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.
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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Jianting Zhao, Lin Zhao, Zhe Sun, Fujun Niu, Guojie Hu, Defu Zou, Guangyue Liu, Erji Du, Chong Wang, Lingxiao Wang, Yongping Qiao, Jianzong Shi, Yuxin Zhang, Junqiang Gao, Yuanwei Wang, Yan Li, Wenjun Yu, Huayun Zhou, Zanpin Xing, Minxuan Xiao, Luhui Yin, and Shengfeng Wang
The Cryosphere, 16, 4823–4846, https://doi.org/10.5194/tc-16-4823-2022, https://doi.org/10.5194/tc-16-4823-2022, 2022
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Permafrost has been warming and thawing globally; this is especially true in boundary regions. We focus on the changes and variability in permafrost distribution and thermal dynamics in the northern limit of permafrost on the Qinghai–Tibet Plateau (QTP) by applying a new permafrost model. Unlike previous papers on this topic, our findings highlight a slow, decaying process in the response of permafrost in the QTP to a warming climate, especially regarding areal extent.
Lu Gao, Jianhui Wei, Lingxiao Wang, Matthias Bernhardt, Karsten Schulz, and Xingwei Chen
Earth Syst. Sci. Data, 10, 2097–2114, https://doi.org/10.5194/essd-10-2097-2018, https://doi.org/10.5194/essd-10-2097-2018, 2018
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High-resolution temperature data sets are important for the Chinese Tian Shan, which has a complex ecological environment system. This study presents a unique high-resolution (1 km, 6-hourly) air temperature data set for this area from 1979 to 2016 based on a robust statistical downscaling framework. The strongest advantage of this method is its independence of local meteorological stations due to a model internal, vertical lapse rate scheme. This method was validated for other mountains.
Defu Zou, Lin Zhao, Guojie Hu, Erji Du, Guangyue Liu, Chong Wang, and Wangping Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-114, https://doi.org/10.5194/essd-2024-114, 2024
Revised manuscript under review for ESSD
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This study provides a baseline data of permafrost temperature at 15 meters depth in the Qinghai-Tibet Plateau (QTP) over the period 2010–2019 at a spatial resolution of nearly 1 km, using 231 borehole records and a machine learning method. The average MAGT15m of the QTP permafrost was -1.85 °C, with 90% of values ranging from -5.1 °C to -0.1 °C and 51.2% exceeding -1.5 °C. The data can serve as a crucial boundary condition for deeper permafrost assessments and a reference for model simulations.
Francisco José Cuesta-Valero, Hugo Beltrami, Almudena García-García, Gerhard Krinner, Moritz Langer, Andrew H. MacDougall, Jan Nitzbon, Jian Peng, Karina von Schuckmann, Sonia I. Seneviratne, Wim Thiery, Inne Vanderkelen, and Tonghua Wu
Earth Syst. Dynam., 14, 609–627, https://doi.org/10.5194/esd-14-609-2023, https://doi.org/10.5194/esd-14-609-2023, 2023
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Climate change is caused by the accumulated heat in the Earth system, with the land storing the second largest amount of this extra heat. Here, new estimates of continental heat storage are obtained, including changes in inland-water heat storage and permafrost heat storage in addition to changes in ground heat storage. We also argue that heat gains in all three components should be monitored independently of their magnitude due to heat-dependent processes affecting society and ecosystems.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Jianting Zhao, Lin Zhao, Zhe Sun, Fujun Niu, Guojie Hu, Defu Zou, Guangyue Liu, Erji Du, Chong Wang, Lingxiao Wang, Yongping Qiao, Jianzong Shi, Yuxin Zhang, Junqiang Gao, Yuanwei Wang, Yan Li, Wenjun Yu, Huayun Zhou, Zanpin Xing, Minxuan Xiao, Luhui Yin, and Shengfeng Wang
The Cryosphere, 16, 4823–4846, https://doi.org/10.5194/tc-16-4823-2022, https://doi.org/10.5194/tc-16-4823-2022, 2022
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Permafrost has been warming and thawing globally; this is especially true in boundary regions. We focus on the changes and variability in permafrost distribution and thermal dynamics in the northern limit of permafrost on the Qinghai–Tibet Plateau (QTP) by applying a new permafrost model. Unlike previous papers on this topic, our findings highlight a slow, decaying process in the response of permafrost in the QTP to a warming climate, especially regarding areal extent.
Tonghua Wu, Changwei Xie, Xiaofan Zhu, Jie Chen, Wu Wang, Ren Li, Amin Wen, Dong Wang, Peiqing Lou, Chengpeng Shang, Yune La, Xianhua Wei, Xin Ma, Yongping Qiao, Xiaodong Wu, Qiangqiang Pang, and Guojie Hu
Earth Syst. Sci. Data, 14, 1257–1269, https://doi.org/10.5194/essd-14-1257-2022, https://doi.org/10.5194/essd-14-1257-2022, 2022
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We presented an 11-year time series of meteorological, active layer, and permafrost data at the Mahan Mountain relict permafrost site in northeastern Qinghai-Tibet Plateau. From 2010 to 2020, the increasing rate of active layer thickness was 1.8 cm-year and the permafrost temperature showed slight changes. The release of those data would be helpful to understand the impacts of climate change on permafrost in relict permafrost regions and to validate the permafrost models and land surface models.
Yi Zhao, Zhuotong Nan, Hailong Ji, and Lin Zhao
The Cryosphere, 16, 825–849, https://doi.org/10.5194/tc-16-825-2022, https://doi.org/10.5194/tc-16-825-2022, 2022
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Convective heat transfer (CHT) is important in affecting thermal regimes in permafrost regions. We quantified its thermal impacts by contrasting the simulation results from three scenarios in which the Simultaneous Heat and Water model includes full, partial, and no consideration of CHT. The results show the CHT commonly happens in shallow and middle soil depths during thawing periods and has greater impacts in spring than summer. The CHT has both heating and cooling effects on the active layer.
Xiaowen Wang, Lin Liu, Yan Hu, Tonghua Wu, Lin Zhao, Qiao Liu, Rui Zhang, Bo Zhang, and Guoxiang Liu
Nat. Hazards Earth Syst. Sci., 21, 2791–2810, https://doi.org/10.5194/nhess-21-2791-2021, https://doi.org/10.5194/nhess-21-2791-2021, 2021
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We characterized the multi-decadal geomorphic changes of a low-angle valley glacier in the East Kunlun Mountains and assessed the detachment hazard influence. The observations reveal a slow surge-like dynamic pattern of the glacier tongue. The maximum runout distances of two endmember avalanche scenarios were presented. This study provides a reference to evaluate the runout hazards of low-angle mountain glaciers prone to detachment.
Lin Zhao, Defu Zou, Guojie Hu, Tonghua Wu, Erji Du, Guangyue Liu, Yao Xiao, Ren Li, Qiangqiang Pang, Yongping Qiao, Xiaodong Wu, Zhe Sun, Zanpin Xing, Yu Sheng, Yonghua Zhao, Jianzong Shi, Changwei Xie, Lingxiao Wang, Chong Wang, and Guodong Cheng
Earth Syst. Sci. Data, 13, 4207–4218, https://doi.org/10.5194/essd-13-4207-2021, https://doi.org/10.5194/essd-13-4207-2021, 2021
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Lack of a synthesis dataset of the permafrost state has greatly limited our understanding of permafrost-related research as well as the calibration and validation of RS retrievals and model simulation. We compiled this dataset, including ground temperature, active layer hydrothermal regimes, and meteorological indexes based on our observational network, and we summarized the basic changes in permafrost and its climatic conditions. It is the first comprehensive dataset on permafrost for the QXP.
Lihui Luo, Yanli Zhuang, Mingyi Zhang, Zhongqiong Zhang, Wei Ma, Wenzhi Zhao, Lin Zhao, Li Wang, Yanmei Shi, Ze Zhang, Quntao Duan, Deyu Tian, and Qingguo Zhou
Earth Syst. Sci. Data, 13, 4035–4052, https://doi.org/10.5194/essd-13-4035-2021, https://doi.org/10.5194/essd-13-4035-2021, 2021
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We implement a variety of sensors to monitor the hydrological and thermal deformation between permafrost slopes and engineering projects in the hinterland of the Qinghai–Tibet Plateau. We present the integrated observation dataset from the 1950s to 2020, explaining the instrumentation, processing, data visualisation, and quality control.
Dong Wang, Tonghua Wu, Lin Zhao, Cuicui Mu, Ren Li, Xianhua Wei, Guojie Hu, Defu Zou, Xiaofan Zhu, Jie Chen, Junmin Hao, Jie Ni, Xiangfei Li, Wensi Ma, Amin Wen, Chengpeng Shang, Yune La, Xin Ma, and Xiaodong Wu
Earth Syst. Sci. Data, 13, 3453–3465, https://doi.org/10.5194/essd-13-3453-2021, https://doi.org/10.5194/essd-13-3453-2021, 2021
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The Third Pole regions are important components in the global permafrost, and the detailed spatial soil organic carbon data are the scientific basis for environmental protection as well as the development of Earth system models. Based on multiple environmental variables and soil profile data, this study use machine-learning approaches to evaluate the SOC storage and spatial distribution at a depth interval of 0–3 m in the frozen ground area of the Third Pole region.
Xiangfei Li, Tonghua Wu, Xiaodong Wu, Jie Chen, Xiaofan Zhu, Guojie Hu, Ren Li, Yongping Qiao, Cheng Yang, Junming Hao, Jie Ni, and Wensi Ma
Geosci. Model Dev., 14, 1753–1771, https://doi.org/10.5194/gmd-14-1753-2021, https://doi.org/10.5194/gmd-14-1753-2021, 2021
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In this study, an ensemble simulation of 55296 scheme combinations for at a typical permafrost site on the Qinghai–Tibet Plateau (QTP) was conducted. The general performance of the Noah-MP model for snow cover events (SCEs), soil temperature (ST) and soil liquid water content (SLW) was assessed, and the sensitivities of parameterization schemes at different depths were investigated. We show that Noah-MP tends to overestimate SCEs and underestimate ST and topsoil SLW on the QTP.
Lu Gao, Jianhui Wei, Lingxiao Wang, Matthias Bernhardt, Karsten Schulz, and Xingwei Chen
Earth Syst. Sci. Data, 10, 2097–2114, https://doi.org/10.5194/essd-10-2097-2018, https://doi.org/10.5194/essd-10-2097-2018, 2018
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High-resolution temperature data sets are important for the Chinese Tian Shan, which has a complex ecological environment system. This study presents a unique high-resolution (1 km, 6-hourly) air temperature data set for this area from 1979 to 2016 based on a robust statistical downscaling framework. The strongest advantage of this method is its independence of local meteorological stations due to a model internal, vertical lapse rate scheme. This method was validated for other mountains.
Defu Zou, Lin Zhao, Yu Sheng, Ji Chen, Guojie Hu, Tonghua Wu, Jichun Wu, Changwei Xie, Xiaodong Wu, Qiangqiang Pang, Wu Wang, Erji Du, Wangping Li, Guangyue Liu, Jing Li, Yanhui Qin, Yongping Qiao, Zhiwei Wang, Jianzong Shi, and Guodong Cheng
The Cryosphere, 11, 2527–2542, https://doi.org/10.5194/tc-11-2527-2017, https://doi.org/10.5194/tc-11-2527-2017, 2017
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The area and distribution of permafrost on the Tibetan Plateau are unclear and controversial. This paper generated a benchmark map based on the modified remote sensing products and validated it using ground-based data sets. Compared with two existing maps, the new map performed better and showed that permafrost covered areas of 1.06 × 106 km2. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.
Xiaowen Wang, Lin Liu, Lin Zhao, Tonghua Wu, Zhongqin Li, and Guoxiang Liu
The Cryosphere, 11, 997–1014, https://doi.org/10.5194/tc-11-997-2017, https://doi.org/10.5194/tc-11-997-2017, 2017
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Rock glaciers are abundant in high mountains in western China but have been ignored for 20 years. We used a new remote-sensing-based method to map active rock glaciers in the Chinese part of the Tien Shan and compiled an inventory of 261 active rock glaciers and included quantitative information about their locations, geomorphic parameters, and downslope velocities. Our dataset suggests that the lower limit of permafrost there is 2500–2800 m.
Related subject area
Discipline: Frozen ground | Subject: Remote Sensing
Toward long-term monitoring of regional permafrost thaw with satellite interferometric synthetic aperture radar
Landcover succession for recently drained lakes in permafrost on the Yamal peninsula, Western Siberia
Multitemporal UAV LiDAR detects seasonal heave and subsidence on palsas
Allometric scaling of retrogressive thaw slumps
Brief communication: Identification of tundra topsoil frozen/thawed state from SMAP and GCOM-W1 radiometer measurements using the spectral gradient method
Bedfast and floating-ice dynamics of thermokarst lakes using a temporal deep-learning mapping approach: case study of the Old Crow Flats, Yukon, Canada
Incorporating InSAR kinematics into rock glacier inventories: insights from 11 regions worldwide
Assessing volumetric change distributions and scaling relations of retrogressive thaw slumps across the Arctic
Top-of-permafrost ground ice indicated by remotely sensed late-season subsidence
Inventory and changes of rock glacier creep speeds in Ile Alatau and Kungöy Ala-Too, northern Tien Shan, since the 1950s
The catastrophic thermokarst lake drainage events of 2018 in northwestern Alaska: fast-forward into the future
Global Positioning System interferometric reflectometry (GPS-IR) measurements of ground surface elevation changes in permafrost areas in northern Canada
InSAR time series analysis of seasonal surface displacement dynamics on the Tibetan Plateau
Rapid retreat of permafrost coastline observed with aerial drone photogrammetry
Brief communication: Rapid machine-learning-based extraction and measurement of ice wedge polygons in high-resolution digital elevation models
Sensitivity of active-layer freezing process to snow cover in Arctic Alaska
An estimate of ice wedge volume for a High Arctic polar desert environment, Fosheim Peninsula, Ellesmere Island
Taha Sadeghi Chorsi, Franz J. Meyer, and Timothy H. Dixon
The Cryosphere, 18, 3723–3740, https://doi.org/10.5194/tc-18-3723-2024, https://doi.org/10.5194/tc-18-3723-2024, 2024
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The active layer thaws and freezes seasonally. The annual freeze–thaw cycle of the active layer causes significant surface height changes due to the volume difference between ice and liquid water. We estimate the subsidence rate and active-layer thickness (ALT) for part of northern Alaska for summer 2017 to 2022 using interferometric synthetic aperture radar and lidar. ALT estimates range from ~20 cm to larger than 150 cm in area. Subsidence rate varies between close points (2–18 mm per month).
Clemens von Baeckmann, Annett Bartsch, Helena Bergstedt, Aleksandra Efimova, Barbara Widhalm, Dorothee Ehrich, Timo Kumpula, Alexander Sokolov, and Svetlana Abdulmanova
EGUsphere, https://doi.org/10.5194/egusphere-2024-699, https://doi.org/10.5194/egusphere-2024-699, 2024
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Lakes are common features in Arctic permafrost areas. Landcover change following their drainage needs to be monitored since it has implications for ecology and the carbon cycle. Satellite data are key in this context. We compared a common vegetation index approach with a novel landcover monitoring scheme. Landcover information provides specifically information on wetland features. We also showed that the bioclimatic gradients play a significant role after drainage within the first 10 years.
Cas Renette, Mats Olvmo, Sofia Thorsson, Björn Holmer, and Heather Reese
EGUsphere, https://doi.org/10.5194/egusphere-2024-141, https://doi.org/10.5194/egusphere-2024-141, 2024
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We used a drone to monitor seasonal changes in the height of subarctic permafrost mounds (palsas). With five drone flights in one year, we found a seasonal fluctuation of ca. 15 cm as result of freeze/thaw cycles. On one mound, a large area sank down between each flight as a result of permafrost thaw. The approach of using repeated high-resolution scans from such drone is unique for such environments and highlights its effectiveness in capturing the subtle dynamics of permafrost landscapes.
Jurjen van der Sluijs, Steven V. Kokelj, and Jon F. Tunnicliffe
The Cryosphere, 17, 4511–4533, https://doi.org/10.5194/tc-17-4511-2023, https://doi.org/10.5194/tc-17-4511-2023, 2023
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There is an urgent need to obtain size and erosion estimates of climate-driven landslides, such as retrogressive thaw slumps. We evaluated surface interpolation techniques to estimate slump erosional volumes and developed a new inventory method by which the size and activity of these landslides are tracked through time. Models between slump area and volume reveal non-linear intensification, whereby model coefficients improve our understanding of how permafrost landscapes may evolve over time.
Konstantin Muzalevskiy, Zdenek Ruzicka, Alexandre Roy, Michael Loranty, and Alexander Vasiliev
The Cryosphere, 17, 4155–4164, https://doi.org/10.5194/tc-17-4155-2023, https://doi.org/10.5194/tc-17-4155-2023, 2023
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A new all-weather method for determining the frozen/thawed (FT) state of soils in the Arctic region based on satellite data was proposed. The method is based on multifrequency measurement of brightness temperatures by the SMAP and GCOM-W1/AMSR2 satellites. The created method was tested at sites in Canada, Finland, Russia, and the USA, based on climatic weather station data. The proposed method identifies the FT state of Arctic soils with better accuracy than existing methods.
Maria Shaposhnikova, Claude Duguay, and Pascale Roy-Léveillée
The Cryosphere, 17, 1697–1721, https://doi.org/10.5194/tc-17-1697-2023, https://doi.org/10.5194/tc-17-1697-2023, 2023
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We explore lake ice in the Old Crow Flats, Yukon, Canada, using a novel approach that employs radar imagery and deep learning. Results indicate an 11 % increase in the fraction of lake ice that grounds between 1992/1993 and 2020/2021. We believe this is caused by widespread lake drainage and fluctuations in water level and snow depth. This transition is likely to have implications for permafrost beneath the lakes, with a potential impact on methane ebullition and the regional carbon budget.
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
The Cryosphere, 16, 2769–2792, https://doi.org/10.5194/tc-16-2769-2022, https://doi.org/10.5194/tc-16-2769-2022, 2022
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We present the guidelines developed by the IPA Action Group and within the ESA Permafrost CCI project to include InSAR-based kinematic information in rock glacier inventories. Nine operators applied these guidelines to 11 regions worldwide; more than 3600 rock glaciers are classified according to their kinematics. We test and demonstrate the feasibility of applying common rules to produce homogeneous kinematic inventories at global scale, useful for hydrological and climate change purposes.
Philipp Bernhard, Simon Zwieback, Nora Bergner, and Irena Hajnsek
The Cryosphere, 16, 1–15, https://doi.org/10.5194/tc-16-1-2022, https://doi.org/10.5194/tc-16-1-2022, 2022
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We present an investigation of retrogressive thaw slumps in 10 study sites across the Arctic. These slumps have major impacts on hydrology and ecosystems and can also reinforce climate change by the mobilization of carbon. Using time series of digital elevation models, we found that thaw slump change rates follow a specific type of distribution that is known from landslides in more temperate landscapes and that the 2D area change is strongly related to the 3D volumetric change.
Simon Zwieback and Franz J. Meyer
The Cryosphere, 15, 2041–2055, https://doi.org/10.5194/tc-15-2041-2021, https://doi.org/10.5194/tc-15-2041-2021, 2021
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Thawing of ice-rich permafrost leads to subsidence and slumping, which can compromise Arctic infrastructure. However, we lack fine-scale maps of permafrost ground ice, chiefly because it is usually invisible at the surface. We show that subsidence at the end of summer serves as a
fingerprintwith which near-surface permafrost ground ice can be identified. As this can be done with satellite data, this method may help improve ground ice maps and thus sustainably steward the Arctic.
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
The Cryosphere, 14, 1633–1650, https://doi.org/10.5194/tc-14-1633-2020, https://doi.org/10.5194/tc-14-1633-2020, 2020
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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
Bense, V., Kooi, H., Ferguson, G., and Read, T.: Permafrost degradation as a
control on hydrogeological regime shifts in a warming climate, J.
Geophys. Res.-Earth Surf., 117, F03036, https://doi.org/10.1029/2011JF002143, 2012.
Berardino, P., Fornaro, G., Lanari, R., and Sansosti, E.: A new algorithm
for surface deformation monitoring based on small baseline differential SAR
interferograms, Geoscience and Remote Sensing, IEEE Transactions on, 40,
2375–2383, 2002.
Bian, D., Bian, B., La, B., Wang, C., and Chen, T.: The Response of Water
Level of Selin Co to Climate Change during 1975–2008, Acta
Geographica Sinica, 65, 313–319, 2010 (in Chinese).
Brun, F., Treichler, D., Shean, D., and Immerzeel, W. W.: Limited
contribution of glacier mass loss to the recent increase in Tibetan Plateau
lake volume, Front. Earth Sci., 8, 582060, https://doi.org/10.3389/feart.2020.582060, 2020.
Buckel, J., Reinosch, E., Hördt, A., Zhang, F., Riedel, B., Gerke, M., Schwalb, A., and Mäusbacher, R.: Insights into a remote cryosphere: a multi-method approach to assess permafrost occurrence at the Qugaqie basin, western Nyainqêntanglha Range, Tibetan Plateau, The Cryosphere, 15, 149–168, https://doi.org/10.5194/tc-15-149-2021, 2021.
Chen, C. W. and Zebker, H. A.: Phase unwrapping for large SAR
interferograms: Statistical segmentation and generalized network models,
IEEE T. Geosci. Remote, 40, 1709–1719, 2002.
Chen, J., Liu, L., Zhang, T., Cao, B., and Lin, H.: Using persistent
scatterer interferometry to map and quantify permafrost thaw subsidence: A
case study of Eboling Mountain on the Qinghai–Tibet Plateau, J.
Geophys. Res.-Earth Surf., 123, 2663–2676, 2018.
Chen, J., Wu, Y., O'Connor, M., Cardenas, M. B., Schaefer, K., Michaelides,
R., and Kling, G.: Active layer freeze-thaw and water storage dynamics in
permafrost environments inferred from InSAR, Remote Sens. Environ.,
248, 112007, https://doi.org/10.1016/j.rse.2020.112007, 2020.
Chen, J., Wu, T., Zou, D., Liu, L., Wu, X., Gong, W., Zhu, X., Li, R., Hao,
J., and Hu, G.: Magnitudes and patterns of large-scale permafrost ground
deformation revealed by Sentinel-1 InSAR on the central Qinghai-Tibet
Plateau, Remote Sens. Environ., 268, 112778, https://doi.org/10.1016/j.rse.2021.112778, 2022.
Cheng, G.: The mechanism of repeated-segregation for the formation of thick
layered ground ice, Cold Reg. Sci. Technol., 8, 57–66, 1983.
Daout, S., Doin, M. P., Peltzer, G., Socquet, A., and Lasserre, C.:
Large-scale InSAR monitoring of permafrost freeze–thaw cycles on the
Tibetan Plateau, Geophys. Res. Lett., 44, 901–909, 2017.
Daout, S., Dini, B., Haeberli, W., Doin, M.-P., and Parsons, B.: Ice loss in
the Northeastern Tibetan Plateau permafrost as seen by 16 yr of ESA SAR
missions, Earth Planet. Sc. Lett., 545, 116404, https://doi.org/10.1016/j.epsl.2020.116404, 2020.
Deij, Y., Nima, J., Qianba, O., Zeng, L., and Luosang, Q.: Lake Area
Variation of Selin Tso in 1975–2016 and Its Influential Factors, Plateau
and Mountain Meteorology Research, 38, 35–41, https://doi.org/10.3969/j.issn.1674-2184.2018.02.006, 2018 (in Chinese).
Doin, M. P., Twardzik, C., Ducret, G., Lasserre, C., Guillaso, S., and
Jianbao, S.: InSAR measurement of the deformation around Siling Co Lake:
Inferences on the lower crust viscosity in central Tibet, J.
Geophys. Res.-Sol. Ea., 120, 5290–5310, 2015.
Farinotti, D., Huss, M., Fürst, J. J., Landmann, J., Machguth, H.,
Maussion, F., and Pandit, A.: A consensus estimate for the ice thickness
distribution of all glaciers on Earth, Nat. Geosci., 12, 168–173, 2019.
French, H. and Harbor, J.: The Development and History of Glacial and
Periglacial Geomorphology, Treatise on Geomorphology, Academic Press,
https://doi.org/10.1016/B978-0-12-374739-6.00190-1, 2013.
French, H. M.: The periglacial environment, John Wiley & Sons, ISBN 978-1-119-13278-3, 2017.
Günther, F., Overduin, P. P., Yakshina, I. A., Opel, T., Baranskaya, A. V., and Grigoriev, M. N.: Observing Muostakh disappear: permafrost thaw subsidence and erosion of a ground-ice-rich island in response to arctic summer warming and sea ice reduction, The Cryosphere, 9, 151–178, https://doi.org/10.5194/tc-9-151-2015, 2015.
Guo, W., Liu, S., Xu, J., Wu, L., Shangguan, D., Yao, X., Wei, J., Bao, W.,
Yu, P., and Liu, Q.: The second Chinese glacier inventory: data, methods and
results, J. Glaciol., 61, 357–372, 2015.
Guo, Y., Zhang, Y., Ma, N., Xu, J., and Zhang, T.: Long-term changes in
evaporation over Siling Co Lake on the Tibetan Plateau and its impact on
recent rapid lake expansion, Atmos. Res., 216, 141–150, 2019.
Hwang, C.-W., Cheng, Y. S., Yang, W. H., Zhang, G., Huang, Y. R., Shen, W.
B., and Pan, Y.: Lake level changes in the Tibetan Plateau from Cryosat-2,
SARAL, ICESat, and Jason-2 altimeters, Terr. Atmos. Ocean. Sci., 30, 1–18,
2019.
Jin, H., Huang, Y., Bense, V. F., Ma, Q., Marchenko, S. S., Shepelev, V. V.,
Hu, Y., Liang, S., Spektor, V. V., and Jin, X.: Permafrost Degradation and
Its Hydrogeological Impacts, Water, 14, 372, https://doi.org/10.3390/w14030372, 2022.
Jolivet, R., Agram, P. S., Lin, N. Y., Simons, M., Doin, M. P., Peltzer, G.,
and Li, Z.: Improving InSAR geodesy using global atmospheric models, J. Geophys. Res.-Sol. Ea., 119, 2324–2341, 2014.
Kokelj, S. V. and Jorgenson, M.: Advances in thermokarst research,
Permafrost Periglac. Process., 24, 108–119, 2013.
Lanari, R., Lundgren, P., Manzo, M., and Casu, F.: Satellite radar
interferometry time series analysis of surface deformation for Los Angeles,
California, Geophys. Res. Lett., 31, L23613, https://doi.org/10.1029/2004GL021294, 2004.
Lantuit, H. and Pollard, W.: Fifty years of coastal erosion and
retrogressive thaw slump activity on Herschel Island, southern Beaufort Sea,
Yukon Territory, Canada, Geomorphology, 95, 84–102, 2008.
Lei, Y., Yao, T., Bird, B. W., Yang, K., Zhai, J., and Sheng, Y.: Coherent
lake growth on the central Tibetan Plateau since the 1970s: Characterization
and attribution, J. Hydrol., 483, 61–67, 2013.
Lei, Y., Yang, K., Wang, B., Sheng, Y., Bird, B. W., Zhang, G., and Tian,
L.: Response of inland lake dynamics over the Tibetan Plateau to climate
change, Clim. Change, 125, 281–290, 2014.
Li, X., Long, D., Huang, Q., Han, P., Zhao, F., and Wada, Y.: High-temporal-resolution water level and storage change data sets for lakes on the Tibetan Plateau during 2000–2017 using multiple altimetric missions and Landsat-derived lake shoreline positions, Earth Syst. Sci. Data, 11, 1603–1627, https://doi.org/10.5194/essd-11-1603-2019, 2019.
Li, Y., Liao, J., Guo, H., Liu, Z., and Shen, G.: Patterns and potential
drivers of dramatic changes in Tibetan lakes, 1972–2010, PloS one, 9,
e111890, https://doi.org/10.1371/journal.pone.0111890, 2014.
Li, Z., Zhao, R., Hu, J., Wen, L., Feng, G., Zhang, Z., and Wang, Q.: InSAR
analysis of surface deformation over permafrost to estimate active layer
thickness based on one-dimensional heat transfer model of soils, Sci.
Rep.-UK, 5, 15542, https://doi.org/10.1038/srep15542, 2015.
Liu, L., Schaefer, K., Zhang, T., and Wahr, J.: Estimating 1992–2000
average active layer thickness on the Alaskan North Slope from remotely
sensed surface subsidence, J. Geophys. Res.-Earth Surf.,
117, F01005, https://doi.org/10.1029/2011JF002041, 2012a.
Liu, S., Guo, W., and Xu, J.: The second glacier inventory dataset of China
(version 1.0) (2006–2011), TPDC [data set], https://doi.org/10.3972/glacier.001.2013.db, 2012b.
Lu, P., Han, J., Li, Z., Xu, R., Li, R., Hao, T., and Qiao, G.: Lake
outburst accelerated permafrost degradation on Qinghai-Tibet Plateau, Remote
Sens. Environ., 249, 112011, https://doi.org/10.1016/j.rse.2020.112011, 2020.
Ma, Q., Jin, H.-J., Bense, V. F., Dong-Liang, L., Marchenko, S. S., Harris,
S. A., and Lan, Y.-C.: Impacts of degrading permafrost on streamflow in the
source area of Yellow River on the Qinghai-Tibet Plateau, China, Adv.
Clim. Change Res., 10, 225–239, https://doi.org/10.1016/j.accre.2020.02.001, 2020.
Mackay, J. R.: Downward water movement into frozen ground, western arctic
coast, Canada, Can. J. Earth Sci., 20, 120–134, 1983.
Meng, K., Shi, X., Wang, E., and Liu, F.: High-altitude salt lake elevation
changes and glacial ablation in Central Tibet, 2000–2010, Chinese Sci.
B., 57, 525–534, 2012.
Pepe, A. and Lanari, R.: On the extension of the minimum cost flow algorithm
for phase unwrapping of multitemporal differential SAR interferograms, IEEE
T. Geosci. Remote, 44, 2374–2383, 2006.
Qiao, B., Zhu, L., and Yang, R.: Temporal-spatial differences in lake water
storage changes and their links to climate change throughout the Tibetan
Plateau, Remote Sens. Environ., 222, 232–243, 2019.
Reinosch, E., Buckel, J., Dong, J., Gerke, M., Baade, J., and Riedel, B.: InSAR time series analysis of seasonal surface displacement dynamics on the Tibetan Plateau, The Cryosphere, 14, 1633–1650, https://doi.org/10.5194/tc-14-1633-2020, 2020.
Shiklomanov, N. I., Streletskiy, D. A., Little, J. D., and Nelson, F. E.:
Isotropic thaw subsidence in undisturbed permafrost landscapes, Geophys.
Res. Lett., 40, 6356–6361, 2013.
Song, C., Huang, B., Richards, K., Ke, L., and Hien Phan, V.: Accelerated
lake expansion on the Tibetan Plateau in the 2000s: Induced by glacial
melting or other processes?, Water Resour. Res., 50, 3170–3186, 2014.
Streletskiy, D. A., Shiklomanov, N. I., Little, J. D., Nelson, F. E., Brown,
J., Nyland, K. E., and Klene, A. E.: Thaw subsidence in undisturbed tundra
landscapes, Barrow, Alaska, 1962–2015, Permafrost Periglac.
Process., 28, 566–572, 2016.
Sun, F., Ma, R., He, B., Zhao, X., Zeng, Y., Zhang, S., and Tang, S.:
Changing Patterns of Lakes on The Southern Tibetan Plateau Based on
Multi-Source Satellite Data, Remote Sensing, 12, 3450, https://doi.org/10.3390/rs12203450, 2020.
Tong, K., Su, F., and Xu, B.: Quantifying the contribution of glacier
meltwater in the expansion of the largest lake in Tibet, J.
Geophys. Res.-Atmos., 121, 11158–11173, https://doi.org/10.1002/2016JD025424, 2016.
Treichler, D., Kääb, A., Salzmann, N., and Xu, C.-Y.: Recent glacier and lake changes in High Mountain Asia and their relation to precipitation changes, The Cryosphere, 13, 2977–3005, https://doi.org/10.5194/tc-13-2977-2019, 2019.
Usai, S.: A least squares database approach for SAR interferometric data,
Geoscience and Remote Sensing, IEEE Transactions on, 41, 753–760, 2003.
Wu, Z., Zhao, L., Liu, L., Zhu, R., Gao, Z., Qiao, Y., Tian, L., Zhou, H.,
and Xie, M.: Surface-deformation monitoring in the permafrost regions over
the Tibetan Plateau, using Sentinel-1 data, Sci. Cold Arid
Reg., 10, 114–125, 2018.
Yang, Y., Wu, Q., Yun, H., Jin, H., and Zhang, Z.: Evaluation of the
hydrological contributions of permafrost to the thermokarst lakes on the
Qinghai–Tibet Plateau using stable isotopes, Global Planet. Change,
140, 1–8, 2016.
Yang, Y., Wu, Q., Jin, H., Wang, Q., Huang, Y., Luo, D., Gao, S., and Jin,
X.: Delineating the hydrological processes and hydraulic connectivities
under permafrost degradation on Northeastern Qinghai-Tibet Plateau, China,
J. Hydrol., 569, 359–372, 2019.
Zhang, G.: The lakes larger than 1 km2 in Tibetan Plateau (V3.0) (1970s–2021), National Tibetan Plateau Data Center [data set], https://doi.org/10.11888/Hydro.tpdc.270303, 2019.
Zhang, G., Yao, T., and Kang, S.: Water balance estimates of ten greatest
lakes in China using ICESat and Landsat data, Chin. Sci. Bull.,
58, 2664–2678, 2013 (in Chinese).
Zhang, G., Yao, T., Shum, C., Yi, S., Yang, K., Xie, H., Feng, W., Bolch,
T., Wang, L., and Behrangi, A.: Lake volume and groundwater storage
variations in Tibetan Plateau's endorheic basin, Geophys. Res.
Lett., 44, 5550–5560, 2017.
Zhang, G., Chen, W., and Xie, H.: Tibetan Plateau's lake level and volume
changes from NASA's ICESat/ICESat-2 and Landsat Missions, Geophys.
Res. Lett., 46, 13107–13118, 2019.
Zhang, G., Yao, T., Xie, H., Yang, K., Zhu, L., Shum, C., Bolch, T., Yi, S.,
Allen, S., and Jiang, L.: Response of Tibetan Plateau's lakes to climate
changes: trend, pattern, and mechanisms, Earth-Sci. Rev., 208, 103269, https://doi.org/10.1016/j.earscirev.2020.103269,
2020.
Zhang, G., Bolch, T., Chen, W., and Crétaux, J.-F.: Comprehensive
estimation of lake volume changes on the Tibetan Plateau during 1976–2019
and basin-wide glacier contribution, Sci. Total Environ., 772,
145463, https://doi.org/10.1016/j.scitotenv.2021.145463, 2021a.
Zhang, G., Ran, Y., Wan, W., Luo, W., Chen, W., Xu, F., and Li, X.: 100 years of lake evolution over the Qinghai–Tibet Plateau, Earth Syst. Sci. Data, 13, 3951–3966, https://doi.org/10.5194/essd-13-3951-2021, 2021b.
Zhang, Y., Fattahi, H., and Amelung, F.: Small baseline InSAR time series
analysis: Unwrapping error correction and noise reduction, Comput.
Geosci., 133, 104331, https://doi.org/10.1016/j.cageo.2019.104331, 2019.
Zhang, Y., Xie, C., Wu, T., Zhao, L., Wu, J., Wu, X., Li, R., Hu, G., Liu,
G., and Wang, W.: New permafrost is forming on the exposed bottom of Zonag
Lake on the Qinghai-Tibet Plateau, Sci. Total Environ., 815, 152879, https://doi.org/10.1016/j.scitotenv.2021.152879,
2022.
Zhao, L. and Sheng, Y.: Permafrost and environment changes on the
QinghaiTibetan Plateau, Science Press, Beijing, China, ISBN 9787030581334, 2019 (in Chinese).
Zhao, L., Hu, G., Zou, D., Wu, X., Ma, L., Sun, Z., Yuan, L., Zhou, H., and
Liu, S.: Permafrost Changes and Its Effects on Hydrological Processes on
Qinghai-Tibet Plateau, B. Chinese Acad.
Sci., 34, 1233–1246, 2019 (in Chinese).
Zhao, L., Zou, D., Du, E., Hu, G., Pang, Q., Xiao, Y., Li, R., Sheng, Y.,
Wu, X., Sun, Z., Wang, L., Wang, C., Ma, L., Zhou, H., and Liu, S.: Changing
climate and the permafrost environment on the Qinghai-Tibet (Xizang)
Plateau, Permafrost Periglac. Process., 31, 396–405, https://doi.org/10.1002/ppp.2056, 2020.
Zhou, H., Zhao, L., Tian, l., Wu, Z., Xie, M., Yuan, L., Ni, J., Qiao, Y.,
Gao, Z., and Shi, J.: Monitoring and analysis of surface deformation in the
permafrost area of Wudaoliang on the Tibetan Plateau based on Sentinel-1
data, J. Glaciol. Geocryol., 41, 525–536, 2019 (in Chinese).
Zhu, L., Wang, J., Ju, J., Ma, N., Zhang, Y., Liu, C., Han, B., Liu, L.,
Wang, M., and Ma, Q.: Climatic and lake environmental changes in the Serling
Co region of Tibet over a variety of timescales, Sci. Bull., 64,
422–424, 2019a.
Zhu, L., Zhang, G., Yang, R., Liu, C., Yang, K., Qiao, B., and Han, B.: Lake
Variations on Tibetan Plateau of Recent 40 Years and Future Changing
Tendency, B. Chinese Acad. Sci., 34,
1254–1263, 2019b (in Chinese).
Zou, D., Zhao, L., Sheng, Y., Chen, J., Hu, G., Wu, T., Wu, J., Xie, C., Wu, X., Pang, Q., Wang, W., Du, E., Li, W., Liu, G., Li, J., Qin, Y., Qiao, Y., Wang, Z., Shi, J., and Cheng, G.: A new map of permafrost distribution on the Tibetan Plateau, The Cryosphere, 11, 2527–2542, https://doi.org/10.5194/tc-11-2527-2017, 2017.
Zwieback, S. and Meyer, F. J.: Top-of-permafrost ground ice indicated by remotely sensed late-season subsidence, The Cryosphere, 15, 2041–2055, https://doi.org/10.5194/tc-15-2041-2021, 2021.
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...