Articles | Volume 12, issue 10
https://doi.org/10.5194/tc-12-3373-2018
© Author(s) 2018. 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-12-3373-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Oct 2018
Research article |
| 26 Oct 2018
| 26 Oct 2018
Arctic climate: changes in sea ice extent outweigh changes in snow cover
Aaron Letterly
CORRESPONDING AUTHOR
Cooperative Institute for Meteorological Satellite Studies, University
of Wisconsin, Madison, WI, USA
Jeffrey Key
National Oceanic and Atmospheric Administration, Madison, WI, USA
Yinghui Liu
Cooperative Institute for Meteorological Satellite Studies, University
of Wisconsin, Madison, WI, USA
Related authors
No articles found.
James Anheuser, Yinghui Liu, and Jeffrey R. Key
The Cryosphere, 17, 2871–2889, https://doi.org/10.5194/tc-17-2871-2023, https://doi.org/10.5194/tc-17-2871-2023, 2023
Short summary
Short summary
Sea ice parcels may experience thickness changes primarily through two processes: due to freezing or melting or due to motion relative to other parcels. These processes are independent and will be affected differently in a changing climate. In order to better understand these processes and compare them against models, observational estimates of these process independent from one another are necessary. We present a large spatial- and temporal-scale observational estimate of these processes.
James Anheuser, Yinghui Liu, and Jeffrey R. Key
The Cryosphere, 16, 4403–4421, https://doi.org/10.5194/tc-16-4403-2022, https://doi.org/10.5194/tc-16-4403-2022, 2022
Short summary
Short summary
A prominent part of the polar climate system is sea ice, a better understanding of which would lead to better understanding Earth's climate. Newly published methods for observing the temperature of sea ice have made possible a new method for estimating daily sea ice thickness growth from space using an energy balance. The method compares well with existing sea ice thickness observations.
Yinghui Liu
Atmos. Chem. Phys., 22, 8151–8173, https://doi.org/10.5194/acp-22-8151-2022, https://doi.org/10.5194/acp-22-8151-2022, 2022
Short summary
Short summary
Cloud detection from state-of-art satellite radar and lidar misses low-level clouds. Using in situ observations, this study confirms this cloud detection limitation over the Arctic Ocean. Impacts of this detection limitation from combined satellite radar and lidar on the monthly mean radiation flux estimations at the surface and at the top of the atmosphere in the Arctic are limited but larger from only satellite radar or satellite lidar in monthly mean and instantaneous values.
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
Short summary
Short summary
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.
Jui-Lin Frank Li, Mark Richardson, Wei-Liang Lee, Eric Fetzer, Graeme Stephens, Jonathan Jiang, Yulan Hong, Yi-Hui Wang, Jia-Yuh Yu, and Yinghui Liu
The Cryosphere, 13, 969–980, https://doi.org/10.5194/tc-13-969-2019, https://doi.org/10.5194/tc-13-969-2019, 2019
Short summary
Short summary
Observed summer Arctic sea ice retreat has been faster than simulated by the average CMIP5 models, most of which exclude falling ice particles from their radiative calculations.
We use controlled CESM1-CAM5 simulations to show for the first time that snowflakes' radiative effects can accelerate sea ice retreat. September retreat rates are doubled above current CO2 levels, highlighting falling ice radiative effects as a high priority for inclusion in future modelling of the Arctic.
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.
Yinghui Liu, Matthew D. Shupe, Zhien Wang, and Gerald Mace
Atmos. Chem. Phys., 17, 5973–5989, https://doi.org/10.5194/acp-17-5973-2017, https://doi.org/10.5194/acp-17-5973-2017, 2017
Short summary
Short summary
Detailed and accurate vertical distributions of cloud properties are essential to accurately calculate the surface radiative flux and to depict the mean climate state, and such information is more desirable in the Arctic due to its recent rapid changes and the challenging observation conditions. This study presents a feasible way to provide such information by blending cloud observations from surface and space-based instruments with the understanding of their respective strength and limitations.
Related subject area
Discipline: Sea ice | Subject: Arctic (e.g. Greenland)
Sea-ice conditions from 1880 to 2017 on the Northeast Greenland continental shelf: a biomarker and observational record comparison
The radiative and geometric properties of melting first-year landfast sea ice in the Arctic
Improving short-term sea ice concentration forecasts using deep learning
Retrieval of sea ice drift in the Fram Strait based on data from Chinese satellite HaiYang (HY-1D)
Sea-ice variations and trends during the Common Era in the Atlantic sector of the Arctic Ocean
Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model
Extent, duration and timing of the sea ice cover in Hornsund, Svalbard, from 2014–2023
GREP reanalysis captures the evolution of the Arctic Marginal Ice Zone across timescales
Modeled variations in the inherent optical properties of summer Arctic ice and their effects on the radiation budget: a case based on ice cores from 2008 to 2016
Comparing elevation and backscatter retrievals from CryoSat-2 and ICESat-2 over Arctic summer sea ice
Summer sea ice floe perimeter density in the Arctic: high-resolution optical satellite imagery and model evaluation
Patterns of wintertime Arctic sea-ice leads and their relation to winds and ocean currents
A long-term proxy for sea ice thickness in the Canadian Arctic: 1996–2020
Arctic sea ice radar freeboard retrieval from the European Remote-Sensing Satellite (ERS-2) using altimetry: toward sea ice thickness observation from 1995 to 2021
Rapid sea ice changes in the future Barents Sea
Causes and evolution of winter polynyas north of Greenland
Winter Arctic sea ice thickness from ICESat-2: upgrades to freeboard and snow loading estimates and an assessment of the first three winters of data collection
Sea ice breakup and freeze-up indicators for users of the Arctic coastal environment
Improving model-satellite comparisons of sea ice melt onset with a satellite simulator
Kara and Barents sea ice thickness estimation based on CryoSat-2 radar altimeter and Sentinel-1 dual-polarized synthetic aperture radar
Contribution of warm and moist atmospheric flow to a record minimum July sea ice extent of the Arctic in 2020
Perspectives on future sea ice and navigability in the Arctic
Lasting impact of winds on Arctic sea ice through the ocean's memory
Holocene sea-ice dynamics in Petermann Fjord in relation to ice tongue stability and Nares Strait ice arch formation
Presentation and evaluation of the Arctic sea ice forecasting system neXtSIM-F
Combined influence of oceanic and atmospheric circulations on Greenland sea ice concentration
Seasonal changes in sea ice kinematics and deformation in the Pacific sector of the Arctic Ocean in 2018/19
Year-round impact of winter sea ice thickness observations on seasonal forecasts
Ensemble-based estimation of sea-ice volume variations in the Baffin Bay
Sea ice drift and arch evolution in the Robeson Channel using the daily coverage of Sentinel-1 SAR data for the 2016–2017 freezing season
Brief communication: Arctic sea ice thickness internal variability and its changes under historical and anthropogenic forcing
Seasonal transition dates can reveal biases in Arctic sea ice simulations
The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) high-priority candidate mission
The MOSAiC ice floe: sediment-laden survivor from the Siberian shelf
Spectral attenuation of ocean waves in pack ice and its application in calibrating viscoelastic wave-in-ice models
New observations of the distribution, morphology and dissolution dynamics of cryogenic gypsum in the Arctic Ocean
Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM
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 Mission Benefit Analysis: impact of sea ice thickness, freeboard, and snow depth products on sea ice forecast performance
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Francesco Cocetta, Lorenzo Zampieri, Julia Selivanova, and Doroteaciro Iovino
EGUsphere, https://doi.org/10.5194/egusphere-2024-413, https://doi.org/10.5194/egusphere-2024-413, 2024
Short summary
Short summary
Arctic sea ice 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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Isolde A. Glissenaar, Jack C. Landy, David G. Babb, Geoffrey J. Dawson, and Stephen E. L. Howell
The Cryosphere, 17, 3269–3289, https://doi.org/10.5194/tc-17-3269-2023, https://doi.org/10.5194/tc-17-3269-2023, 2023
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
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
Short summary
Short summary
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
Cess, R. D. and Potter, G. L.: A Methodology for Understanding and
Intercomparing Atmospheric Climate Feedback Processes in General Circulation
Models, J. Geophys. Res., 93, 8305–8314, 1988.
Chapin, F. S., Sturm, M., Serreze, M. C., McFadden, J. P., Key, J. R., Lloyd,
A. H., McGuire, A. D., Rupp, T. S., Lynch, A. H., Schimel, J. P., Beringer,
J., Epstein, H. E., Hinzman, L. D., Jia, G., Ping, C. L., Tape, K., Chapman,
W. L., Euskirchen, E., Thompson, C. D. C., Welker, J. M., and Walker, D. A.:
Role of land surface changes in Arctic summer warming, Science, 310,
657–660, https://doi.org/10.1126/science.1117368, 2005.
Déry, S. J. and Brown, R. D.: Recent Northern Hemisphere snow cover
extent trends and implications for the snow-albedo feedback, Geophys. Res.
Lett., 34, L22504, https://doi.org/10.1029/2007GL031474, 2007.
Fernandes, R., Zhao, H., Wang, X., Key, J., Qu, X., and Hall, A.: Controls on
Northern Hemisphere snow albedo feedback quantified using satellite Earth
observations, Geophys. Res. Lett., 36, L21702, https://doi.org/10.1029/2009GL040057,
2009.
Flanner, M. M., Shell, K. M., Barlage, M., Perovich, D. K., and Tschudi, M.:
Radiative forcing and albedo feedback from the Northern Hemisphere cryosphere
between 1979 and 2008, Nat. Geosci., 4, 151–155, https://doi.org/10.1038/ngeo1062, 2011.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K.,
Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da
Silva, A. M., Gu, W., Kim, G., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert,
S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis
for Research and Applications, Version 2 (MERRA-2), J. Climate, 30,
5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Greenfell, T. C. and Perovich, D. K.: Seasonal and spatial evolution of
albedo in a snow-ice-land-ocean environment, Geophys. Res.-Oceans, 109,
C01001, https://doi.org/10.1029/2003JC001866, 2004.
Groisman, P. Y., Karl, T. R., and Knight, R. W.: Observed impact of snow
cover on the heat balance and the rise of continental spring temperatures,
Science, 263, 198–201, 1994.
Hernández-Henríquez, M. A., Déry, S. J., and Derksen, C.: Polar
amplification and elevation-dependence in trends of Northern Hemisphere snow
cover extent, 1971–2014, Environ. Res. Lett., 10, 044010,
https://doi.org/10.1088/1748-9326/10/4/044010, 2015.
Hori, M., Sugiura, K., Kobayashi, K., Aoki, T., Tanikawa, T., Kuchiki, K.,
Niwano, M., and Enomoto, H.: A 38-year (1978–2015) Northern Hemisphere daily
snow cover extent product derived using consistent objective criteria from
satellite-borne optical sensors, Remote Sens. Environ., 191, 402–418,
https://doi.org/10.1016/j.rse.2017.01.023, 2017.
Kashiwase, H., Ohshima, K. I., Nihashi, S., and Eicken, H.: Evidence for
ice-ocean albedo feedback in the Arctic Ocean shifting to a seasonal ice
zone, Sci. Rep., 7, 8170, https://doi.org/10.1038/s41598-017-08467-z, 2017.
Kato, S., Loeb, N. G., Minnis, P., Francis, J. A., Charlock, T. P., Rutan, D.
A., Clothiaux, E. E., and Sun-Mack, S.: Seasonal and interannual variations
of top-of-atmosphere irradiance and Cloud Cover over polar regions derived
from the CERES data set, Geophys. Res. Lett., 33, L19804,
https://doi.org/10.1029/2006GL026685, 2006.
Key, J. and Schweiger, A.: Tools for atmospheric radiative transfer: Streamer
and FluxNet, Comput. Geosci., 24, 443–451,
https://doi.org/10.1016/S0098-3004(97)00130-1, 1998.
Key, J. and Wang, X.: Climate Algorithm Theoretical Basis Document, Extended
AVHRR Polar Pathfinder (APP-x), CDRP-ATBD-0573, Revision 1.0, 2015.
Key, J., Wang, X., Stroeve, J., and Fowler, C.: Estimating the cloudy-sky
albedo of sea ice and snow from space, J. Geophys. Res., 106, 12489–12497,
2001.
Key, J., Wang, X., Liu, Y., and NOAA CDR Program: NOAA Climate Data Record of
AVHRR Polar Pathfinder Extended (APP-X), Version 1, NOAA National Centers for
Environmental Information, https://doi.org/10.7289/V5MK69W6, 2014.
Key, J., Liu, Y., Wang, X., and NOAA CDR Program: NOAA Climate Data Record
(CDR) of AVHRR Polar Pathfinder (APP) Cryosphere, Version 1.0. NOAA National
Centers for Environmental Information (NCEI), https://doi.org/10.7289/V5BC3WHM, 2015.
Key, J., Wang, X., Liu, Y., Dworak, R., and Letterly, A.: The AVHRR Polar
Pathfinder Climate Data Records, Remote Sens., 8, 167, https://doi.org/10.3390/rs8030167,
2016.
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.
Letterly, A., Key, J., and Liu, Y.: The influence of winter cloud on summer
sea ice in the Arctic, 1983–2013, J. Geophys. Res.-Atmos., 121, 2178–2187,
https://doi.org/10.1002/2015JD024316, 2016.
Lindsay, R. W.: Arctic sea-ice albedo derived from RGPS-based ice-thickness
estimates, Ann. Glaciol., 33, 225–229, https://doi.org/10.3189/172756401781818103, 2001.
Liu, Y. and Key, J.: Less Winter Cloud Aids Summer 2013 Arctic Sea Ice Return
from 2012 Minimum, Environ. Res. Lett., 9, 044002,
https://doi.org/10.1088/1748-9326/9/4/044002, 2014.
Liu, Y., Key, J. R., Liu Z., Wang, X., and Vavrus, S. J.: A cloudier Arctic
expected with diminishing sea ice, Geophys. Res. Lett., 39, L05705,
https://doi.org/10.1029/2012GL051251, 2012.
Loranty, M. M., Goetz, S. J., and Beck, P. S. A.: Tundra vegetation effects
on pan-Arctic albedo, Environ. Res. Lett., 6, 024014,
https://doi.org/10.1088/1748-9326/6/2/024014, 2011.
Markus, T., Stroeve, J., and Miller, J.: Recent changes in Arctic sea ice
melt onset, freezeup, and melt season length, J. Geophys. Res.-Oceans, 114,
C12024, https://doi.org/10.1029/2009JC005436, 2009.
Nghiem, S., Rigor, I., Perovich, D., Clemente-Colon, P., Weatherly, J., and
Neumann, G.: Rapid reduction of Arctic perennial sea ice, Geophys. Res.
Lett., 34, L19504, https://doi.org/10.1029/2007GL031138, 2007.
Onarheim, I. H., Eldevik, T., Smedsrud, L. H., and Stroeve, J. C.: Seasonal
and Regional Manifestation of Arctic Sea Ice Loss, J. Climate, 31,
4917–4932, https://doi.org/10.1175/JCLI-D-17-0427.1, 2018.
Parkinson, C. L., Cavalieri, D. J., Gloersen, P., Zwally, H. J., and Comiso,
J. C.: Arctic sea ice extents, areas, and trends, 1978–1996, J. Geophys.
Res., 104, 20837–20856, https://doi.org/10.1029/1999JC900082, 1999.
Perovich, D. K. and Light, B.: Sunlight, Sea Ice, and the Ice Albedo Feedback
in a Changing Arctic Sea Ice Cover. Hanover (NH): Army Engineer Research and
Development Center (US), Report No.: AD1013715, 2015.
Perovich, D. K. and Polashenski, C.: Albedo evolution of seasonal Arctic sea
ice, Geophys. Res. Lett., 39, L08501, https://doi.org/10.1029/2012GL051432, 2012.
Perovich, D. K., Nghiem, S., Markus, T., and Schweiger, A.: Seasonal
evolution and interannual variability of the local solar energy absorbed by
the Arctic sea ice-ocean system, J. Geophys. Res.-Oceans, 112, C03005,
https://doi.org/10.1029/2006JC003558, 2007.
Pinker, R. T., Niu, X., and Ma, Y.: Solar heating of the Arctic Ocean in the
context of ice-albedo feedback, J. Geophys. Res.-Oceans, 119, 8395–8409,
https://doi.org/10.1002/2014JC010232, 2014.
Pistone, K., Eisenman, I., and Ramanathan, V.: Observational determination of
albedo decrease caused by vanishing Arctic sea ice, P. Natl. Acad. Sci. USA,
111, 3322–3326, https://doi.org/10.1073/pnas.1318201111, 2014.
Polyakov, I. V., Walsh, J. E., and Kwok, R.: Recent changes of Arctic
multiyear sea-ice coverage and the likely causes, B. Am. Meteorol. Soc. 93,
145–151, https://doi.org/10.1175/bams-d-11-00070.1, 2012.
Qu, X. and Hall, A.: What controls the strength of the snow-albedo feedback?,
J. Climate, 20, 3971–3981, https://doi.org/10.1175/JCLI4186.1, 2007.
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J.,
Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G., Bloom, S.,
Chen, J., Collins, D., Conaty, A., da Silva, A., Gu, W., Joiner, J., Koster,
R. D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P., Redder, C.
R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and
Woollen, J.: MERRA: NASA's modern-era retrospective analysis for research and
applications, J. Climate, 24, 3624–3648, 2011.
Robinson, D. A. and Frei, A.: Seasonal variability of northern hemisphere
snow extent using visible satellite data, Professional Geographer, 51,
307–314, 2000.
Robinson, D. A., Dewey, K. F., and Heim, R. R.: Global Snow Cover Monitoring:
An Update, B. Am. Meteorol. Soc., 74, 1689–1696, 1993.
Rösel, A. and Kaleschke, L.: Exceptional melt pond occurrence in the
years 2007 and 2011 on the Arctic sea ice revealed from MODIS satellite data,
J. Geophys. Res.-Oceans, 117, C05018, https://doi.org/10.1029/2011JC007869, 2012.
Rösel, A., Kaleschke, L., and Birnbaum, G.: Melt ponds on Arctic sea ice
determined from MODIS satellite data using an artificial neural network, The
Cryosphere, 6, 431–446, https://doi.org/10.5194/tc-6-431-2012, 2012.
Serreze, M. C., Holland, M. M., and Stroeve, J.: Perspectives on the Arctic's
shrinking sea-ice cover, Science, 315, 1533–1536, 2007.
Stroeve, J. C., Serreze, M. C., Holland, M. M., Kay, J. E., Maslanik, J., and
Barrett, A. P.: The Arctic's rapidly shrinking sea ice cover: a research
synthesis, Clim. Change, 110, 1005–1027, https://doi.org/10.1007/s10584-011-0101-1,
2012.
Stone, R. S., Dutton, E. G., Harris, J. M., and Longenecker, D.: Earlier
spring snowmelt in northern Alaska as an indicator of climate change, J.
Geophys. Res., 107, 4089, https://doi.org/10.1029/2000JD000286, 2002.
Stroeve, J. C., Markus, T., Boisvert, L., Miller, J., and Barret, A.: Changes
in the Arctic melt season and implications for sea ice loss, Geophys. Res.
Lett., 41, 1216–1225, https://doi.org/10.1002/2013GL058951, 2014.
Sturm, M., Douglas, T., Racine, C., and Liston, G. E.: Changing snow and
shrub conditions affect albedo with global implications, J. Geophys. Res.,
110, G01004, https://doi.org/10.1029/2005JG000013, 2005.
Thackeray, C. W., Fletcher, C. G., Mudryk, L. R., and Derksen, C.:
Quantifying the Uncertainty in Historical and Future Simulations of Northern
Hemisphere Spring Snow Cover, J. Climate, 29, 8647–8663,
https://doi.org/10.1175/JCLI-D-16-0341.1, 2016.
Wang, X. and Key, J.: Arctic Surface, Cloud, and Radiation Properties Based
on the AVHRR Polar Pathfinder Dataset, Part I: Spatial and Temporal
Characteristics, J. Climate, 18, 2558–2574, https://doi.org/10.1175/JCLI3438.1, 2005.
Short summary
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.
Significant reductions in Arctic sea ice and snow cover on Arctic land have led to increases in...
