Articles | Volume 12, issue 9
https://doi.org/10.5194/tc-12-3067-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-12-3067-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Sep 2018
Research article |
| 27 Sep 2018
| 27 Sep 2018
The physical properties of coarse-fragment soils and their effects on permafrost dynamics: a case study on the central Qinghai–Tibetan Plateau
Shuhua Yi
School of Geographic Sciences, Nantong University, 999 Tongjing Road, Nantong, 226007, China
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment
and Resources, Chinese Academy of Sciences, 320 Donggang West Road, 730000, Lanzhou, Gansu, China
Yujie He
Chinese Research Academy of Environmental Sciences, No.8 Dayangfang, Chaoyang District, 100012, Beijing, China
Xinlei Guo
Department of Ecosystem and Landscape Dynamics, Institute for Biodiversity and
Ecosystem Dynamics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
Jianjun Chen
College of Geomatics and Geoinformation, Guilin University of Technology, 12 Jiangan Road, Guilin, 541004, China
Guangxi Key Laboratory of Spatial Information and Geomatics, 12 Jiangan Road, Guilin, 541004, China
Qingbai Wu
State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment
and Resources, Chinese Academy of Sciences, 320 Donggang West Road, 730000, Lanzhou, Gansu, China
Yu Qin
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment
and Resources, Chinese Academy of Sciences, 320 Donggang West Road, 730000, Lanzhou, Gansu, China
Yongjian Ding
CORRESPONDING AUTHOR
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment
and Resources, Chinese Academy of Sciences, 320 Donggang West Road, 730000, Lanzhou, Gansu, China
Key Laboratory of Ecohydrology of Inland River Basin, Chinese Academy of Sciences, Lanzhou 730000, China
University of Chinese Academy Sciences, Beijing, 100049, China
Related authors
Huifang Zhang, Zhonggang Tang, Binyao Wang, Hongcheng Kan, Yi Sun, Yu Qin, Baoping Meng, Meng Li, Jianjun Chen, Yanyan Lv, Jianguo Zhang, Shuli Niu, and Shuhua Yi
Earth Syst. Sci. Data, 15, 821–846, https://doi.org/10.5194/essd-15-821-2023, https://doi.org/10.5194/essd-15-821-2023, 2023
Short summary
Short summary
The accuracy of regional grassland aboveground biomass (AGB) is always limited by insufficient ground measurements and large spatial gaps with satellite pixels. This paper used more than 37 000 UAV images as bridges to successfully obtain AGB values matching MODIS pixels. The new AGB estimation model had good robustness, with an average R2 of 0.83 and RMSE of 34.13 g m2. Our new dataset provides important input parameters for understanding the Qinghai–Tibet Plateau during global climate change.
Yu Qin, Shuhua Yi, Yongjian Ding, Wei Zhang, Yan Qin, Jianjun Chen, and Zhiwei Wang
Biogeosciences, 16, 1097–1109, https://doi.org/10.5194/bg-16-1097-2019, https://doi.org/10.5194/bg-16-1097-2019, 2019
Lihui Luo, Zhongqiong Zhang, Wei Ma, Shuhua Yi, and Yanli Zhuang
Geosci. Model Dev., 11, 2475–2491, https://doi.org/10.5194/gmd-11-2475-2018, https://doi.org/10.5194/gmd-11-2475-2018, 2018
Short summary
Short summary
Based on the current situation of permafrost modeling in the Qinghai–Tibet Plateau (QTP), a software PIC was developed to evaluate the temporal–spatial change trends of permafrost, which allows us to automatically compute permafrost indices with daily weather and atmospheric forcing datasets. The main features include computing, visualization, and statistics. The software will serve engineering applications and can be used to assess the impact of climate change on permafrost over the QTP.
Shuhua Yi, Jianjun Chen, Yu Qin, and Gaowei Xu
Biogeosciences, 13, 6273–6284, https://doi.org/10.5194/bg-13-6273-2016, https://doi.org/10.5194/bg-13-6273-2016, 2016
Short summary
Short summary
Plateau pika is common on the Qinghai-Tibet Plateau (QTP). Since pika dig burrows and graze on grassland to compete with yaks and sheep, they are believed to be a pest. They have been killed by humans since the 1950s. However, there are no serious studies that quantitatively evaluate the grazing and excavating effects of pika on grassland. With the advancement of UAV technology, we did a pilot study to evaluate the grazing and burying effects of pika.
S. Yi, K. Wischnewski, M. Langer, S. Muster, and J. Boike
Geosci. Model Dev., 7, 1671–1689, https://doi.org/10.5194/gmd-7-1671-2014, https://doi.org/10.5194/gmd-7-1671-2014, 2014
S. Yi, J. Chen, Q. Wu, and Y. Ding
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-4703-2013, https://doi.org/10.5194/tcd-7-4703-2013, 2013
Revised manuscript not accepted
Xiaoying Li, Huijun Jin, Qi Feng, Qingbai Wu, Hongwei Wang, Ruixia He, Dongliang Luo, Xiaoli Chang, Raul-David Şerban, and Tao Zhan
Earth Syst. Sci. Data, 16, 5009–5026, https://doi.org/10.5194/essd-16-5009-2024, https://doi.org/10.5194/essd-16-5009-2024, 2024
Short summary
Short summary
In Northeast China, the permafrost is more sensitive to climate warming and fire disturbances than the boreal and Arctic permafrost. Since 2016, a continuous ground hydrothermal regime and soil nutrient content observation system has been gradually established in Northeast China. The integrated dataset includes soil moisture content, soil organic carbon, total nitrogen, total phosphorus, total potassium, ground temperatures at depths of 0–20 m, and active layer thickness from 2016 to 2022.
Jia Qin, Yongjian Ding, Faxiang Shi, Junhao Cui, Yaping Chang, Tianding Han, and Qiudong Zhao
Hydrol. Earth Syst. Sci., 28, 973–987, https://doi.org/10.5194/hess-28-973-2024, https://doi.org/10.5194/hess-28-973-2024, 2024
Short summary
Short summary
The linkage between the seasonal hydrothermal change of active layer, suprapermafrost groundwater, and surface runoff, which has been regarded as a “black box” in hydrological analyses and simulations, is a bottleneck problem in permafrost hydrological studies. Based on field observations, this study identifies seasonal variations and causes of suprapermafrost groundwater. The linkages and framework of watershed hydrology responding to the freeze–thaw of the active layer also are explored.
Huifang Zhang, Zhonggang Tang, Binyao Wang, Hongcheng Kan, Yi Sun, Yu Qin, Baoping Meng, Meng Li, Jianjun Chen, Yanyan Lv, Jianguo Zhang, Shuli Niu, and Shuhua Yi
Earth Syst. Sci. Data, 15, 821–846, https://doi.org/10.5194/essd-15-821-2023, https://doi.org/10.5194/essd-15-821-2023, 2023
Short summary
Short summary
The accuracy of regional grassland aboveground biomass (AGB) is always limited by insufficient ground measurements and large spatial gaps with satellite pixels. This paper used more than 37 000 UAV images as bridges to successfully obtain AGB values matching MODIS pixels. The new AGB estimation model had good robustness, with an average R2 of 0.83 and RMSE of 34.13 g m2. Our new dataset provides important input parameters for understanding the Qinghai–Tibet Plateau during global climate change.
Junfeng Wang, Qingbai Wu, Ziqiang Yuan, and Hojeong Kang
The Cryosphere, 14, 2835–2848, https://doi.org/10.5194/tc-14-2835-2020, https://doi.org/10.5194/tc-14-2835-2020, 2020
Short summary
Short summary
The active layer, a buffer between permafrost and the atmosphere, is more sensitive and responds more quickly to climate change. How the freeze–thaw action at different stages regulates carbon emissions is still unclear. We conducted 2-year continuous in situ measurements in an alpine meadow permafrost ecosystem in the Qinghai–Tibet Plateau and found the freeze–thaw process modified the Rs dynamics differently in different stages. Results suggest great changes in freeze–thaw process patterns.
Junfeng Liu, Rensheng Chen, Yongjian Ding, Chuntan Han, Yong Yang, Zhangwen Liu, Xiqiang Wang, Shuhai Guo, Yaoxuan Song, and Wenwu Qing
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-67, https://doi.org/10.5194/tc-2020-67, 2020
Preprint withdrawn
Short summary
Short summary
we try to investigate the spatial and temporal variability of albedo, micro scale surface roughness, and LAIs, with the objective to better understanding and simulating surface albedo variability over snow and dirty ice surface at the August-one ice cap in Qilian Mountain. Snow and ice surface albedo parameterization methods are established based on either surface roughness or both surface roughness and LAIs.
Jia Qin, Yongjian Ding, Tianding Han, Junhao Li, Shaoping Wang, and Yaping Chang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-626, https://doi.org/10.5194/hess-2019-626, 2019
Revised manuscript not accepted
Short summary
Short summary
Based on the spatial-temporal variations of runoff, river ice, snowmelt and water-energy budgets, as well as Arctic index, we found that the lowest, mean, and highest monthly discharge of Eurasian rivers had large zonal differences and different trends during 1951–2015, especially after the late 1990s. River-ice is a dominate factor in winter runoff variation. A
warm Arctic-large dischargeand a
warm Arctic- few dischargepattern exist in different latitudes of Eurasia after the late 1990s.
Yu Qin, Shuhua Yi, Yongjian Ding, Wei Zhang, Yan Qin, Jianjun Chen, and Zhiwei Wang
Biogeosciences, 16, 1097–1109, https://doi.org/10.5194/bg-16-1097-2019, https://doi.org/10.5194/bg-16-1097-2019, 2019
Bin Cao, Tingjun Zhang, Qingbai Wu, Yu Sheng, Lin Zhao, and Defu Zou
The Cryosphere, 13, 511–519, https://doi.org/10.5194/tc-13-511-2019, https://doi.org/10.5194/tc-13-511-2019, 2019
Short summary
Short summary
Many maps have been produced to estimate permafrost distribution over the Qinghai–Tibet Plateau. However the evaluation and inter-comparisons of them are poorly understood due to limited in situ measurements. We provided an in situ inventory of evidence of permafrost presence or absence, with 1475 sites over the Qinghai–Tibet Plateau. Based on the in situ measurements, our evaluation results showed a wide range of map performance, and the estimated permafrost region and area are extremely large.
Hanbo Yun, Qingbai Wu, Qianlai Zhuang, Anping Chen, Tong Yu, Zhou Lyu, Yuzhong Yang, Huijun Jin, Guojun Liu, Yang Qu, and Licheng Liu
The Cryosphere, 12, 2803–2819, https://doi.org/10.5194/tc-12-2803-2018, https://doi.org/10.5194/tc-12-2803-2018, 2018
Short summary
Short summary
Here we reported the QTP permafrost region was a CH4 sink of −0.86 ± 0.23 g CH4-C m−2 yr−1 over 2012–2016, soil temperature and soil water content were dominant factors controlling CH4 fluxes, and their correlations changed with soil depth due to cryoturbation dynamics. This region was a net CH4 sink in autumn, but a net source in spring, despite both seasons experiencing similar top soil thawing and freezing dynamics.
Lihui Luo, Zhongqiong Zhang, Wei Ma, Shuhua Yi, and Yanli Zhuang
Geosci. Model Dev., 11, 2475–2491, https://doi.org/10.5194/gmd-11-2475-2018, https://doi.org/10.5194/gmd-11-2475-2018, 2018
Short summary
Short summary
Based on the current situation of permafrost modeling in the Qinghai–Tibet Plateau (QTP), a software PIC was developed to evaluate the temporal–spatial change trends of permafrost, which allows us to automatically compute permafrost indices with daily weather and atmospheric forcing datasets. The main features include computing, visualization, and statistics. The software will serve engineering applications and can be used to assess the impact of climate change on permafrost over the QTP.
Liyun Dai, Tao Che, Yongjian Ding, and Xiaohua Hao
The Cryosphere, 11, 1933–1948, https://doi.org/10.5194/tc-11-1933-2017, https://doi.org/10.5194/tc-11-1933-2017, 2017
Short summary
Short summary
Snow depth over QTP plays a very important role in the climate and hydrological system, but there are uncertainties on the snow depth products derived from passive microwave remote sensing data. In this study, we evaluated the ability of passive microwave to detect snow cover and snow depth over QTP, presented the accuracy of passive microwave snow cover and snow depth products over QTP, and analyzed the possible reasons causing the uncertainties.
Shuhua Yi, Jianjun Chen, Yu Qin, and Gaowei Xu
Biogeosciences, 13, 6273–6284, https://doi.org/10.5194/bg-13-6273-2016, https://doi.org/10.5194/bg-13-6273-2016, 2016
Short summary
Short summary
Plateau pika is common on the Qinghai-Tibet Plateau (QTP). Since pika dig burrows and graze on grassland to compete with yaks and sheep, they are believed to be a pest. They have been killed by humans since the 1950s. However, there are no serious studies that quantitatively evaluate the grazing and excavating effects of pika on grassland. With the advancement of UAV technology, we did a pilot study to evaluate the grazing and burying effects of pika.
Qingbai Wu, Zhongqiong Zhang, Siru Gao, and Wei Ma
The Cryosphere, 10, 1695–1706, https://doi.org/10.5194/tc-10-1695-2016, https://doi.org/10.5194/tc-10-1695-2016, 2016
Ji Chen, Yu Sheng, Qingbai Wu, Lin Zhao, Jing Li, and Jingyi Zhao
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-134, https://doi.org/10.5194/tc-2016-134, 2016
Revised manuscript not accepted
Short summary
Short summary
The extreme thin and short-time snow cover in the northeastern Qinghai-Tibet plateau is predominantly during spring and autumn. Removal of seasonal snow cover is beneficial for cooling the active layer in the first few years. Seasonal snow cover maintains the high water content of the active layer because of the inhibitory action of snow cover on the evaporation capacity in the natural site during the daytime and in summer. Snow removal can therefore lead to a rapid decrease of soil moisture.
Shengyun Chen, Wenjie Liu, Qian Zhao, Lin Zhao, Qingbai Wu, Xingjie Lu, Shichang Kang, Xiang Qin, Shilong Chen, Jiawen Ren, and Dahe Qin
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-80, https://doi.org/10.5194/tc-2016-80, 2016
Revised manuscript not accepted
Short summary
Short summary
Experimental warming was manipulated using open top chambers in alpine grassland ecosystem in the permafrost regions of the Qinghai-Tibet Plateau. The results revealed variations of earlier thawing, later freezing and longer freezing-thawing periods in shallow soil. Further, the estimated permafrost table declined under the warming scenarios. The work will be helpful to evaluate the stability of Qinghai-Tibet Railway/Highway and estimate the release of carbon under the future climate warming.
C. Mu, T. Zhang, Q. Wu, X. Peng, B. Cao, X. Zhang, B. Cao, and G. Cheng
The Cryosphere, 9, 479–486, https://doi.org/10.5194/tc-9-479-2015, https://doi.org/10.5194/tc-9-479-2015, 2015
S. Yi, K. Wischnewski, M. Langer, S. Muster, and J. Boike
Geosci. Model Dev., 7, 1671–1689, https://doi.org/10.5194/gmd-7-1671-2014, https://doi.org/10.5194/gmd-7-1671-2014, 2014
S. Yi, J. Chen, Q. Wu, and Y. Ding
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-4703-2013, https://doi.org/10.5194/tcd-7-4703-2013, 2013
Revised manuscript not accepted
Related subject area
Discipline: Frozen ground | Subject: Numerical Modelling
Modelling the effect of free convection on permafrost melting rates in frozen rock clefts
Coupled thermo–geophysical inversion for permafrost monitoring
Simulating ice segregation and thaw consolidation in permafrost environments with the CryoGrid community model
Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer
Representation of soil hydrology in permafrost regions may explain large part of inter-model spread in simulated Arctic and subarctic climate
Simulating the current and future northern limit of permafrost on the Qinghai–Tibet Plateau
Evaluating simplifications of subsurface process representations for field-scale permafrost hydrology models
Strong increase in thawing of subsea permafrost in the 22nd century caused by anthropogenic climate change
Lateral thermokarst patterns in permafrost peat plateaus in northern Norway
A method for solving heat transfer with phase change in ice or soil that allows for large time steps while guaranteeing energy conservation
Effects of multi-scale heterogeneity on the simulated evolution of ice-rich permafrost lowlands under a warming climate
Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change
Pathways of ice-wedge degradation in polygonal tundra under different hydrological conditions
Thaw processes in ice-rich permafrost landscapes represented with laterally coupled tiles in a land surface model
Observation and modelling of snow at a polygonal tundra permafrost site: spatial variability and thermal implications
Amir Sedaghatkish, Frédéric Doumenc, Pierre-Yves Jeannin, and Marc Luetscher
The Cryosphere, 18, 4531–4546, https://doi.org/10.5194/tc-18-4531-2024, https://doi.org/10.5194/tc-18-4531-2024, 2024
Short summary
Short summary
We developed a model to simulate the natural convection of water within frozen rock crevices subject to daily warming in mountain permafrost regions. Traditional models relying on conduction and latent heat flux typically overlook free convection. The results reveal that free convection can significantly accelerate the melting rate by an order of magnitude compared to conduction-based models. Our results are important for assessing the impact of climate change on mountain infrastructure.
Soňa Tomaškovičová and Thomas Ingeman-Nielsen
The Cryosphere, 18, 321–340, https://doi.org/10.5194/tc-18-321-2024, https://doi.org/10.5194/tc-18-321-2024, 2024
Short summary
Short summary
We present the results of a fully coupled modeling framework for simulating the ground thermal regime using only surface measurements to calibrate the thermal model. The heat conduction model is forced by surface ground temperature measurements and calibrated using the field measurements of time lapse apparent electrical resistivity. The resistivity-calibrated thermal model achieves a performance comparable to the traditional calibration of borehole temperature measurements.
Juditha Aga, Julia Boike, Moritz Langer, Thomas Ingeman-Nielsen, and Sebastian Westermann
The Cryosphere, 17, 4179–4206, https://doi.org/10.5194/tc-17-4179-2023, https://doi.org/10.5194/tc-17-4179-2023, 2023
Short summary
Short summary
This study presents a new model scheme for simulating ice segregation and thaw consolidation in permafrost environments, depending on ground properties and climatic forcing. It is embedded in the CryoGrid community model, a land surface model for the terrestrial cryosphere. We describe the model physics and functionalities, followed by a model validation and a sensitivity study of controlling factors.
Brian Groenke, Moritz Langer, Jan Nitzbon, Sebastian Westermann, Guillermo Gallego, and Julia Boike
The Cryosphere, 17, 3505–3533, https://doi.org/10.5194/tc-17-3505-2023, https://doi.org/10.5194/tc-17-3505-2023, 2023
Short summary
Short summary
It is now well known from long-term temperature measurements that Arctic permafrost, i.e., ground that remains continuously frozen for at least 2 years, is warming in response to climate change. Temperature, however, only tells half of the story. In this study, we use computer modeling to better understand how the thawing and freezing of water in the ground affects the way permafrost responds to climate change and what temperature trends can and cannot tell us about how permafrost is changing.
Philipp de Vrese, Goran Georgievski, Jesus Fidel Gonzalez Rouco, Dirk Notz, Tobias Stacke, Norman Julius Steinert, Stiig Wilkenskjeld, and Victor Brovkin
The Cryosphere, 17, 2095–2118, https://doi.org/10.5194/tc-17-2095-2023, https://doi.org/10.5194/tc-17-2095-2023, 2023
Short summary
Short summary
The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone. We used an adapted version of the Max Planck Institute (MPI) Earth System Model to show that differences in the representation of the soil hydrology in permafrost-affected regions could help explain a large part of this inter-model spread and have pronounced impacts on important elements of Earth systems as far to the south as the tropics.
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
Short summary
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.
Bo Gao and Ethan T. Coon
The Cryosphere, 16, 4141–4162, https://doi.org/10.5194/tc-16-4141-2022, https://doi.org/10.5194/tc-16-4141-2022, 2022
Short summary
Short summary
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.
Stiig Wilkenskjeld, Frederieke Miesner, Paul P. Overduin, Matteo Puglini, and Victor Brovkin
The Cryosphere, 16, 1057–1069, https://doi.org/10.5194/tc-16-1057-2022, https://doi.org/10.5194/tc-16-1057-2022, 2022
Short summary
Short summary
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
The Cryosphere, 15, 3423–3442, https://doi.org/10.5194/tc-15-3423-2021, https://doi.org/10.5194/tc-15-3423-2021, 2021
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Anisimov, O. A.: Potential feedback of thawing permafrost to the global
climate system through methan emission, Environ. Res. Lett., 2, 045016,
https://doi.org/10.1088/1748-9326/2/4/045016, 2007.
Arocena, J., Hall, K., and Zhu, L. P.: Soil formation in high elevation and
permafrost areas in the Qinghai Plateau (China), Span. J. Soil
Sci., 2, 34–49, 2012.
Azam, G., Grant, C. D., Murray, R. S., Nuberg, I. K., and Misra, R. K. :
Comparison of the penetration of primary and lateral roots of pea and
different tree seedlings growing in hard soils, Soil Res., 52, 87–96,
2014.
Boike, J., Kattenstroth, B., Abramova, K., Bornemann, N., Chetverova, A.,
Fedorova, I., Fröb, K., Grigoriev, M., Grüber, M., Kutzbach, L., Langer, M.,
Minke, M., Muster, S., Piel, K., Pfeiffer, E.-M., Stoof, G., Westermann, S.,
Wischnewski, K., Wille, C., and Hubberten, H.-W.: Baseline characteristics of
climate, permafrost and land cover from a new permafrost observatory in the
Lena River Delta, Siberia (1998–2011), Biogeosciences, 10, 2105–2128,
https://doi.org/10.5194/bg-10-2105-2013, 2013.
Chen, H., Nan, Z., Zhao, L., Ding, Y., Chen, J., and Pang, Q.: Noah
Modelling of the Permafrost Distribution and Characteristics in the West
Kunlun Area, Qinghai-Tibet Plateau, China, Permafr. Periglac., 26, 160–174,
2015.
Chen, J., Yi, S., and Qin, Y.: The contribution of plateau pika disturbance
and erosion on patchy alpine grassland soil on the Qinghai-Tibetan Plateau:
Implications for grassland restoration, Geoderma, 297, 1–9, 2017.
Chen, Y., Yang, K., Tang, W., Qin, J., and Zhao, L.: Parameterizing soil
organic carbon's impacts on soil porosity and thermal parameters for Eastern
Tibet grasslands, Sci. China Ser. D, 55, 1001–1011,
2012.
Côté, J. and Konrad, J.: A generalized thermal conductivity model for soils
and construction materials, Can. Geotech. J., 42, 443–458, 2005.
Du, Z., Cai, Y., Yan, Y., and Wang, X.: Embedded rock fragments affect
alpine steppe plant growth, soil carbon and nitrogen in the northern Tibetan
Plateau, Plant. Soil, 420, 79–92, 2017.
Farouki, O. T.: Thermal properties of soils, Cold Reg. Res. Eng. Lab.,
Hanover, N. H, 1986.
Fox, J. D.: Incorporating Freeze-Thaw Calculations into a water balance
model, Water Resour. Res., 28, 2229–2244, 1992.
Frey, K. E. and McClelland, J. W.: Impacts of permafrost degradation on
arctic river biogeochemistry, Hydrol. Process., 23, 169–182, 2009.
Goodrich, E. L.: Efficient Numerical Technique for one-dimensional Thermal
Problems with phase change, Int. J. Heat Mass Transf., 21, 615–621, 1978.
Gwenzi, W., Hinz, C., Holmes, K., Phillips, I. R., and Mullins, I. J.:
Field-scale spatial variability of saturated hydraulic conductivity on a
recently constructed artificial ecosystem, Geoderma, 166, 43–56, 2011.
Han, X., Liu, J., Zhang, J., and Zhang, Z.: Identifying soil structure along
headwater hillslopes using ground penetrating radar based technique, J.
Mount. Sci., 13, 405–415, 2016.
Jorgenson, M. T., Shur, Y. L., and Pullman, E. R.: Abrupt increase in
permafrost degradation in Arctic Alaska, Res. Lett., 33, L02503,
https://doi.org/10.1029/2005GL024960, 2006.
Langer, M., Westermann, S., Heikenfeld, M., Dorn, W., and Boike, J.:
Satellite-based modeling of permafrost temperatures in a tundra lowland
landscape, Remote Sens. Environ., 135, 12–24, 2013.
Li, J., Sheng, Y., Wu, J., Chen, J., and Zhang, X.: Probability distribution
of permafrost along a transportation corridor in the northeastern Qinghai
province of China, Cold Reg. Sci. Technol., 59, 12–18, 2009.
Li, W., Zhao, L., Wu, X., Zhao, Y., Fang, H., and Shi, W.: Distribution of
soils and landform relationships in the permafrost regions of Qinghai-Xizang
(Tibetan) Plateau, Chinese Sci. Bull., 23, 2216–2226, 2015.
Lin, Z., Niu, F., Liu, H., and Lu, J.: Hydrothermal processes of alpine
tundra lakes, Beiluhe Basin, Qinghai-Tibet Plateau, Cold Reg. Sci. Techol.,
65, 446–455, 2011.
Luo, S., Lv, S., Zhang, Y., Hu, Z., Ma, Y., Li, S., and Shang, L.: Soil
thermal conductivity parameterization establishment and application in
numerical model of central Tibetan Plateau, China J. Geophys.,
52, 919–928, 2009 (in Chinese with English Abstract).
McGuire, A. D., Melillo, J., Jobbagy, E. G., Kicklighter, D., Grace, A. L.,
Moore, B., and Vorosmarty, C. J.: Interactions Between Carbon and Nitrogen
Dynamics in Estimating Net Primary Productivity for Potential Vegetation in
North America, Global Biogeochem. Cy., 6, 101–124, 1992.
McGuire, A. D., Clein, J. S., Melillo, J., Kicklighter, D., Meier, R. A.,
Vorosmarty, C. J., and Serreze, M. C.: Modelling carbon responses of tundra
ecosystems to historical and projected climate: sensitivity of pan-Arctic
carbon storage to temporal and spatial variation in climate, Global Change
Biol., 6 (Suppl. 1), 141–159, 2000.
McGuire, A. D., Anderson, L. G., Christensen, T. R., Dallimore, S., Guo, L.,
Hayes, D. J., and Roulet, N.: Sensitivity of the carbon cycle in the
Arctic to climate change, Ecol. Monogr., 79, 523–555, 2009.
Nan, Z., Li, S., and Cheng, G.: Prediction of permafrost distribution on the
Qinghai-Tibet Plateau in the next 50 and 100 years, Sci. China Ser.
D, 48, 797–804, 2005.
Nelson, F. E., Anisimov, O. A., and Shiklomanov, N. I.: Subsidence risk from
thawing permafrost, Nature, 410, 889–890, 2001.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Flanner, M. G., Kluzek, E.,
Lawrence, P. J., Levis, S., Swenson, S. C., and Thornton, P.: Technical
description of version 4.0 of the Community Land Model (CLM), University
Corporation for Atmospheric Research, NCAR 2153-2400, 2010.
Pan, Y., Lv, S., Li, S., Gao, Y., Meng, X., Ao, Y., and Wang, S.: Simulating
the role of gravel in freeze–thaw processon the Qinghai–Tibet Plateau,
Theor. Appl. Climatol., 127, 1011–1022, 2017.
Qin, Y., Yi, S., Chen, J., Ren, S., and Ding, Y.: Effects of gravel on soil
and vegetation properties of alpine grassland on the Qinghai-Tibetan
plateau, Ecol. Eng., 74, 351–355, 2015.
Qin, Y., Wu, T. , Zhao, L., Wu, X., Li, R., Xie, C., Pang, Q., Hu, G., Qiao,
Y., Zhao, G., Liu, G., Zhu, X., and Hao, J.: Numerical Modeling of the
Active Layer Thickness and Permafrost Thermal State Across Qinghai-Tibetan
Plateau, J. Geophys. Res.-Atmos., 21, 11604–11620,
https://doi.org/10.1002/2017JD026858, 2017.
Romanovsky, V. E. and Osterkamp, T. E.: Effects of unfrozen water on heat
and mass transport processes in the active layer and permafrost, Permafr.
Periglac., 11, 219–239, 2000.
Salmon, V. G., Soucy, P., Mauritz, M., Celis, G., Natali, S. M., Mack, M.
C., and Schuur, E. A.: Nitrogen availability increases in a tundra ecosystem
during five years of experimental permafrost thaw, Global Change Biol., 22,
1927–1941, 2015.
Soil Survey Staff: Keys to Soil Taxonomy, 12th Ed., USDA-Natural Resources
Conservation Service, Washington, DC, 2014.
Stephens, D. B., Hsu, K., Prieksat, M. A., Ankeny, M. D., Blandford, N.,
Roth, T. L., Kelsey, J. A., and Whitworth, J. R.: A comparison of estimated
and calculated effective porosity, Hydrol. Process., 6, 156–165, 1998.
Swenson, S. C., Lawrence, D. M., and Lee, H.: Improved simulation of the
terrestrial hydrological cycle in permafrost regions by the Community Land
Model, J. Adv. Model. Earth Syst., 4, M08002,
https://doi.org/10.1029/2012MS000165, 2013.
Walvoord, M. A. and Striegl, R. G.: Increased groundwater to stream
discharge from permafrost thawing in the Yukon River basin: Potential
impacts on lateral export of carbon and nitrogen, Geophys. Res. Lett., 34,
L12402, https://doi.org/10.1029/2007GL030216, 2007.
Wang, F. X., Kang, Y., Liu, S. P., and Hou, X. Y.: Effects of soil matric
potential on potato growth under drip irrigation in the North China
Plain, Agr. Water Manage., 88, 34–42, 2007.
Wang, G., Li. Y., Wang. Y., and Wu, Q.: Effects of permafrost thawing on
vegetation and soil carbon pool losses on the Qinghai-Tibet Plateau, China,
Geoderma, 143, 143–152, 2008.
Wang, H., Xiao, B., Wang, M., and Shao, M.: Modeling the soil water
retention curves of soil-gravel mixtures with regression method on the Loess
Plateau of China, PLoS ONE, 8, e59475, https://doi.org/10.1371/journal.pone.0059475,
2013.
Wang, L., Zhou, J., Qi, J., Sun, L., Yang, K., Tian, L., and Koike, T.:
Development of a land surface model with coupled snow and frozen soil
physics, Water Resour. Res., 53, 5085–5103, https://doi.org/10.1002/2017WR020451,
2017.
Wang, X., Liu, G., and Liu, S.: Effects of gravel on grassland soil carbon
and nitrogen in the arid regions of the Tibetan Plateau, Geoderma, 166,
181–188, 2011.
Wang, Z., Wang, Q., Zhao, L., Wu, X., Yue, G., Zou, D., Nan, Z., Liu, G.,
Pang, Q., Fang, H., Wu, T., Shi, J., Jiao, K., Zhao, Y., and Zhang, L.:
Mapping the vegetation distribution of the permafrost zone on the
Qinghai-Tibet Plateau, J. Mountain Sci., 13, 1035–1046, 2016.
Woo, M. K., Arain, M. A., Mollinga, M., and Yi, S.: A two-directional freeze
and thaw algorithm for hydrologic and land surface modelling, Geophys. Res.
Lett., 31, L12501, https://doi.org/10.1029/2004GL019475, 2004.
Wright, N., Hayashi, M., and Quinton, W. L.: Spatial and temporal variations
in active layer thawing and their implication on runoff generation in
peat-covered permafrost terrain, Water Resour. Res., 45, W05414,
https://doi.org/10.1029/2008WR006880, 2009.
Wu, Q. and Zhang, T.:. Changes in active layer thickness over the
Qinghai-Tibetan Plateau from 1995 to 2007, J. Geophys. Res., 115, D09107,
https://doi.org/10.1029/2009JD012974, 2010.
Wu, Q., Cheng, G., and Ma, W.: Impact of permafrost change on the
Qinghai-Tibet Railroad engineering, Sc. China Ser. D, 47, 122–130, 2004.
Wu, Q., Zhang, Z., Gao, S., and Ma, W.: Thermal impacts of engineering
activities and vegetation layer on permafrost in different alpine
ecosystems of the Qinghai-Tibet Plateau, China, The Cryosphere, 10,
1695–1706, https://doi.org/10.5194/tc-10-1695-2016, 2016.
Wu, X. and Nan, Z.: A Multilayer Soil Texture Dataset for Permafrost
Modeling over Qinghai – Tibetan Plateau, IGARSS, 4917–4920, 2016.
Wu, X., Zhao, L., Fang, H., Zhao, Y., Smoak, J. M., Pang, Q., and Ding, Y.:
Environmental controls on soil organic carbon and nitrogen stocks in the
high-altitude arid western Qinghai-Tibetan Plateau permafrost region, J.
Geophys. Res., 121, 176–187, 2016.
Wu, X., Nan, Z., Zhao, S., Zhao, L., and Cheng, G.: Spatial modeling of
permafrost distribution and properties on the Qinghai-Tibetan Plateau,
Permafr. Periglac., 29, 86–99, https://doi.org/10.1002/ppp.1971, 2018.
Yang, J., Mi, R., and Liu, J.:Variations in soil properties and their effect
on subsurface biomass distribution in four alpine meadows of the hinterland
of the Tibetan Plateau of China, Environ. Geol., 57, 1881–1891, 2009.
Yang, K., Zhu, L., Chen, Y., Zhao, L., Qin, J., Lu, H., and Fang, N.: Land
surface model calibration through microwave data assimilation for improving
soil moisture simulations, J. Hydrol., 533, 266–276, 2016.
Ye, B., Yang, D., Zhang, Z., and Kane, D. L.: Variation of hydrological
regime with permafrost coverage over Lena Basin in Siberia, J. Geophys.
Res., 114, D07102, https://doi.org/10.1029/2008JD010537, 2009.
Yi, S.: FragMAP: a tool for long-term and cooperative monitoring and analysis
of small-scale habitat fragmentation using an unmanned aerial vehicle,
Int. J. Remote Sens., 38, 2686–2697, 2017.
Yi, S., Manies, K. L., Harden, J., and McGuire, A. D.: The characteristics
of organic soil in black spruce forests: Implications for the application of
land surface and ecosystem models in cold regions, Geophys. Res. Lett., 36,
L05501, https://doi.org/10.1029/2008GL037014, 2009a.
Yi, S., McGuire, A. D., Harden, J., Kasischke, E., Manies, K. L., Hinzman,
L. D., Liljedahl, A., Randerson, J. T., Liu, H., Romanovsky, V. E.,
Marchenko, S., and Kim, Y.: Interactions between soil thermal and
hydrological dynamics in the response of Alaska ecosystems to fire
disturbance, J. Geophys. Res., 114, G02015, https://doi.org/10.1029/2008JG000841,
2009b.
Yi, S., McGuire, A. D., Kasischke, E., Harden, J., Manies, K. L., Mack, M.,
and Turetsky, M. R.: A Dynamic organic soil biogeochemical model for
simulating the effects of wildfire on soil environmental conditions and
carbon dynamics of black spruce forests, J. Geophys. Res., 115, G04015,
https://doi.org/10.1029/2010JG001302, 2010.
Yi, S., Li, N., Xiang, B., Ye, B., and McGuire, A.D.: Representing the
effects of alpine grassland vegetation cover on the simulation of soil
thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau,
J. Geophys. Res., 118, 1–14, https://doi.org/10.1002/jgrg.20093, 2013.
Yi, S., Wang, X., Qin, Y., Xiang, B., and Ding, Y.: Responses of alpine
grassland on Qinghai–Tibetan plateau to climate warming and permafrost
degradation: a modeling perspective, Environ. Res. Lett., 9, 074014,
https://doi.org/10.1088/1748-9326/9/7/074014, 2014a.
Yi, S., Wischnewski, K., Langer, M., Muster, S., and Boike, J.: Freeze/thaw
processes in complex permafrost landscapes of northern Siberia simulated
using the TEM ecosystem model: impact of thermokarst ponds and lakes, Geosci.
Model Dev., 7, 1671–1689, https://doi.org/10.5194/gmd-7-1671-2014, 2014b.
Yin, G., Niu, F., Lin, Z., Luo, J., and Liu, M.: Effects of local factors
and climate on permafrost conditions and distribution in Beiluhe basin,
Qinghai-Tibet Plateau, China, Sci. Total Environ., 581–582,
472–485, 2017.
Yuan, F. M., Yi, S. H., McGuire, A. D., Johnson, K. D., Liang, J., Harden,
J. W., and Kurz, W. A.:Assessment of boreal forest historical C dynamics in
the Yukon River Basin: relative roles of warming and fire regime change,
Ecol. Appl., 22, 2091–2109, 2012.
Zhang, Z. F. and Ward, A. L.: Determining the porosity and saturated
hydraulic conductivity of binary mixtures, Vadose Zone J., 10, 313–321,
2011.
Zhuang, Q., Romanovsky, V. E., and McGuire, A. D.: Incorporation of a
permafrost model into a large-scale ecosystem model: Evaluation of temporal
and spatial scaling issues in simulating soil thermal dynamics, J. Geophys.
Res., 106, 33649–33670, 2001.
Zhuang, Q., Melillo, J., Kicklighter, D., Prinn, R. G., McGuire, A. D.,
Steudler, P. A., Felzer, B. S., and Hu, S.: Methane fluxes between
terrestrial ecosystems and the atmosphere at northern high latitudes during
the past century: A retrospective analysis with a process-based
biogeochemistry model, Global Biogeochem. Cy., 18, GB3010,
https://doi.org/10.1029/2004GB002239, 2004.
Zhuang, Q., He, J., Lu, Y., Ji, L., Xiao, J., and Luo, T.: Carbon dynamics
of terrestrial ecosystems on the Tibetan Plateau during the 20th century: an
analysis with a process-based biogeochemical model, Global Ecol. Biogeogr.,
19, 649–662, 2010.
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.
Download
The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.
- Article
(3012 KB) - Full-text XML
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.
Coarse-fragment soil on the Qinghai–Tibetan Plateau has different thermal and hydrological...
