Articles | Volume 16, issue 7
https://doi.org/10.5194/tc-16-2745-2022
© Author(s) 2022. 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-16-2745-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jul 2022
Research article |
| 14 Jul 2022
| 14 Jul 2022
Contribution of ground ice melting to the expansion of Selin Co (lake) on the Tibetan Plateau
Lingxiao Wang
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Huayun Zhou
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
University of the Chinese Academy of Sciences, Beijing 100049, China
Shibo Liu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
University of the Chinese Academy of Sciences, Beijing 100049, China
Erji Du
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Guangyue Liu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Yao Xiao
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Guojie Hu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Chong Wang
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Zhe Sun
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Zhibin Li
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Yongping Qiao
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Tonghua Wu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Chengye Li
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Xubing Li
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
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Discipline: Frozen ground | Subject: Remote Sensing
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Maria Shaposhnikova, Claude Duguay, and Pascale Roy-Léveillée
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Aldo Bertone, Chloé Barboux, Xavier Bodin, Tobias Bolch, Francesco Brardinoni, Rafael Caduff, Hanne H. Christiansen, Margaret M. Darrow, Reynald Delaloye, Bernd Etzelmüller, Ole Humlum, Christophe Lambiel, Karianne S. Lilleøren, Volkmar Mair, Gabriel Pellegrinon, Line Rouyet, Lucas Ruiz, and Tazio Strozzi
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Andreas Kääb, Tazio Strozzi, Tobias Bolch, Rafael Caduff, Håkon Trefall, Markus Stoffel, and Alexander Kokarev
The Cryosphere, 15, 927–949, https://doi.org/10.5194/tc-15-927-2021, https://doi.org/10.5194/tc-15-927-2021, 2021
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We present a map of rock glacier motion over parts of the northern Tien Shan and time series of surface speed for six of them over almost 70 years.
This is by far the most detailed investigation of this kind available for central Asia.
We detect a 2- to 4-fold increase in rock glacier motion between the 1950s and present, which we attribute to atmospheric warming.
Relative to the shrinking glaciers in the region, this implies increased importance of periglacial sediment transport.
Ingmar Nitze, Sarah W. Cooley, Claude R. Duguay, Benjamin M. Jones, and Guido Grosse
The Cryosphere, 14, 4279–4297, https://doi.org/10.5194/tc-14-4279-2020, https://doi.org/10.5194/tc-14-4279-2020, 2020
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In summer 2018, northwestern Alaska was affected by widespread lake drainage which strongly exceeded previous observations. We analyzed the spatial and temporal patterns with remote sensing observations, weather data and lake-ice simulations. The preceding fall and winter season was the second warmest and wettest on record, causing the destabilization of permafrost and elevated water levels which likely led to widespread and rapid lake drainage during or right after ice breakup.
Jiahua Zhang, Lin Liu, and Yufeng Hu
The Cryosphere, 14, 1875–1888, https://doi.org/10.5194/tc-14-1875-2020, https://doi.org/10.5194/tc-14-1875-2020, 2020
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Ground surface in permafrost areas undergoes uplift and subsides seasonally due to freezing–thawing active layer. Surface elevation change serves as an indicator of frozen-ground dynamics. In this study, we identify 12 GPS stations across the Canadian Arctic, which are useful for measuring elevation changes by using reflected GPS signals. Measurements span from several years to over a decade and at daily intervals and help to reveal frozen ground dynamics at various temporal and spatial scales.
Eike Reinosch, Johannes Buckel, Jie Dong, Markus Gerke, Jussi Baade, and Björn Riedel
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In this research we present the results of our satellite analysis of a permafrost landscape and periglacial landforms in mountainous regions on the Tibetan Plateau. We study seasonal and multiannual surface displacement processes, such as the freezing and thawing of the ground, seasonally accelerated sliding on steep slopes, and continuous permafrost creep. This study is the first step of our goal to create an inventory of actively moving landforms within the Nyainqêntanglha range.
Andrew M. Cunliffe, George Tanski, Boris Radosavljevic, William F. Palmer, Torsten Sachs, Hugues Lantuit, Jeffrey T. Kerby, and Isla H. Myers-Smith
The Cryosphere, 13, 1513–1528, https://doi.org/10.5194/tc-13-1513-2019, https://doi.org/10.5194/tc-13-1513-2019, 2019
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Episodic changes of permafrost coastlines are poorly understood in the Arctic. By using drones, satellite images, and historic photos we surveyed a permafrost coastline on Qikiqtaruk – Herschel Island. We observed short-term coastline retreat of 14.5 m per year (2016–2017), exceeding long-term average rates of 2.2 m per year (1952–2017). Our study highlights the value of these tools to assess understudied episodic changes of eroding permafrost coastlines in the context of a warming Arctic.
Charles J. Abolt, Michael H. Young, Adam L. Atchley, and Cathy J. Wilson
The Cryosphere, 13, 237–245, https://doi.org/10.5194/tc-13-237-2019, https://doi.org/10.5194/tc-13-237-2019, 2019
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We present a workflow that uses a machine-learning algorithm known as a convolutional neural network (CNN) to rapidly delineate ice wedge polygons in high-resolution topographic datasets. Our workflow permits thorough assessments of polygonal microtopography at the kilometer scale or greater, which can improve understanding of landscape hydrology and carbon budgets. We demonstrate that a single CNN can be trained to delineate polygons with high accuracy in diverse tundra settings.
Yonghong Yi, John S. Kimball, Richard H. Chen, Mahta Moghaddam, and Charles E. Miller
The Cryosphere, 13, 197–218, https://doi.org/10.5194/tc-13-197-2019, https://doi.org/10.5194/tc-13-197-2019, 2019
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To better understand active-layer freezing process and its climate sensitivity, we developed a new 1 km snow data set for permafrost modeling and used the model simulations with multiple new in situ and P-band radar data sets to characterize the soil freeze onset and duration of zero curtain in Arctic Alaska. Results show that zero curtains of upper soils are primarily affected by early snow cover accumulation, while zero curtains of deeper soils are more closely related to maximum thaw depth.
Claire Bernard-Grand'Maison and Wayne Pollard
The Cryosphere, 12, 3589–3604, https://doi.org/10.5194/tc-12-3589-2018, https://doi.org/10.5194/tc-12-3589-2018, 2018
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This study provides a first approximation of the volume of ice in ice wedges, a ground-ice feature in permafrost for a High Arctic polar desert region. We demonstrate that Geographical Information System analyses can be used on satellite images to estimate ice wedge volume. We estimate that 3.81 % of the top 5.9 m of permafrost could be ice-wedge ice on the Fosheim Peninsula. In response to climate change, melting ice wedges will result in widespread terrain disturbance in this region.
Cited articles
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Short summary
Selin Co has exhibited the greatest increase in water storage among all the lakes on the Tibetan Plateau in the past decades. This study presents the first attempt to quantify the water contribution of ground ice melting to the expansion of Selin Co by evaluating the ground surface deformation since terrain surface settlement provides a
windowto detect the subsurface ground ice melting. Results reveal that ground ice meltwater contributed ~ 12 % of the lake volume increase during 2017–2020.
Selin Co has exhibited the greatest increase in water storage among all the lakes on the Tibetan...
