Articles | Volume 16, issue 3
The Cryosphere, 16, 1107–1123, 2022
https://doi.org/10.5194/tc-16-1107-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Cryosphere, 16, 1107–1123, 2022
https://doi.org/10.5194/tc-16-1107-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
31 Mar 2022
Research article
| 31 Mar 2022
Contribution of warm and moist atmospheric flow to a record minimum July sea ice extent of the Arctic in 2020
Yu Liang et al.
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Yunhe Wang, Xiaojun Yuan, Haibo Bi, Mitchell Bushuk, Yu Liang, Cuihua Li, and Haijun Huang
The Cryosphere, 16, 1141–1156, https://doi.org/10.5194/tc-16-1141-2022, https://doi.org/10.5194/tc-16-1141-2022, 2022
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We develop a regional linear Markov model consisting of four modules with seasonally dependent variables in the Pacific sector. The model retains skill for detrended sea ice extent predictions for up to 7-month lead times in the Bering Sea and the Sea of Okhotsk. The prediction skill, as measured by the percentage of grid points with significant correlations (PGS), increased by 75 % in the Bering Sea and 16 % in the Sea of Okhotsk relative to the earlier pan-Arctic model.
Haibo Bi, Qinghua Yang, Xi Liang, Liang Zhang, Yunhe Wang, Yu Liang, and Haijun Huang
The Cryosphere, 13, 1423–1439, https://doi.org/10.5194/tc-13-1423-2019, https://doi.org/10.5194/tc-13-1423-2019, 2019
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The Arctic sea ice extent is diminishing, which is deemed an immediate response to a warmer Earth. However, quantitative estimates about the contribution due to transport and melt to the sea ice loss are still vague. This study mainly utilizes satellite observations to quantify the dynamic and thermodynamic aspects of ice loss for nearly 40 years (1979–2016). In addition, the potential impacts on ice reduction due to different atmospheric circulation pattern are highlighted.
Haibo Bi, Zehua Zhang, Yunhe Wang, Xiuli Xu, Yu Liang, Jue Huang, Yilin Liu, and Min Fu
The Cryosphere, 13, 1025–1042, https://doi.org/10.5194/tc-13-1025-2019, https://doi.org/10.5194/tc-13-1025-2019, 2019
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Baffin Bay serves as a huge reservoir of sea ice which provides solid freshwater sources for the seas downstream. Based on satellite observations, significant increasing trends are found for the annual sea ice area flux through the three gates. These trends are chiefly related to the increasing ice motion which is associated with thinner ice owing to the warmer climate (i.e., higher surface air temperature and shortened freezing period) and increased air and water drag coefficients.
Yafei Nie, Chengkun Li, Martin Vancoppenolle, Bin Cheng, Fabio Boeira Dias, Xianqing Lv, and Petteri Uotila
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-170, https://doi.org/10.5194/gmd-2022-170, 2022
Preprint under review for GMD
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State-of-the-art Earth System Models simulate the observed sea ice extent relatively well, but this is often due to errors in the dynamic and the other processes in the simulated sea ice changes cancelling each other out. We assessed the sensitivity of these processes simulated by the coupled ocean-sea ice model NEMO4.0-SI3 to 18 parameters. The performance of the model in simulating sea ice change processes was ultimately improved by adjusting the three identified key parameters.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Yunhe Wang, Xiaojun Yuan, Haibo Bi, Mitchell Bushuk, Yu Liang, Cuihua Li, and Haijun Huang
The Cryosphere, 16, 1141–1156, https://doi.org/10.5194/tc-16-1141-2022, https://doi.org/10.5194/tc-16-1141-2022, 2022
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We develop a regional linear Markov model consisting of four modules with seasonally dependent variables in the Pacific sector. The model retains skill for detrended sea ice extent predictions for up to 7-month lead times in the Bering Sea and the Sea of Okhotsk. The prediction skill, as measured by the percentage of grid points with significant correlations (PGS), increased by 75 % in the Bering Sea and 16 % in the Sea of Okhotsk relative to the earlier pan-Arctic model.
Bin Cheng, Yubing Cheng, Timo Vihma, Anna Kontu, Fei Zheng, Juha Lemmetyinen, Yubao Qiu, and Jouni Pulliainen
Earth Syst. Sci. Data, 13, 3967–3978, https://doi.org/10.5194/essd-13-3967-2021, https://doi.org/10.5194/essd-13-3967-2021, 2021
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Climate change strongly impacts the Arctic, with clear signs of higher air temperature and more precipitation. A sustainable observation programme has been carried out in Lake Orajärvi in Sodankylä, Finland. The high-quality air–snow–ice–water temperature profiles have been measured every winter since 2009. The data can be used to investigate the lake ice surface heat balance and the role of snow in lake ice mass balance and parameterization of snow-to-ice transformation in snow/ice models.
Ruibo Lei, Mario Hoppmann, Bin Cheng, Guangyu Zuo, Dawei Gui, Qiongqiong Cai, H. Jakob Belter, and Wangxiao Yang
The Cryosphere, 15, 1321–1341, https://doi.org/10.5194/tc-15-1321-2021, https://doi.org/10.5194/tc-15-1321-2021, 2021
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Quantification of ice deformation is useful for understanding of the role of ice dynamics in climate change. Using data of 32 buoys, we characterized spatiotemporal variations in ice kinematics and deformation in the Pacific sector of Arctic Ocean for autumn–winter 2018/19. Sea ice in the south and west has stronger mobility than in the east and north, which weakens from autumn to winter. An enhanced Arctic dipole and weakened Beaufort Gyre in winter lead to an obvious turning of ice drifting.
Shihe Ren, Xi Liang, Qizhen Sun, Hao Yu, L. Bruno Tremblay, Bo Lin, Xiaoping Mai, Fu Zhao, Ming Li, Na Liu, Zhikun Chen, and Yunfei Zhang
Geosci. Model Dev., 14, 1101–1124, https://doi.org/10.5194/gmd-14-1101-2021, https://doi.org/10.5194/gmd-14-1101-2021, 2021
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Sea ice plays a crucial role in global energy and water budgets. To get a better simulation of sea ice, we coupled a sea ice model with an atmospheric and ocean model to form a fully coupled system. The sea ice simulation results of this coupled system demonstrated that a two-way coupled model has better performance in terms of sea ice, especially in summer. This indicates that sea-ice–ocean–atmosphere interaction plays a crucial role in controlling Arctic summertime sea ice distribution.
Thomas Krumpen, Florent Birrien, Frank Kauker, Thomas Rackow, Luisa von Albedyll, Michael Angelopoulos, H. Jakob Belter, Vladimir Bessonov, Ellen Damm, Klaus Dethloff, Jari Haapala, Christian Haas, Carolynn Harris, Stefan Hendricks, Jens Hoelemann, Mario Hoppmann, Lars Kaleschke, Michael Karcher, Nikolai Kolabutin, Ruibo Lei, Josefine Lenz, Anne Morgenstern, Marcel Nicolaus, Uwe Nixdorf, Tomash Petrovsky, Benjamin Rabe, Lasse Rabenstein, Markus Rex, Robert Ricker, Jan Rohde, Egor Shimanchuk, Suman Singha, Vasily Smolyanitsky, Vladimir Sokolov, Tim Stanton, Anna Timofeeva, Michel Tsamados, and Daniel Watkins
The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, https://doi.org/10.5194/tc-14-2173-2020, 2020
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In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with it on the 1-year-long MOSAiC journey through the Arctic. Here we provide historical context of the floe's evolution and initial state for upcoming studies. We show that the ice encountered on site was exceptionally thin and was formed on the shallow Siberian shelf. The analyses presented provide the initial state for the analysis and interpretation of upcoming biogeochemical and ecological studies.
Dawei Gui, Xiaoping Pang, Ruibo Lei, Xi Zhao, and Jia Wang
Abstr. Int. Cartogr. Assoc., 1, 101, https://doi.org/10.5194/ica-abs-1-101-2019, https://doi.org/10.5194/ica-abs-1-101-2019, 2019
Haibo Bi, Qinghua Yang, Xi Liang, Liang Zhang, Yunhe Wang, Yu Liang, and Haijun Huang
The Cryosphere, 13, 1423–1439, https://doi.org/10.5194/tc-13-1423-2019, https://doi.org/10.5194/tc-13-1423-2019, 2019
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The Arctic sea ice extent is diminishing, which is deemed an immediate response to a warmer Earth. However, quantitative estimates about the contribution due to transport and melt to the sea ice loss are still vague. This study mainly utilizes satellite observations to quantify the dynamic and thermodynamic aspects of ice loss for nearly 40 years (1979–2016). In addition, the potential impacts on ice reduction due to different atmospheric circulation pattern are highlighted.
Wenfeng Huang, Bin Cheng, Jinrong Zhang, Zheng Zhang, Timo Vihma, Zhijun Li, and Fujun Niu
Hydrol. Earth Syst. Sci., 23, 2173–2186, https://doi.org/10.5194/hess-23-2173-2019, https://doi.org/10.5194/hess-23-2173-2019, 2019
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Up to now, little has been known on ice thermodynamics and lake–atmosphere interaction over the Tibetan Plateau during ice-covered seasons due to a lack of field data. Here, model experiments on ice thermodynamics were conducted in a shallow lake using HIGHTSI. Water–ice heat flux was a major source of uncertainty for lake ice thickness. Heat and mass budgets were estimated within the vertical air–ice–water system. Strong ice sublimation occurred and was responsible for water loss during winter.
Haibo Bi, Zehua Zhang, Yunhe Wang, Xiuli Xu, Yu Liang, Jue Huang, Yilin Liu, and Min Fu
The Cryosphere, 13, 1025–1042, https://doi.org/10.5194/tc-13-1025-2019, https://doi.org/10.5194/tc-13-1025-2019, 2019
Short summary
Short summary
Baffin Bay serves as a huge reservoir of sea ice which provides solid freshwater sources for the seas downstream. Based on satellite observations, significant increasing trends are found for the annual sea ice area flux through the three gates. These trends are chiefly related to the increasing ice motion which is associated with thinner ice owing to the warmer climate (i.e., higher surface air temperature and shortened freezing period) and increased air and water drag coefficients.
Timo Vihma, Petteri Uotila, Stein Sandven, Dmitry Pozdnyakov, Alexander Makshtas, Alexander Pelyasov, Roberta Pirazzini, Finn Danielsen, Sergey Chalov, Hanna K. Lappalainen, Vladimir Ivanov, Ivan Frolov, Anna Albin, Bin Cheng, Sergey Dobrolyubov, Viktor Arkhipkin, Stanislav Myslenkov, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 19, 1941–1970, https://doi.org/10.5194/acp-19-1941-2019, https://doi.org/10.5194/acp-19-1941-2019, 2019
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The Arctic marine climate system, ecosystems, and socio-economic systems are changing rapidly. This calls for the establishment of a marine Arctic component of the Pan-Eurasian Experiment (MA-PEEX), for which we present a plan. The program will promote international collaboration; sustainable marine meteorological, sea ice, and oceanographic observations; advanced data management; and multidisciplinary research on the marine Arctic and its interaction with the Eurasian continent.
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
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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.
T. Vihma, R. Pirazzini, I. Fer, I. A. Renfrew, J. Sedlar, M. Tjernström, C. Lüpkes, T. Nygård, D. Notz, J. Weiss, D. Marsan, B. Cheng, G. Birnbaum, S. Gerland, D. Chechin, and J. C. Gascard
Atmos. Chem. Phys., 14, 9403–9450, https://doi.org/10.5194/acp-14-9403-2014, https://doi.org/10.5194/acp-14-9403-2014, 2014
Related subject area
Discipline: Sea ice | Subject: Arctic (e.g. Greenland)
Kara and Barents sea ice thickness estimation based on CryoSat-2 radar altimeter and Sentinel-1 dual-polarized synthetic aperture radar
Perspectives on future sea ice and navigability in the Arctic
Improving model-satellite comparisons of sea ice melt onset with a satellite simulator
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 climate: changes in sea ice extent outweigh changes in snow cover
Arctic Mission Benefit Analysis: impact of sea ice thickness, freeboard, and snow depth products on sea ice forecast performance
Thin Arctic sea ice in L-band observations and an ocean reanalysis
Snow depth on Arctic sea ice from historical in situ data
Impacts of a lengthening open water season on Alaskan coastal communities: deriving locally relevant indices from large-scale datasets and community observations
Thermodynamic and dynamic ice thickness contributions in the Canadian Arctic Archipelago in NEMO-LIM2 numerical simulations
Juha Karvonen, Eero Rinne, Heidi Sallila, Petteri Uotila, and Marko Mäkynen
The Cryosphere, 16, 1821–1844, https://doi.org/10.5194/tc-16-1821-2022, https://doi.org/10.5194/tc-16-1821-2022, 2022
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We propose a method to provide sea ice thickness (SIT) estimates over a test area in the Arctic utilizing radar altimeter (RA) measurement lines and C-band SAR imagery. The RA data are from CryoSat-2, and SAR imagery is from Sentinel-1. By combining them we get a SIT grid covering the whole test area instead of only narrow measurement lines from RA. This kind of SIT estimation can be extended to cover the whole Arctic (and Antarctic) for operational SIT monitoring.
Jinlei Chen, Shichang Kang, Wentao Du, Junming Guo, Min Xu, Yulan Zhang, Xinyue Zhong, Wei Zhang, and Jizu Chen
The Cryosphere, 15, 5473–5482, https://doi.org/10.5194/tc-15-5473-2021, https://doi.org/10.5194/tc-15-5473-2021, 2021
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Sea ice is retreating with rapid warming in the Arctic. It will continue and approach the worst predicted pathway released by the IPCC. The irreversible tipping point might show around 2060 when the oldest ice will have completely disappeared. It has a huge impact on human production. Ordinary merchant ships will be able to pass the Northeast Passage and Northwest Passage by the midcentury, and the opening time will advance to the next 10 years for icebreakers with moderate ice strengthening.
Abigail Smith, Alexandra Jahn, Clara Burgard, and Dirk Notz
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-331, https://doi.org/10.5194/tc-2021-331, 2021
Revised manuscript accepted for TC
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The timing of Arctic sea ice melt each year is an important metric for assessing how sea ice in climate models compares to satellite observations. Here, we utilize a new tool for creating more direct comparisons between climate models 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.
Qiang Wang, Sergey Danilov, Longjiang Mu, Dmitry Sidorenko, and Claudia Wekerle
The Cryosphere, 15, 4703–4725, https://doi.org/10.5194/tc-15-4703-2021, https://doi.org/10.5194/tc-15-4703-2021, 2021
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Using simulations, we found that changes in ocean freshwater content induced by wind perturbations can significantly affect the Arctic sea ice drift, thickness, concentration and deformation rates years after the wind perturbations. The impact is through changes in sea surface height and surface geostrophic currents and the most pronounced in warm seasons. Such a lasting impact might become stronger in a warming climate and implies the importance of ocean initialization in sea ice prediction.
Henrieka Detlef, Brendan Reilly, Anne Jennings, Mads Mørk Jensen, Matt O'Regan, Marianne Glasius, Jesper Olsen, Martin Jakobsson, and Christof Pearce
The Cryosphere, 15, 4357–4380, https://doi.org/10.5194/tc-15-4357-2021, https://doi.org/10.5194/tc-15-4357-2021, 2021
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Here we examine the Nares Strait sea ice dynamics over the last 7000 years and their implications for the late Holocene readvance of the floating part of Petermann Glacier. We propose that the historically observed sea ice dynamics are a relatively recent feature, while most of the mid-Holocene was marked by variable sea ice conditions in Nares Strait. Nonetheless, major advances of the Petermann ice tongue were preceded by a shift towards harsher sea ice conditions in Nares Strait.
Timothy Williams, Anton Korosov, Pierre Rampal, and Einar Ólason
The Cryosphere, 15, 3207–3227, https://doi.org/10.5194/tc-15-3207-2021, https://doi.org/10.5194/tc-15-3207-2021, 2021
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neXtSIM (neXt-generation Sea Ice Model) includes a novel and extremely realistic way of modelling sea ice dynamics – i.e. how the sea ice moves and deforms in response to the drag from winds and ocean currents. It has been developed over the last few years for a variety of applications, but this paper represents its first demonstration in a forecast context. We present results for the time period from November 2018 to June 2020 and show that it agrees well with satellite observations.
Sourav Chatterjee, Roshin P. Raj, Laurent Bertino, Sebastian H. Mernild, Meethale Puthukkottu Subeesh, Nuncio Murukesh, and Muthalagu Ravichandran
The Cryosphere, 15, 1307–1319, https://doi.org/10.5194/tc-15-1307-2021, https://doi.org/10.5194/tc-15-1307-2021, 2021
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Sea ice in the Greenland Sea (GS) is important for its climatic (fresh water), economical (shipping), and ecological contribution (light availability). The study proposes a mechanism through which sea ice concentration in GS is partly governed by the atmospheric and ocean circulation in the region. The mechanism proposed in this study can be useful for assessing the sea ice variability and its future projection in the GS.
Ruibo Lei, Mario Hoppmann, Bin Cheng, Guangyu Zuo, Dawei Gui, Qiongqiong Cai, H. Jakob Belter, and Wangxiao Yang
The Cryosphere, 15, 1321–1341, https://doi.org/10.5194/tc-15-1321-2021, https://doi.org/10.5194/tc-15-1321-2021, 2021
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Quantification of ice deformation is useful for understanding of the role of ice dynamics in climate change. Using data of 32 buoys, we characterized spatiotemporal variations in ice kinematics and deformation in the Pacific sector of Arctic Ocean for autumn–winter 2018/19. Sea ice in the south and west has stronger mobility than in the east and north, which weakens from autumn to winter. An enhanced Arctic dipole and weakened Beaufort Gyre in winter lead to an obvious turning of ice drifting.
Beena Balan-Sarojini, Steffen Tietsche, Michael Mayer, Magdalena Balmaseda, Hao Zuo, Patricia de Rosnay, Tim Stockdale, and Frederic Vitart
The Cryosphere, 15, 325–344, https://doi.org/10.5194/tc-15-325-2021, https://doi.org/10.5194/tc-15-325-2021, 2021
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Our study for the first time shows the impact of measured sea ice thickness (SIT) on seasonal forecasts of all the seasons. We prove that the long-term memory present in the Arctic winter SIT is helpful to improve summer sea ice forecasts. Our findings show that realistic SIT initial conditions to start a forecast are useful in (1) improving seasonal forecasts, (2) understanding errors in the forecast model, and (3) recognizing the need for continuous monitoring of world's ice-covered oceans.
Chao Min, Qinghua Yang, Longjiang Mu, Frank Kauker, and Robert Ricker
The Cryosphere, 15, 169–181, https://doi.org/10.5194/tc-15-169-2021, https://doi.org/10.5194/tc-15-169-2021, 2021
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An ensemble of four estimates of the sea-ice volume (SIV) variations in Baffin Bay from 2011 to 2016 is generated from the locally merged satellite observations, three modeled sea ice thickness sources (CMST, NAOSIM, and PIOMAS) and NSIDC ice drift data (V4). Results show that the net increase of the ensemble mean SIV occurs from October to April with the largest SIV increase in December, and the reduction occurs from May to September with the largest SIV decline in July.
Mohammed E. Shokr, Zihan Wang, and Tingting Liu
The Cryosphere, 14, 3611–3627, https://doi.org/10.5194/tc-14-3611-2020, https://doi.org/10.5194/tc-14-3611-2020, 2020
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This paper uses sequential daily SAR images covering the Robeson Channel to quantitatively study kinematics of individual ice floes with exploration of wind influence and the evolution of the ice arch at the entry of the channel. Results show that drift of ice floes within the Robeson Channel and the arch are both significantly influenced by wind. The study highlights the advantage of using the high-resolution daily SAR coverage in monitoring sea ice cover in narrow water passages.
Guillian Van Achter, Leandro Ponsoni, François Massonnet, Thierry Fichefet, and Vincent Legat
The Cryosphere, 14, 3479–3486, https://doi.org/10.5194/tc-14-3479-2020, https://doi.org/10.5194/tc-14-3479-2020, 2020
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We document the spatio-temporal internal variability of Arctic sea ice thickness and its changes under anthropogenic forcing, which is key to understanding, and eventually predicting, the evolution of sea ice in response to climate change.
The patterns of sea ice thickness variability remain more or less stable during pre-industrial, historical and future periods, despite non-stationarity on short timescales. These patterns start to change once Arctic summer ice-free events occur, after 2050.
Abigail Smith, Alexandra Jahn, and Muyin Wang
The Cryosphere, 14, 2977–2997, https://doi.org/10.5194/tc-14-2977-2020, https://doi.org/10.5194/tc-14-2977-2020, 2020
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The annual cycle of Arctic sea ice can be used to gain more information about how climate model simulations of sea ice compare to observations. In some models, the September sea ice area agrees with observations for the wrong reasons because biases in the timing of seasonal transitions compensate for other unrealistic sea ice characteristics. This research was done to provide new process-based metrics of Arctic sea ice using satellite observations, the CESM Large Ensemble, and CMIP6 models.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
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The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
Thomas Krumpen, Florent Birrien, Frank Kauker, Thomas Rackow, Luisa von Albedyll, Michael Angelopoulos, H. Jakob Belter, Vladimir Bessonov, Ellen Damm, Klaus Dethloff, Jari Haapala, Christian Haas, Carolynn Harris, Stefan Hendricks, Jens Hoelemann, Mario Hoppmann, Lars Kaleschke, Michael Karcher, Nikolai Kolabutin, Ruibo Lei, Josefine Lenz, Anne Morgenstern, Marcel Nicolaus, Uwe Nixdorf, Tomash Petrovsky, Benjamin Rabe, Lasse Rabenstein, Markus Rex, Robert Ricker, Jan Rohde, Egor Shimanchuk, Suman Singha, Vasily Smolyanitsky, Vladimir Sokolov, Tim Stanton, Anna Timofeeva, Michel Tsamados, and Daniel Watkins
The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, https://doi.org/10.5194/tc-14-2173-2020, 2020
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In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with it on the 1-year-long MOSAiC journey through the Arctic. Here we provide historical context of the floe's evolution and initial state for upcoming studies. We show that the ice encountered on site was exceptionally thin and was formed on the shallow Siberian shelf. The analyses presented provide the initial state for the analysis and interpretation of upcoming biogeochemical and ecological studies.
Sukun Cheng, Justin Stopa, Fabrice Ardhuin, and Hayley H. Shen
The Cryosphere, 14, 2053–2069, https://doi.org/10.5194/tc-14-2053-2020, https://doi.org/10.5194/tc-14-2053-2020, 2020
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Wave states in ice in polar oceans are mostly studied near the ice edge. However, observations in the internal ice field, where ice morphology is very different from the ice edge, are rare. Recently derived wave data from satellite imagery are easier and cheaper than field studies and provide large coverage. This work presents a way of using these data to have a close view of some key features in the wave propagation over hundreds of kilometers and calibrate models for predicting wave decay.
Jutta E. Wollenburg, Morten Iversen, Christian Katlein, Thomas Krumpen, Marcel Nicolaus, Giulia Castellani, Ilka Peeken, and Hauke Flores
The Cryosphere, 14, 1795–1808, https://doi.org/10.5194/tc-14-1795-2020, https://doi.org/10.5194/tc-14-1795-2020, 2020
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Based on an observed omnipresence of gypsum crystals, we concluded that their release from melting sea ice is a general feature in the Arctic Ocean. Individual gypsum crystals sank at more than 7000 m d−1, suggesting that they are an important ballast mineral. Previous observations found gypsum inside phytoplankton aggregates at 2000 m depth, supporting gypsum as an important driver for pelagic-benthic coupling in the ice-covered Arctic Ocean.
Xiaoyong Yu, Annette Rinke, Wolfgang Dorn, Gunnar Spreen, Christof Lüpkes, Hiroshi Sumata, and Vladimir M. Gryanik
The Cryosphere, 14, 1727–1746, https://doi.org/10.5194/tc-14-1727-2020, https://doi.org/10.5194/tc-14-1727-2020, 2020
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This study presents an evaluation of Arctic sea ice drift speed for the period 2003–2014 in a state-of-the-art coupled regional model for the Arctic, called HIRHAM–NAOSIM. In particular, the dependency of the drift speed on the near-surface wind speed and sea ice conditions is presented. Effects of sea ice form drag included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice are discussed.
Yinghui Liu, Jeffrey R. Key, Xuanji Wang, and Mark Tschudi
The Cryosphere, 14, 1325–1345, https://doi.org/10.5194/tc-14-1325-2020, https://doi.org/10.5194/tc-14-1325-2020, 2020
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This study provides a consistent and accurate multi-decadal product of ice thickness and ice volume from 1984 to 2018 based on satellite-derived ice age. Sea ice volume trends from this dataset are stronger than the trends from other datasets. Changes in sea ice thickness contribute more to overall sea ice volume trends than changes in sea ice area do in all months.
Alice K. DuVivier, Patricia DeRepentigny, Marika M. Holland, Melinda Webster, Jennifer E. Kay, and Donald Perovich
The Cryosphere, 14, 1259–1271, https://doi.org/10.5194/tc-14-1259-2020, https://doi.org/10.5194/tc-14-1259-2020, 2020
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In autumn 2019, a ship will be frozen into the Arctic sea ice for a year to study system changes. We analyze climate model data from a group of experiments and follow virtual sea ice floes throughout a year. The modeled sea ice conditions along possible tracks are highly variable. Observations that sample a wide range of sea ice conditions and represent the variety and diversity in possible conditions are necessary for improving climate model parameterizations over all types of sea ice.
Xiao-Yi Yang, Guihua Wang, and Noel Keenlyside
The Cryosphere, 14, 693–708, https://doi.org/10.5194/tc-14-693-2020, https://doi.org/10.5194/tc-14-693-2020, 2020
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The post-2007 Arctic sea ice cover is characterized by a remarkable increase in annual cycle amplitude, which is attributed to multiyear variability in spring Bering sea ice extent. We demonstrated that changes of NPGO mode, by anomalous wind stress curl and Ekman pumping, trigger subsurface variability in the Bering basin. This accounts for the significant decadal oscillation of spring Bering sea ice after 2007. The study helps us to better understand the recent Arctic climate regime shift.
Adam W. Bateson, Daniel L. Feltham, David Schröder, Lucia Hosekova, Jeff K. Ridley, and Yevgeny Aksenov
The Cryosphere, 14, 403–428, https://doi.org/10.5194/tc-14-403-2020, https://doi.org/10.5194/tc-14-403-2020, 2020
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The Arctic sea ice cover has been observed to be decreasing, particularly in summer. We use numerical models to gain insight into processes controlling its seasonal and decadal evolution. Sea ice is made of pieces of ice called floes. Previous models have set these floes to be the same size, which is not supported by observations. In this study we show that accounting for variable floe size reveals the importance of sea ice regions close to the open ocean in driving seasonal retreat of sea ice.
Alex West, Mat Collins, Ed Blockley, Jeff Ridley, and Alejandro Bodas-Salcedo
The Cryosphere, 13, 2001–2022, https://doi.org/10.5194/tc-13-2001-2019, https://doi.org/10.5194/tc-13-2001-2019, 2019
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This study presents a framework for examining the causes of model errors in Arctic sea ice volume, using HadGEM2-ES as a case study. Simple models are used to estimate how much of the error in energy arriving at the ice surface is due to error in key Arctic climate variables. The method quantifies how each variable affects sea ice volume balance and shows that for HadGEM2-ES an annual mean low bias in ice thickness is likely due to errors in surface melt onset.
Caixin Wang, Robert M. Graham, Keguang Wang, Sebastian Gerland, and Mats A. Granskog
The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, https://doi.org/10.5194/tc-13-1661-2019, 2019
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A warm bias and higher total precipitation and snowfall were found in ERA5 compared with ERA-Interim (ERA-I) over Arctic sea ice. The warm bias in ERA5 was larger in the cold season when 2 m air temperature was < −25 °C and smaller in the warm season than in ERA-I. Substantial anomalous Arctic rainfall in ERA-I was reduced in ERA5, particularly in summer and autumn. When using ERA5 and ERA-I to force a 1-D sea ice model, the effects on ice growth are very small (cm) during the freezing period.
John E. Walsh, J. Scott Stewart, and Florence Fetterer
The Cryosphere, 13, 1073–1088, https://doi.org/10.5194/tc-13-1073-2019, https://doi.org/10.5194/tc-13-1073-2019, 2019
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Persistence-based statistical forecasts of a Beaufort Sea ice severity index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the trends are removed from the data. This finding is consistent with the notion of a springtime “predictability barrier” that has been found in sea ice forecasts based on more sophisticated methods.
Leandro Ponsoni, François Massonnet, Thierry Fichefet, Matthieu Chevallier, and David Docquier
The Cryosphere, 13, 521–543, https://doi.org/10.5194/tc-13-521-2019, https://doi.org/10.5194/tc-13-521-2019, 2019
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The Arctic is a main component of the Earth's climate system. It is fundamental to understand the behavior of Arctic sea ice coverage over time and in space due to many factors, e.g., shipping lanes, the travel and tourism industry, hunting and fishing activities, mineral resource extraction, and the potential impact on the weather in midlatitude regions. In this work we use observations and results from models to understand how variations in the sea ice thickness change over time and in space.
John R. Mioduszewski, Stephen Vavrus, Muyin Wang, Marika Holland, and Laura Landrum
The Cryosphere, 13, 113–124, https://doi.org/10.5194/tc-13-113-2019, https://doi.org/10.5194/tc-13-113-2019, 2019
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Arctic sea ice is projected to thin substantially in every season by the end of the 21st century with a corresponding increase in its interannual variability as the rate of ice loss peaks. This typically occurs when the mean ice thickness falls between 0.2 and 0.6 m. The high variability in both growth and melt processes is the primary factor resulting in increased ice variability. This study emphasizes the importance of short-term variations in ice cover within the mean downward trend.
Marion Lebrun, Martin Vancoppenolle, Gurvan Madec, and François Massonnet
The Cryosphere, 13, 79–96, https://doi.org/10.5194/tc-13-79-2019, https://doi.org/10.5194/tc-13-79-2019, 2019
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The present analysis shows that the increase in the Arctic ice-free season duration will be asymmetrical, with later autumn freeze-up contributing about twice as much as earlier spring retreat. This feature is robustly found in a hierarchy of climate models and is consistent with a simple mechanism: solar energy is absorbed more efficiently than it can be released in non-solar form and should emerge out of variability within the next few decades.
Abigail Smith and Alexandra Jahn
The Cryosphere, 13, 1–20, https://doi.org/10.5194/tc-13-1-2019, https://doi.org/10.5194/tc-13-1-2019, 2019
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Here we assessed how natural climate variations and different definitions impact the diagnosed and projected Arctic sea ice melt season length using model simulations. Irrespective of the definition or natural variability, the sea ice melt season is projected to lengthen, potentially by as much as 4–5 months by 2100 under the business as usual scenario. We also find that different definitions have a bigger impact on melt onset, while natural variations have a bigger impact on freeze onset.
Yuanyuan Zhang, Xiao Cheng, Jiping Liu, and Fengming Hui
The Cryosphere, 12, 3747–3757, https://doi.org/10.5194/tc-12-3747-2018, https://doi.org/10.5194/tc-12-3747-2018, 2018
Aaron Letterly, Jeffrey Key, and Yinghui Liu
The Cryosphere, 12, 3373–3382, https://doi.org/10.5194/tc-12-3373-2018, https://doi.org/10.5194/tc-12-3373-2018, 2018
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Significant reductions in Arctic sea ice and snow cover on Arctic land have led to increases in absorbed solar energy by the surface. Does one play a more important role in Arctic climate change? Using 34 years of satellite data we found that solar energy absorption increased by 10 % over the ocean, which was 3 times greater than over land. Therefore, the decreasing sea ice cover, not changes in terrestrial snow cover, has been the dominant feedback mechanism over the last few decades.
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
The Cryosphere, 12, 2569–2594, https://doi.org/10.5194/tc-12-2569-2018, https://doi.org/10.5194/tc-12-2569-2018, 2018
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We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
Steffen Tietsche, Magdalena Alonso-Balmaseda, Patricia Rosnay, Hao Zuo, Xiangshan Tian-Kunze, and Lars Kaleschke
The Cryosphere, 12, 2051–2072, https://doi.org/10.5194/tc-12-2051-2018, https://doi.org/10.5194/tc-12-2051-2018, 2018
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We compare Arctic sea-ice thickness from L-band microwave satellite observations and an ocean–sea ice reanalysis. There is good agreement for some regions and times but systematic discrepancy in others. Errors in both the reanalysis and observational products contribute to these discrepancies. Thus, we recommend proceeding with caution when using these observations for model validation or data assimilation. At the same time we emphasise their unique value for improving sea-ice forecast models.
Elena V. Shalina and Stein Sandven
The Cryosphere, 12, 1867–1886, https://doi.org/10.5194/tc-12-1867-2018, https://doi.org/10.5194/tc-12-1867-2018, 2018
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In this paper we analyze snow data from Soviet airborne expeditions, Sever, which operated in late winter 1959-1986, in the Arctic and made snow measurements on the ice around plane landing sites. The snow measurements were made on the multiyear ice in the central Arctic and on the first-year ice in the Eurasian seas in the areas for which snow characteristics are poorly described in the literature. The main goal of this study is to produce an improved data set of snow depth on the sea ice.
Rebecca J. Rolph, Andrew R. Mahoney, John Walsh, and Philip A. Loring
The Cryosphere, 12, 1779–1790, https://doi.org/10.5194/tc-12-1779-2018, https://doi.org/10.5194/tc-12-1779-2018, 2018
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Using thresholds of physical climate variables developed from community observations, together with two large-scale datasets, we have produced local indices directly relevant to the impacts of a reduced sea ice cover on Alaska coastal communities. We demonstrate how community observations can inform use of large-scale datasets to derive these locally relevant indices.
Xianmin Hu, Jingfan Sun, Ting On Chan, and Paul G. Myers
The Cryosphere, 12, 1233–1247, https://doi.org/10.5194/tc-12-1233-2018, https://doi.org/10.5194/tc-12-1233-2018, 2018
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We evaluated the sea ice thickness simulation in the Canadian Arctic Archipelago region using 1/4 and 1/12 degree NEMO LIM2 configurations. Model resolution dose not play a significant role. Relatively smaller thermodynamic contribution in the winter season is found in the thick ice covered areas, with larger contributions in the thin ice covered regions. No significant trend in winter maximum ice volume is found in the northern CAA and Baffin Bay but a decline is simulated within Parry Channel.
Cited articles
Årthun, M. and Eldevik, T.: On anomalous ocean heat transport toward
the Arctic and associated climate predictability, J. Climate, 29,
689–704, 2016.
Årthun, M., Eldevik, T., Smedsrud, L., Skagseth, Ø., and Ingvaldsen,
R.: Quantifying the influence of Atlantic heat on Barents Sea ice
variability and retreat, J. Climate, 25, 4736–4743, 2012.
Babar, B., Graversen, R., and Boström, T.: Solar radiation estimation at
high latitudes: Assessment of the CMSAF databases, ASR and ERA5, Sol.
Energy, 182, 397–411, 2019.
Ballinger, T. J., Overland, J. E., Wang, M., Bhatt, U. S., Hanna, E., Hanssen-Bauer, I., Kim, S. J., Thoman, R. L., and Walsh, J. E.: Arctic Report Card 2020: Surface Air Temperature, National Oceanic and Atmospheric Administration, https://doi.org/10.25923/gcw8-2z06, 2020.
Baxter, I., Ding, Q., Schweiger, A., L'Heureux, M., Baxter, S., Wang, T.,
Zhang, Q., Harnos, K., Markle, B., and Topal, D.: How tropical Pacific
surface cooling contributed to accelerated sea ice melt from 2007 to 2012 as
ice is thinned by anthropogenic forcing, J. Climate, 32, 8583–8602,
2019.
Bi, H., Zhang, J., Wang, Y., Zhang, Z., Zhang, Y., Fu, M., Huang, H., and
Xu, X.: Arctic Sea Ice Volume Changes in Terms of Age as Revealed From
Satellite Observations, IEEE J. Sel. Top. Appl., 11, 2223–2237, 2018.
Bi, H., Zhang, Z., Wang, Y., Xu, X., Liang, Y., Huang, J., Liu, Y., and Fu, M.: Baffin Bay sea ice inflow and outflow: 1978–1979 to 2016–2017, The Cryosphere, 13, 1025–1042, https://doi.org/10.5194/tc-13-1025-2019, 2019.
Bi, H., Wang, Y., Liang, Y., Sun, W., Liang, X., Yu, Q., Zhang, Z., and Xu,
X.: Influences of Summertime Arctic Dipole Atmospheric Circulation on Sea
Ice Concentration Variations in the Pacific Sector of the Arctic during
Different Pacific Decadal Oscillation Phases, J. Climate, 34,
3003–3019, https://doi.org/10.1175/jcli-d-19-0843.1, 2021.
Brümmer, B., Müller, G., Affeld, B., Gerdes, R., Karcher, M., and
Kauker, F.: Cyclones over Fram Strait: impact on sea ice and variability,
Polar Res., 20, 147–152, https://doi.org/10.3402/polar.v20i2.6511, 2001.
Cesana, G., Kay, J. E., Chepfer, H., English, J. M., and de Boer, G.:
Ubiquitous low-level liquid-containing Arctic clouds: New observations and
climate model constraints from CALIPSO-GOCCP, Geophys. Res. Lett.,
39, L20804, https://doi.org/10.1029/2012GL053385, 2012.
Cohen, L., Hudson, S. R., Walden, V. P., Graham, R. M., and Granskog, M. A.:
Meteorological conditions in a thinner Arctic sea ice regime from winter
through summer during the Norwegian Young Sea Ice expedition (N-ICE2015),
J. Geophys. Res.-Atmos., 122, 7235–7259, https://doi.org/10.1002/2016JD026034, 2017.
Comiso, J. C.: Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP
SSM/I-SSMIS, Version 3, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/7Q8HCCWS4I0R,
2017.
Comiso, J. C. and Hall, D. K.: Climate trends in the Arctic as observed
from space, Wiley Interdiscip. Rev. Clim. Change, 5, 389–409, https://doi.org/10.1002/wcc.277,
2014.
Crépin, A.-S., Karcher, M., and Gascard, J.-C.: Arctic climate change,
economy and society (ACCESS): Integrated perspectives, Ambio, 46, 341–354,
2017.
Curry, J. A., Schramm, J. L., Rossow, W. B., and Randall, D.: Overview of
Arctic Cloud and Radiation Characteristics, J. Climate, 9,
1731–1764, 1996.
Deser, C. and Teng, H.: Evolution of Arctic sea ice concentration trends
and the role of atmospheric circulation forcing, 1979–2007, Geophys.
Res. Lett., 35, L02504, https://doi.org/10.1029/2007gl032023, 2008.
Deser, C., Walsh, J. E., and Timlin, M. S.: Arctic sea ice variability in
the context of recent atmospheric circulation trends, J. Climate,
13, 617–633, https://doi.org/10.1175/1520-0442(2000)013<0617:Asivit>2.0.Co;2, 2000.
Ding, Q., Schweiger, A., L'Heureux, M., Battisti, David S., Po-Chedley, S.,
Johnson, Nathaniel C., Blanchard-Wrigglesworth, E., Harnos, K., Zhang, Q.,
Eastman, R., and Steig, Eric J.: Influence of high-latitude atmospheric
circulation changes on summertime Arctic sea ice, Nat. Clim. Change, 7,
289–295, https://doi.org/10.1038/nclimate3241, 2017.
Dmitrenko, I., Gribanov, V., Volkov, D., Berezovskaya, S., and Kassens, H.:
The role of river runoff in the interannual variability of the fast-ice
extension in the Russian Arctic, Russ. Meteorol. Hydrol., 3, 65–72, 2000.
Dou, T., Xiao, C., Liu, J., Wang, Q., Pan, S., Su, J., Yuan, X., Ding, M., Zhang, F., Xue, K., Bieniek, P. A., and Eicken, H.: Trends and spatial variation in rain-on-snow events over the Arctic Ocean during the early melt season, The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, 2021.
Doyle, J., Lesins, G., Thackray, C., Perro, C., Nott, G., Duck, T., Damoah,
R., and Drummond, J.: Water vapor intrusions into the High Arctic during
winter, Geophys. Res. Lett., 38, L12806,
https://doi.org/10.1029/2011GL047493, 2011.
Dufour, A., Zolina, O., and Gulev, S. K.: Atmospheric moisture transport to
the Arctic: Assessment of reanalyses and analysis of transport components,
J. Climate, 29, 5061–5081, 2016.
English, J. M., Gettelman, A., and Henderson, G. R.: Arctic Radiative
Fluxes: Present-Day Biases and Future Projections in CMIP5 Models, J.
Climate, 28, 6019–6038, https://doi.org/10.1175/jcli-d-14-00801.1, 2015.
Gaffney, S.: Probabilistic curve-aligned clustering and prediction with
regression mixture models, University of California, Irvine, 2004.
Graversen, R. G., Mauritsen, T., Tjernström, M., Källén, E., and
Svensson, G.: Vertical structure of recent Arctic warming, Nature, 451,
53–56, 2008.
Graversen, R. G., Mauritsen, T., Drijfhout, S., Tjernström, M., and
Mårtensson, S.: Warm winds from the Pacific caused extensive Arctic
sea-ice melt in summer 2007, Clim. Dynam., 36, 2103–2112, 2011.
Gu, S., Zhang, Y., Wu, Q., and Yang, X. Q.: The linkage between Arctic sea
ice and midlatitude weather: In the perspective of energy, J.
Geophys. Res.-Atmos., 123, 11536–511550, 2018.
Hall, A.: The role of surface albedo feedback in climate, J.
Climate, 17, 1550–1568, 2004.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., and Schepers, D.:
The ERA5 global reanalysis, Q. J. Roy. Meteor.
Soc., 146, 1999–2049, 2020.
Horvath, S., Stroeve, J., Rajagopalan, B., and Jahn, A.: Arctic sea ice melt
onset favored by an atmospheric pressure pattern reminiscent of the North
American-Eurasian Arctic pattern, Clim. Dynam., 57, 1771–1787,
https://doi.org/10.1007/s00382-021-05776-y, 2021.
Huang, Y., Dong, X., Xi, B., and Deng, Y.: A survey of the atmospheric
physical processes key to the onset of Arctic sea ice melt in spring,
Clim. Dynam., 52, 4907–4922, 2019.
Jakobson, E. and Vihma, T.: Atmospheric moisture budget in the Arctic based on the ERA-40 reanalysis, Int. J. Climatol., 30,
2175–2194, 2010.
Johansson, E., Devasthale, A., Tjernström, M., Ekman, A. M. L., and
L'Ecuyer, T.: Response of the lower troposphere to moisture intrusions into
the Arctic, Geophys. Res. Lett., 44, 2527–2536, https://doi.org/10.1002/2017GL072687, 2017.
Kapsch, M.-L., Graversen, R. G., and Tjernström, M.: Springtime
atmospheric energy transport and the control of Arctic summer sea-ice
extent, Nat. Clim. Change, 3, 744–748, 2013.
Kapsch, M.-L., Skific, N., Graversen, R. G., Tjernström, M., and
Francis, J. A.: Summers with low Arctic sea ice linked to persistence of
spring atmospheric circulation patterns, Clim. Dynam., 52, 2497–2512,
https://doi.org/10.1007/s00382-018-4279-z, 2019.
Kay, J. E., L'Ecuyer, T., Chepfer, H., Loeb, N., Morrison, A., and Cesana,
G.: Recent Advances in Arctic Cloud and Climate Research, Current Climate
Change Reports, 2, 159–169, https://doi.org/10.1007/s40641-016-0051-9, 2016.
Kim, K.-Y., Hamlington, B. D., Na, H., and Kim, J.: Mechanism of seasonal Arctic sea ice evolution and Arctic amplification, The Cryosphere, 10, 2191–2202, https://doi.org/10.5194/tc-10-2191-2016, 2016.
Komurcu, M., Storelvmo, T., Tan, I., Lohmann, U., Yun, Y., Penner, J. E.,
Wang, Y., Liu, X., and Takemura, T.: Intercomparison of the cloud water
phase among global climate models, J. Geophys. Res.-Atmos., 119, 3372–3400, 2014.
Koyama, T., Stroeve, J., Cassano, J., and Crawford, A.: Sea Ice Loss and
Arctic Cyclone Activity from 1979 to 2014, J. Climate, 30,
4735–4754, https://doi.org/10.1175/jcli-d-16-0542.1, 2017.
Krumpen, T., von Albedyll, L., Goessling, H. F., Hendricks, S., Juhls, B., Spreen, G., Willmes, S., Belter, H. J., Dethloff, K., Haas, C., Kaleschke, L., Katlein, C., Tian-Kunze, X., Ricker, R., Rostosky, P., Rückert, J., Singha, S., and Sokolova, J.: MOSAiC drift expedition from October 2019 to July 2020: sea ice conditions from space and comparison with previous years, The Cryosphere, 15, 3897–3920, https://doi.org/10.5194/tc-15-3897-2021, 2021.
Kwok, R.: Exchange of sea ice between the Arctic Ocean and the Canadian
Arctic Archipelago, Geophys. Res. Lett., 33, 627–642, 2006.
Kwok, R.: Baffin Bay ice drift and export: 2002–2007, Geophys. Res.
Lett., 34, L19501, https://doi.org/10.1029/2007GL031204, 2007.
Kwok, R.: Arctic sea ice thickness, volume, and multiyear ice coverage:
losses and coupled variability (1958–2018), Environ. Res. Lett., 13, 105005, https://doi.org/10.1088/1748-9326/aae3ec,
2018.
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.
Lei, R., Tian-Kunze, X., Leppäranta, M., Wang, J., Kaleschke, L., and
Zhang, Z.: Changes in summer sea ice, albedo, and portioning of surface
solar radiation in the Pacific sector of Arctic Ocean during 1982–2009,
J. Geophys. Res.-Oceans, 121, 5470–5486, 2016.
Lei, R., Gui, D., Hutchings, J. K., Wang, J., and Pang, X.: Backward and
forward drift trajectories of sea ice in the northwestern Arctic Ocean in
response to changing atmospheric circulation, Int. J.
Climatol., 39, 4372–4391, https://doi.org/10.1002/joc.6080, 2019.
Lei, R., Gui, D., Heil, P., Hutchings, J. K., and Ding, M.: Comparisons of
sea ice motion and deformation, and their responses to ice conditions and
cyclonic activity in the western Arctic Ocean between two summers, Cold
Reg. Sci. Technol., 170, 102925, https://doi.org/10.1016/j.coldregions.2019.102925, 2020.
Liang, Y., Bi, H., Wang, Y., Huang, H., Zhang, Z., Huang, J., and Liu, Y.:
Role of Extratropical Wintertime Cyclones in Regulating the Variations of
Baffin Bay Sea Ice Export, J. Geophys. Res.-Atmos.,
126, e2020JD033616, https://doi.org/10.1029/2020JD033616, 2021.
Liu, Z. and Schweiger, A.: Synoptic conditions, clouds, and sea ice melt
onset in the Beaufort and Chukchi seasonal ice zone, J. Climate, 30,
6999–7016, 2017.
Markus, T., Stroeve, J. C., 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.
Miles, M. W., Divine, D. V., Furevik, T., Jansen, E., Moros, M., and
Ogilvie, A. E.: A signal of persistent Atlantic multidecadal variability in
Arctic sea ice, Geophys. Res. Lett., 41, 463–469, 2014.
Mortin, J., Svensson, G., Graversen, R. G., Kapsch, M. L., Stroeve, J. C.,
and Boisvert, L. N.: Melt onset over Arctic sea ice controlled by
atmospheric moisture transport, Geophys. Res. Lett., 43, 6636–6642, https://doi.org/10.1002/2016GL069330, 2016.
NASA Earth Sciences: Arctic Sea Ice Melt, NASA Earth Sciences [data set], https://earth.gsfc.nasa.gov/index.php/cryo/data/arctic-sea-ice-melt, last
access: 22 February 2021.
Neu, U., Akperov, M. G., Bellenbaum, N., Benestad, R., Blender, R.,
Caballero, R., Cocozza, A., Dacre, H. F., Feng, Y., and Fraedrich, K.:
IMILAST: A community effort to intercompare extratropical cyclone detection
and tracking algorithms, B. Am. Meteorol. Soc.,
94, 529–547, 2013.
Ogi, M. and Wallace, J. M.: The role of summer surface wind anomalies in the summer Arctic sea ice extent in 2010 and 2011, Geophys. Res. Lett., 39, L09704, https://doi.org/10.1029/2012GL051330, 2012.
Ogi, M., Rysgaard, S., and Barber, D. G.: Importance of combined winter and
summer Arctic Oscillation (AO) on September sea ice extent, Environ. Res.
Lett., 11, 034019, https://doi.org/10.1088/1748-9326/11/3/034019, 2016.
Olason, E. and Notz, D.: Drivers of variability in Arctic sea-ice drift
speed, J. Geophys. Res.-Oceans, 119, 5755–5775, https://doi.org/10.1002/2014JC009897, 2015.
Overland, J., Francis, J. A., Hall, R., Hanna, E., Kim, S.-J., and Vihma,
T.: The melting Arctic and midlatitude weather patterns: Are they
connected?, J. Climate, 28, 7917–7932, 2015.
Papritz, L.: Arctic lower-tropospheric warm and cold extremes: Horizontal
and vertical transport, diabatic processes, and linkage to synoptic
circulation features, J. Climate, 33, 993–1016, 2020.
Parkinson, C. and Washington, W.: A large-scale numerical model of sea ice,
J. Geophys. Res., 84, 311–337, https://doi.org/10.1029/JC084iC01p00311, 1979.
Persson, P. O. G.: Onset and end of the summer melt season over sea ice:
Thermal structure and surface energy perspective from SHEBA, Clim.
Dynam., 39, 1349–1371, 2012.
Polar Science Center: PIOMAS Data, Polar Science Center [data set], http://psc.apl.uw.edu/research/projects/arctic-sea-ice-volume-anomaly/data/model_grid, last access: 23 March 2021.
Post, E., Bhatt, U. S., Bitz, C. M., Brodie, J. F., Fulton, T. L.,
Hebblewhite, M., Kerby, J., Kutz, S. J., Stirling, I., and Walker, D. A.:
Ecological consequences of sea-ice decline, Science, 341, 519–524, 2013.
Previdi, M., Janoski, T. P., Chiodo, G., Smith, K. L., and Polvani, L. M.:
Arctic amplification: A rapid response to radiative forcing, Geophys.
Res. Lett., 47, e2020GL089933, https://doi.org/10.1029/2020GL089933, 2020.
Rigor, I. G. and Wallace, J. M.: Variations in the age of Arctic sea-ice
and summer sea-ice extent, Geophys. Res. Lett., 31, L09401, https://doi.org/10.1029/2004GL019492, 2004.
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.
Screen, J. A. and Deser, C.: Pacific Ocean Variability Influences the Time
of Emergence of a Seasonally Ice-Free Arctic Ocean, Geophys. Res.
Lett., 46, 2222–2231, https://doi.org/10.1029/2018GL081393,
2019.
Sepp, M. and Jaagus, J.: Changes in the activity and tracks of Arctic
cyclones, Climatic Change, 105, 577–595, https://doi.org/10.1007/s10584-010-9893-7, 2011.
Serreze, M. C.: Climatological aspects of cyclone development and decay in
the Arctic, Journal of Atmosphere, 33, 1–23, https://doi.org/10.1080/07055900.1995.9649522, 1995.
Serreze, M. C. and Barry, R. G.: Processes and impacts of Arctic
amplification: A research synthesis, Global Planetary Change, 77, 85–96,
2011.
Serreze, M. C., Box, J. E., Barry, R. G., and Walsh, J. E.: Characteristics
of Arctic synoptic activity, 1952–1989, Meteorol. Atmos.
Phys., 51, 147–164, 1993.
Singh, H. K., Bitz, C. M., Donohoe, A., and Rasch, P.: A source–receptor
perspective on the polar hydrologic cycle: Sources, seasonality, and
Arctic–Antarctic parity in the hydrologic cycle response to CO2 doubling,
J. Climate, 30, 9999–10017, 2017.
Smedsrud, L. H., Halvorsen, M. H., Stroeve, J. C., Zhang, R., and Kloster, K.: Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years, The Cryosphere, 11, 65–79, https://doi.org/10.5194/tc-11-65-2017, 2017.
Stramler, K., Genio, A., and Rossow, W. B.: Synoptically Driven Arctic
Winter States, J. Climate, 24, 1747–1762, 2011.
Stroeve, J., Barrett, A., Serreze, M., and Schweiger, A.: Using records from submarine, aircraft and satellites to evaluate climate model simulations of Arctic sea ice thickness, The Cryosphere, 8, 1839–1854, https://doi.org/10.5194/tc-8-1839-2014, 2014.
Thorndike, A. and Colony, R.: Sea ice motion in response to geostrophic
winds, J. Geophys. Res.-Oceans, 87, 5845–5852, 1982.
Tschudi, M., Stroeve, J., and Stewart, J.: Relating the age of Arctic sea
ice to its thickness, as measured during NASA's ICESat and IceBridge
campaigns, Remote Sensing, 8, 457, https://doi.org/10.3390/rs8060457, 2016.
Tschudi, M., Meier, W. N., Stewart, J. S., Fowler, C., and Maslanik., J.:
Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 4,
NASA National Snow and Ice Data Center Distributed
Active Archive Center, Boulder, Colorado USA [data set], https://doi.org/10.5067/INAWUWO7QH7B, 2019.
Vázquez, M., Nieto, R., Drumond, A., and Gimeno, L.: Moisture transport
into the Arctic: Source-receptor relationships and the roles of atmospheric
circulation and evaporation, J. Geophys. Res.-Atmos.,
121, 13493–13509, https://doi.org/10.1002/2016JD025400, 2016.
Vázquez, M., Nieto, R., Drumond, A., and Gimeno, L.: Extreme Sea Ice
Loss over the Arctic: An Analysis Based on Anomalous Moisture Transport,
Atmosphere, 8, 32, https://doi.org/10.3390/atmos8020032, 2017.
Vihma, T., Screen, J., Tjernström, M., Newton, B., Zhang, X., Popova,
V., Deser, C., Holland, M., and Prowse, T.: The atmospheric role in the
Arctic water cycle: A review on processes, past and future changes, and
their impacts, J. Geophys. Res.-Biogeo.,
121, 586–620, 2016.
Villamil-Otero, G. A., Zhang, J., He, J., and Zhang, X.: Role of
extratropical cyclones in the recently observed increase in poleward
moisture transport into the Arctic Ocean, Adv. Atmos. Sci.,
35, 85–94, 2018.
Wang, J., Zhang, J., Watanabe, E., Ikeda, M., Mizobata, K., Walsh, J. E.,
Bai, X., and Wu, B.: Is the Dipole Anomaly a major driver to record lows in
Arctic summer sea ice extent?, Geophys. Res. Lett., 36, L05706,
https://doi.org/10.1029/2008gl036706, 2009.
Wang, X., Key, J., Kwok, R., and Zhang, J.: Comparison of Arctic sea ice
thickness from satellites, aircraft, and PIOMAS data, Remote Sensing, 8,
713, https://doi.org/10.3390/rs8090713, 2016.
Wang, X. L., Swail, V. R., and Zwiers, F. W.: Climatology and changes of
extratropical cyclone activity: Comparison of ERA-40 with NCEP–NCAR
reanalysis for 1958–2001, J. Climate, 19, 3145–3166, 2006.
Wang, X. L., Feng, Y., Compo, G., Swail, V., Zwiers, F., Allan, R., and
Sardeshmukh, P.: Trends and low frequency variability of extra-tropical
cyclone activity in the ensemble of twentieth century reanalysis, Clim.
Dynam., 40, 2775–2800, 2013.
Wang, Y., Bi, H., Huang, H., Liu, Y., Liu, Y., Liang, X., Fu, M., and Zhang,
Z.: Satellite-observed trends in the Arctic sea ice concentration for the
period 1979–2016, Journal of Oceanology & Limnology, 37, 18–37, 2019.
Warner, J., Screen, J., and Scaife, A.: Links Between Barents-Kara Sea Ice and the Extratropical Atmospheric Circulation Explained by Internal Variability and Tropical Forcing, Geophys. Res. Lett., 47,
e2019GL085679, https://doi.org/10.1029/2019GL085679, 2020.
Wernli, H. and Papritz, L.: Role of polar anticyclones and mid-latitude
cyclones for Arctic summertime sea-ice melting, Nat. Geosci., 11,
108–113, 2018.
Wu, B. Y., Wang, J., and Walsh, J. E.: Dipole anomaly in the winter Arctic
atmosphere and its association with sea ice motion, J. Climate, 19,
210–225, https://doi.org/10.1175/Jcli3619.1, 2006.
Yin, J. H.: A consistent poleward shift of the storm tracks in simulations
of 21st century climate, Geophys. Res. Lett., 32, L18701,
https://doi.org/10.1029/2005gl023684, 2005.
Zhang, J. and Rothrock, D.: Modeling global sea ice with a thickness and
enthalpy distribution model in generalized curvilinear coordinates, Mon.
Weather Rev., 131, 845–861, 2003.
Zhang, J., Lindsay, R., Schweiger, A., and Steele, M.: The impact of an
intense summer cyclone on 2012 Arctic sea ice retreat, Geophys. Res.
Lett., 40, 720–726, https://doi.org/10.1002/grl.50190, 2013.
Zhang, R.: Mechanisms for low-frequency variability of summer Arctic sea ice
extent, P. Natl. Acad. Sci. USA, 112, 4570–4575,
2015.
Zhang, X., Walsh, J. E., Zhang, J., Bhatt, U. S., and Ikeda, M.: Climatology
and interannual variability of arctic cyclone activity: 1948–2002, J. Climate, 17, 2300–2317, https://doi.org/10.1175/1520-0442(2004)017<2300:Caivoa>2.0.Co;2, 2004.
Zhang, X., He, J., Zhang, J., Polyakov, I., Gerdes, R., Inoue, J., and Wu,
P.: Enhanced poleward moisture transport and amplified northern
high-latitude wetting trend, Nat. Clim. Change, 3, 47–51, 2013.
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.
A record minimum July sea ice extent, since 1979, was observed in 2020. Our results reveal that...
