Articles | Volume 16, issue 12
https://doi.org/10.5194/tc-16-4823-2022
© 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-16-4823-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Dec 2022
Research article |
| 05 Dec 2022
| 05 Dec 2022
Simulating the current and future northern limit of permafrost on the Qinghai–Tibet Plateau
Jianting Zhao
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Lin Zhao
CORRESPONDING AUTHOR
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Zhe Sun
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China
Fujun Niu
State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Guojie Hu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Guangyue Liu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Erji Du
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Chong Wang
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Lingxiao Wang
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Yongping Qiao
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Jianzong Shi
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Yuxin Zhang
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Junqiang Gao
School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China
Yuanwei Wang
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Wenjun Yu
School of Hydrology and Water Resources, Nanjing University of Information Science & Technology, Nanjing 210044, China
Huayun Zhou
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Zanpin Xing
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key Laboratory of Cryospheric Sciences,
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Minxuan Xiao
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Luhui Yin
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Shengfeng Wang
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
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This preprint is open for discussion and under review for The Cryosphere (TC).
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The thermal regime is a key indicator of permafrost evolution. We quantitatively analyzed the spatiotemporal dynamics of the permafrost status in western Tibet since the 1980s, based on numerical simulations using the enhanced, model-forcing-driven Moving-Grid Permafrost Model. Our simulated results indicated that slow and lagged response of permafrost to climate warming, which closely linked to historical thermal conditions.
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Discipline: Frozen ground | Subject: Numerical Modelling
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Bo Gao and Ethan T. Coon
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Representing water at constant density, neglecting cryosuction, and neglecting heat advection are three commonly applied but not validated simplifications in permafrost models to reduce computation complexity at field scale. We investigated this problem numerically by Advanced Terrestrial Simulator and found that neglecting cryosuction can cause significant bias (10%–60%), constant density primarily affects predicting water saturation, and ignoring heat advection has the least impact.
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Thawing permafrost releases carbon to the atmosphere, enhancing global warming. Part of the permafrost soils have been flooded by rising sea levels since the last ice age, becoming subsea permafrost (SSPF). The SSPF is less studied than the part on land. In this study we use a global model to obtain rates of thawing of SSPF under different future climate scenarios until the year 3000. After the year 2100 the scenarios strongly diverge, closely connected to the eventual disappearance of sea ice.
Léo C. P. Martin, Jan Nitzbon, Johanna Scheer, Kjetil S. Aas, Trond Eiken, Moritz Langer, Simon Filhol, Bernd Etzelmüller, and Sebastian Westermann
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It is important to understand how permafrost landscapes respond to climate changes because their thaw can contribute to global warming. We investigate how a common permafrost morphology degrades using both field observations of the surface elevation and numerical modeling. We show that numerical models accounting for topographic changes related to permafrost degradation can reproduce the observed changes in nature and help us understand how parameters such as snow influence this phenomenon.
Niccolò Tubini, Stephan Gruber, and Riccardo Rigon
The Cryosphere, 15, 2541–2568, https://doi.org/10.5194/tc-15-2541-2021, https://doi.org/10.5194/tc-15-2541-2021, 2021
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We present a new method to compute temperature changes with melting and freezing – a fundamental challenge in cryosphere research – extremely efficiently and with guaranteed correctness of the energy balance for any time step size. This is a key feature since the integration time step can then be chosen according to the timescale of the processes to be studied, from seconds to days.
Jan Nitzbon, Moritz Langer, Léo C. P. Martin, Sebastian Westermann, Thomas Schneider von Deimling, and Julia Boike
The Cryosphere, 15, 1399–1422, https://doi.org/10.5194/tc-15-1399-2021, https://doi.org/10.5194/tc-15-1399-2021, 2021
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We used a numerical model to investigate how small-scale landscape heterogeneities affect permafrost thaw under climate-warming scenarios. Our results show that representing small-scale heterogeneities in the model can decide whether a landscape is water-logged or well-drained in the future. This in turn affects how fast permafrost thaws under warming. Our research emphasizes the importance of considering small-scale processes in model assessments of permafrost thaw under climate change.
Eleanor J. Burke, Yu Zhang, and Gerhard Krinner
The Cryosphere, 14, 3155–3174, https://doi.org/10.5194/tc-14-3155-2020, https://doi.org/10.5194/tc-14-3155-2020, 2020
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Permafrost will degrade under future climate change. This will have implications locally for the northern high-latitude regions and may well also amplify global climate change. There have been some recent improvements in the ability of earth system models to simulate the permafrost physical state, but further model developments are required. Models project the thawed volume of soil in the top 2 m of permafrost will increase by 10 %–40 % °C−1 of global mean surface air temperature increase.
Jan Nitzbon, Moritz Langer, Sebastian Westermann, Léo Martin, Kjetil Schanke Aas, and Julia Boike
The Cryosphere, 13, 1089–1123, https://doi.org/10.5194/tc-13-1089-2019, https://doi.org/10.5194/tc-13-1089-2019, 2019
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We studied the stability of ice wedges (massive bodies of ground ice in permafrost) under recent climatic conditions in the Lena River delta of northern Siberia. For this we used a novel modelling approach that takes into account lateral transport of heat, water, and snow and the subsidence of the ground surface due to melting of ground ice. We found that wetter conditions have a destabilizing effect on the ice wedges and associated our simulation results with observations from the study area.
Kjetil S. Aas, Léo Martin, Jan Nitzbon, Moritz Langer, Julia Boike, Hanna Lee, Terje K. Berntsen, and Sebastian Westermann
The Cryosphere, 13, 591–609, https://doi.org/10.5194/tc-13-591-2019, https://doi.org/10.5194/tc-13-591-2019, 2019
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Many permafrost landscapes contain large amounts of excess ground ice, which gives rise to small-scale elevation differences. This results in lateral fluxes of snow, water, and heat, which we investigate and show how it can be accounted for in large-scale models. Using a novel model technique which can account for these differences, we are able to model both the current state of permafrost and how these landscapes change as permafrost thaws, in a way that could not previously be achieved.
Isabelle Gouttevin, Moritz Langer, Henning Löwe, Julia Boike, Martin Proksch, and Martin Schneebeli
The Cryosphere, 12, 3693–3717, https://doi.org/10.5194/tc-12-3693-2018, https://doi.org/10.5194/tc-12-3693-2018, 2018
Short summary
Short summary
Snow insulates the ground from the cold air in the Arctic winter, majorly affecting permafrost. This insulation depends on snow characteristics and is poorly quantified. Here, we characterize it at a carbon-rich permafrost site, using a recent technique that retrieves the 3-D structure of snow and its thermal properties. We adapt a snowpack model enabling the simulation of this insulation over a whole winter. We estimate that local snow variations induce up to a 6 °C spread in soil temperatures.
Shuhua Yi, Yujie He, Xinlei Guo, Jianjun Chen, Qingbai Wu, Yu Qin, and Yongjian Ding
The Cryosphere, 12, 3067–3083, https://doi.org/10.5194/tc-12-3067-2018, https://doi.org/10.5194/tc-12-3067-2018, 2018
Short summary
Short summary
Coarse-fragment soil on the Qinghai–Tibetan Plateau has different thermal and hydrological properties to soils commonly used in modeling studies. We took soil samples and measured their physical properties in a laboratory, which were used in a model to simulate their effects on permafrost dynamics. Model errors were reduced using the measured properties, in which porosity played an dominant role.
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Short summary
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.
Permafrost has been warming and thawing globally; this is especially true in boundary regions....
