice Data Center, Digital media, 2002.
Haas, C., Lobach, J., Hendricks, S., Rabenstein, L., and Pfaffling, A.: Helicopter-borne measurements of sea ice thickness, using a small and lightweight, digital EM system, J. Appl. Geophys., 67, 234–241, 2009.
Holland, M. M. and Stroeve, J. C.: Changing seasonal sea ice predictor relationships in a changing Arctic climate, Geophys. Res. Lett., 38, L18501, https://doi.org/10.1029/2011GL049303, 2011.
Holland, M. M., Serreze, M. C., and Stroeve, J.: The sea ice mass budget of the Arctic and its future change as simulated by coupled climate models, Clim. Dynam., 34, 185–200, https://doi.org/10.1007/s00382-008-0493-4, 2010.
Kwok, R.: Observational assessments of Arctic Ocean sea ice motion, export, and thickness in CMIP3 climate simulations, J. Geophys. Res., 116, C00D05, https://doi.org/10.1029/2011JC007004, 2011.
Kwok, R. and Rothrock, D. A.: Decline in Arctic sea ice thickness from submarine and ICESat records: 1958–2008, Geophys. Res. Lett., 36, L15501, https://doi.org/10.1029/2009GL039035, 2009.
Kwok, R., Cunningham, G. F., Wensnahan, M., Rigor, I., Zwally, H. J., and Yi, D.: Thinning and volume loss of Arctic sea ice: 2003–2008, J. Geophys. Res., 114, C07005, https://doi.org/10.1029/2009JC005312, 2009.
Kurtz, N., Studinger, M., Harbeck, J., Onana, V., and Farrell, S.: IceBridge Sea Ice Freeboard, Snow Depth, and Thickness, Version 1. Boulder, Colorado USA: NASA DAAC at the National Snow and Ice Data Center, 2012.
Kurtz, N. T., Farrell, S. L., Studinger, M., Galin, N., Harbeck, J. P., Lindsay, R., Onana, V. D., Panzer, B., and Sonntag, J. G.: Sea ice thickness, freeboard, and snow depth products from Operation IceBridge airborne data, The Cryosphere, 7, 1035–1056, https://doi.org/10.5194/tc-7-1035-2013, 2013.
Kurtz, N. T., Galin, N., and Studinger, M.: An improved CryoSat-2 sea ice freeboard retrieval algorithm through the use of waveform fitting, The Cryosphere, 8, 1217–1237, https://doi.org/10.5194/tc-8-1217-2014, 2014.
Laxon, S., Peacock, N., and Smith, D.: High interannual variability of sea ice thickness in the Arctic region, Nature, 425, 947–950, https://doi.org/10.1038/nature02050, 2003.
Laxon, S. W., Giles, K. A., Ridout, A. L., Wingham, D. J., Willatt, R., Cullen, R., Kwok, R., Schweiger, A., Zhang, J., Haas, C., Hendricks, S., Krishfield, R., Kurtz, N., Farrell, S., and Davidson, M.: CryoSat estimates of Arctic sea ice thickness and volume, Geophys. Res. Lett., 40, 732–737, https://doi.org/10.1002/grl.50193, 2013.
Lindsay, R. W.: Unified Sea Ice Thickness Climate Data Record, Polar Science Center, Applied Physics Laboratory, University of Washington, Washington, psc.apl.washington.edu/sea_ice_cdr (last access: 1 November 2013), digital media, 2010.
Lindsay, R., Haas, C., Hendricks, S., Hunkeler, P., Kurtz, N., Paden, J., Panzer, B., Sonntag, J., Yungel, J., and Zhang, J.: Seasonal forecasts of Arctic sea ice initialized with observations of ice thickness, Geophys. Res. Lett., 39, L21502, https://doi.org/10.1029/2012GL053576, 2012.
Lindsay, R.: Unified Sea Ice Thickness Climate Data Record Collection Spanning 1947–2012, Boulder, Colorado USA: National Snow and Ice Data Center, https://doi.org/10.7265/N5D50JXV, 2013.
Massonnet, F., Fichefet, T., Goosse, H., Bitz, C. M., Philippon-Berthier, G., Holland, M. M., and Barriat, P.-Y.: Constraining projections of summer Arctic sea ice, The Cryosphere, 6, 1383–1394, https://doi.org/10.5194/tc-6-1383-2012, 2012.
Melling, H. and Riedel, D. A.: Ice Draft and Ice Velocity Data in the Beaufort Sea, 1990–2003. Boulder, Colorado USA: National Snow and Ice Data Center, Digital media, 2008.
Notz, D. and Marotzke, J.: Observations reveal external driver for Arctic sea-ice retreat, Geophys. Res. Lett., 39, L08502, https://doi.org/10.1029/2012GL051094, 2012.
Rothrock, D. A. and Wensnahan, M.: The Accuracy of Sea-Ice Drafts Measured from U.S. Navy Submarines, J. Atmos. Ocean. Tech., 24, 1936–1949, https://doi.org/10.1175/JTECH2097.1, 2007.
Santer, B. D., Thorne, P. W., Haimberger, L., Taylor, K. E., Wigley, T. M. L., Lanzante, J. R., Solomon, S., Free, M., Gleckler, P. J., Jones, P. D., Karl, T. R., Klein, S. A., Mears, C., Nychka, D., Schmidt, G. A., Sherwood, S. C., and Wentz, F. J.: Consistency of modeled and observed temperature trends in the tropical troposphere, Int. J. Climatol., 28, 1703–1722, https://doi.org/10.1002/joc.1756, 2008.
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.
Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N., and Holland, M. M.: The emergence of surface-based Arctic amplification, The Cryosphere, 3, 11–19, https://doi.org/10.5194/tc-3-11-2009, 2009.
Stroeve, J., Holland, M. M., Meier, W., Scambos, T., and Serreze, M.: Arctic sea ice decline: Faster than Forecast, Geophys. Res. Lett., 34, L09501, https://doi.org/10.1029/2007GL029703, 2007.
Stroeve, J. C., Kattsov, V., Barrett, A., Serreze, M., Pavlova, T., Holland, M., and Meier, W. N.: Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations, Geophys. Res. Lett., 39, L16502, https://doi.org/10.1029/2012GL052676, 2012a.
Stroeve, J. C., Serreze, M. C., Kay, J. E., Holland, M. M., Meier, W. N., and Barrett, A. P.: The Arctic's rapidly shrinking sea ice cover: A research synthesis, Climatic Change, 110, 1005–1027, https://doi.org/10.1007/s10584-011-0101-1, 2012b.
Stroeve, J. C., Hamilton, L., Bitz, C., and Blanchard-Wigglesworth, E.: Predicting September sea ice: Ensemble skill of the SEARCH sea ice outlook 2008–2013, Geophys. Res. Lett., 41, 2411–2418, https://doi.org/10.1002/2014GL059388, 2014.
Thompson, A. M., Calvin, K. V., Smith, S. J., Kyle, G. P., Volke, A., Patel, P., Delgado-Arias, S., Bond-Lamberty, B., Wise, M. A., Clark, L. E., and Edmonds, J. A.: RCP4.5: a pathway for stabilization of radiative forcing by 2100, Climatic Change, 109, 77–94, https://doi.org/10.1007/s10584-011-0151-4, 2011.
Wang, M. and Overland, J. E.: A sea ice free summer Arctic within 30 years?, Geophys. Res. Lett., 36, L07502, https://doi.org/10.1029/2009GL037820, 2009.
Wang, M. and Overland, J. E.: A sea ice free summer Arctic within 30 years – an update from CMIP5 models, Geophys. Res. Lett., 39, L18501, https://doi.org/10.1029/2012GL052868, 2012.
Warren, S, Rigor, I. G., and Untersteiner, N.: Snow depth on Arctic sea ice, J. Climate, 12, 1814–1829, 1998.
Zhang, J. L. and Rothrock, D. A.: Modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates, Mon. Weather Rev., 131, 845–861, 2003.
Zygmuntowska, M., Rampal, P., Ivanova, N., and Smedsrud, L. H.: Uncertainties in Arctic sea ice thickness and volume: new estimates and implications for trends, The Cryosphere, 8, 705–720, https://doi.org/10.5194/tc-8-705-2014, 2014
Search articles
Download
Notice on corrigendum
The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.
-
Article
(8453 KB)
The Cryosphere
An interactive open-access journal of the European Geosciences Union
All site content, except where otherwise noted, is licensed under the Creative Commons Attribution 4.0 License.