Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-865-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-14-865-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 Feb 2022
Data description paper |
| 24 Feb 2022
| 24 Feb 2022
New high-resolution estimates of the permafrost thermal state and hydrothermal conditions over the Northern Hemisphere
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou 730000, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Xin Li
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan
Plateau Earth System, Environment and Resources, Institute of Tibetan
Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Guodong Cheng
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou 730000, China
Institute of Urban Study, Shanghai Normal University, Shanghai 200234,
China
Jingxin Che
School of Science, Nanchang Institute of Technology, Nanchang 330099, China
Juha Aalto
Department of Geosciences and Geography, University of Helsinki, P.O.
Box 64, Gustaf Hällströmin katu 2a, 00014 Helsinki, Finland
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki,
Finland
Olli Karjalainen
Geography Research Unit, University of Oulu, P.O. Box 8000, 90014,
Oulu, Finland
Jan Hjort
Geography Research Unit, University of Oulu, P.O. Box 8000, 90014,
Oulu, Finland
Miska Luoto
Department of Geosciences and Geography, University of Helsinki, P.O.
Box 64, Gustaf Hällströmin katu 2a, 00014 Helsinki, Finland
Huijun Jin
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou 730000, China
Institute of Cold Regions Science and Engineering and School of Civil
Engineering, Northeast Forestry University, Harbin 150040, China
Jaroslav Obu
Department of Geosciences, University of Oslo, Postboks 1047
Blindern, 0316 Oslo, Norway
Masahiro Hori
Earth Observation Research Center, Japan Aerospace Exploration
Agency, 2-1-1, Sengen, Tsukuba, Ibaraki 305-8505, Japan
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou 730000, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Xiaoli Chang
School of Resource and Environment and Safety Engineering, Hunan
University of Science and Technology, Xiangtan 411201, China
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Wenjun Tang, Kun Yang, Jun Qin, Xin Li, and Xiaolei Niu
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Tao Che, Xin Li, Shaomin Liu, Hongyi Li, Ziwei Xu, Junlei Tan, Yang Zhang, Zhiguo Ren, Lin Xiao, Jie Deng, Rui Jin, Mingguo Ma, Jian Wang, and Xiaofan Yang
Earth Syst. Sci. Data, 11, 1483–1499, https://doi.org/10.5194/essd-11-1483-2019, https://doi.org/10.5194/essd-11-1483-2019, 2019
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Olli Karjalainen, Miska Luoto, Juha Aalto, and Jan Hjort
The Cryosphere, 13, 693–707, https://doi.org/10.5194/tc-13-693-2019, https://doi.org/10.5194/tc-13-693-2019, 2019
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The Cryosphere, 12, 2803–2819, https://doi.org/10.5194/tc-12-2803-2018, https://doi.org/10.5194/tc-12-2803-2018, 2018
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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.
Youhua Ran, Xin Li, and Guodong Cheng
The Cryosphere, 12, 595–608, https://doi.org/10.5194/tc-12-595-2018, https://doi.org/10.5194/tc-12-595-2018, 2018
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Approximately 88 % of the permafrost area in the 1960s has been thermally degraded in the past half century over the Qinghai–Tibetan Plateau. The mean elevations of the very cold, cold, cool, warm, very warm, and likely thawing permafrost areas increased by 88 m, 97 m, 155 m, 185 m, 161 m, and 250 m, respectively. This degradation may lead to increases in risks to infrastructure, flood, reductions in ecosystem resilience, and positive climate feedback.
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.
Xicai Pan, Yanping Li, Qihao Yu, Xiaogang Shi, Daqing Yang, and Kurt Roth
The Cryosphere, 10, 1591–1603, https://doi.org/10.5194/tc-10-1591-2016, https://doi.org/10.5194/tc-10-1591-2016, 2016
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Using a 9-year dataset in conjunction with a process-based model, we verify that the common assumption of a considerably smaller thermal conductivity in the thawed season than the frozen season is not valid at a site with a stratified active layer on the Qinghai–Tibet Plateau (QTP). The unique hydraulic and thermal mechanism in the active layer challenges the concept of thermal offset used in conceptual permafrost models and hints at the reason for rapid permafrost warming on the QTP.
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
X. Pan, Q. Yu, and Y. You
The Cryosphere Discuss., https://doi.org/10.5194/tcd-8-6117-2014, https://doi.org/10.5194/tcd-8-6117-2014, 2014
Revised manuscript not accepted
L. Zhao, L. Wang, X. Liu, H. Xiao, Y. Ruan, and M. Zhou
Hydrol. Earth Syst. Sci., 18, 4129–4151, https://doi.org/10.5194/hess-18-4129-2014, https://doi.org/10.5194/hess-18-4129-2014, 2014
W. Tian, X. Li, G.-D. Cheng, X.-S. Wang, and B. X. Hu
Hydrol. Earth Syst. Sci., 16, 4707–4723, https://doi.org/10.5194/hess-16-4707-2012, https://doi.org/10.5194/hess-16-4707-2012, 2012
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TPRoGI: a comprehensive rock glacier inventory for the Tibetan Plateau using deep learning
Modern air, englacial and permafrost temperatures at high altitude on Mt Ortles (3905 m a.s.l.), in the eastern European Alps
Super-high-resolution aerial imagery datasets of permafrost landscapes in Alaska and northwestern Canada
A new 2010 permafrost distribution map over the Qinghai–Tibet Plateau based on subregion survey maps: a benchmark for regional permafrost modeling
Long-term energy balance measurements at three different mountain permafrost sites in the Swiss Alps
Permafrost, active layer, and meteorological data (2010–2020) at the Mahan Mountain relict permafrost site of northeastern Qinghai–Tibet Plateau
A synthesis dataset of permafrost thermal state for the Qinghai–Tibet (Xizang) Plateau, China
An integrated observation dataset of the hydrological and thermal deformation in permafrost slopes and engineering infrastructure in the Qinghai–Tibet Engineering Corridor
A 1 km resolution soil organic carbon dataset for frozen ground in the Third Pole
Historical and recent aufeis in the Indigirka River basin (Russia)
A 16-year record (2002–2017) of permafrost, active-layer, and meteorological conditions at the Samoylov Island Arctic permafrost research site, Lena River delta, northern Siberia: an opportunity to validate remote-sensing data and land surface, snow, and permafrost models
A long-term (2002 to 2017) record of closed-path and open-path eddy covariance CO2 net ecosystem exchange fluxes from the Siberian Arctic
A synthesis dataset of permafrost-affected soil thermal conditions for Alaska, USA
Northern Hemisphere surface freeze–thaw product from Aquarius L-band radiometers
A 20-year record (1998–2017) of permafrost, active layer and meteorological conditions at a high Arctic permafrost research site (Bayelva, Spitsbergen)
High-resolution elevation mapping of the McMurdo Dry Valleys, Antarctica, and surrounding regions
PeRL: a circum-Arctic Permafrost Region Pond and Lake database
An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing
Soraya Kaiser, Julia Boike, Guido Grosse, and Moritz Langer
Earth Syst. Sci. Data, 16, 3719–3753, https://doi.org/10.5194/essd-16-3719-2024, https://doi.org/10.5194/essd-16-3719-2024, 2024
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Arctic warming, leading to permafrost degradation, poses primary threats to infrastructure and secondary ecological hazards from possible infrastructure failure. Our study created a comprehensive Alaska inventory combining various data sources with which we improved infrastructure classification and data on contaminated sites. This resource is presented as a GeoPackage allowing planning of infrastructure damage and possible implications for Arctic communities facing permafrost challenges.
Xiaoqing Peng, Guangshang Yang, Oliver W. Frauenfeld, Xuanjia Li, Weiwei Tian, Guanqun Chen, Yuan Huang, Gang Wei, Jing Luo, Cuicui Mu, and Fujun Niu
Earth Syst. Sci. Data, 16, 2033–2045, https://doi.org/10.5194/essd-16-2033-2024, https://doi.org/10.5194/essd-16-2033-2024, 2024
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It is important to know about the distribution of thermokarst landscapes. However, most work has been done in the permafrost regions of the Qinghai–Tibetan Plateau, except for the Qilian Mountains in the northeast. Here we used satellite images and field work to investigate and analyze its potential driving factors. We found a total of 1064 hillslope thermokarst (HT) features in this area, and 82 % were initiated in the last 10 years. These findings will be significant for the next predictions.
Raul-David Şerban, Huijun Jin, Mihaela Şerban, Giacomo Bertoldi, Dongliang Luo, Qingfeng Wang, Qiang Ma, Ruixia He, Xiaoying Jin, Xinze Li, Jianjun Tang, and Hongwei Wang
Earth Syst. Sci. Data, 16, 1425–1446, https://doi.org/10.5194/essd-16-1425-2024, https://doi.org/10.5194/essd-16-1425-2024, 2024
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A particular observational network for ground surface temperature (GST) has been established on the northeastern Qinghai–Tibet Plateau, covering various environmental conditions and scales. This analysis revealed the substantial influences of the land cover on the spatial variability in GST over short distances (<16 m). Improving the monitoring of GST is important for the biophysical processes at the land–atmosphere boundary and for understanding the climate change impacts on cold environments.
Zhangyu Sun, Yan Hu, Adina Racoviteanu, Lin Liu, Stephan Harrison, Xiaowen Wang, Jiaxin Cai, Xin Guo, Yujun He, and Hailun Yuan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-28, https://doi.org/10.5194/essd-2024-28, 2024
Revised manuscript accepted for ESSD
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We propose a new dataset, TPRoGI [v1.0], encompassing rock glaciers in the entire Tibetan Plateau. We used a neural network, DeepLabv3+, and images from Planet Basemaps. The inventory identified 44,273 rock glaciers, covering 6,000 km2, mainly at elevations of 4,000 to 5,500 m.a.s.l. The dataset, with details on distribution and characteristics, aids in understanding permafrost distribution, mountain hydrology, and climate impacts in High Mountain Asia, filling a knowledge gap.
Luca Carturan, Fabrizio De Blasi, Roberto Dinale, Gianfranco Dragà, Paolo Gabrielli, Volkmar Mair, Roberto Seppi, David Tonidandel, Thomas Zanoner, Tiziana Lazzarina Zendrini, and Giancarlo Dalla Fontana
Earth Syst. Sci. Data, 15, 4661–4688, https://doi.org/10.5194/essd-15-4661-2023, https://doi.org/10.5194/essd-15-4661-2023, 2023
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This paper presents a new dataset of air, englacial, soil surface and rock wall temperatures collected between 2010 and 2016 on Mt Ortles, which is the highest summit of South Tyrol, Italy. Details are provided on instrument type and characteristics, field methods, and data quality control and assessment. The obtained data series are available through an open data repository. This is a rare dataset from a summit area lacking observations on permafrost and glaciers and their climatic response.
Tabea Rettelbach, Ingmar Nitze, Inge Grünberg, Jennika Hammar, Simon Schäffler, Daniel Hein, Matthias Gessner, Tilman Bucher, Jörg Brauchle, Jörg Hartmann, Torsten Sachs, Julia Boike, and Guido Grosse
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-193, https://doi.org/10.5194/essd-2023-193, 2023
Revised manuscript accepted for ESSD
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Permafrost landscapes in the Arctic are rapidly changing due to climate warming. We here publish aerial images and elevation models with very high spatial detail that help study these landscapes in northwestern Canada and Alaska. The images were collected using the Modular Aerial Camera System (MACS). This dataset has significant implications for understanding permafrost landscape dynamics in response to climate change. It is publicly available for further research.
Zetao Cao, Zhuotong Nan, Jianan Hu, Yuhong Chen, and Yaonan Zhang
Earth Syst. Sci. Data, 15, 3905–3930, https://doi.org/10.5194/essd-15-3905-2023, https://doi.org/10.5194/essd-15-3905-2023, 2023
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This study provides a new 2010 permafrost distribution map of the Qinghai–Tibet Plateau (QTP), using an effective mapping approach based entirely on satellite temperature data, well constrained by survey-based subregion maps, and considering the effects of local factors. The map shows that permafrost underlies about 41 % of the total QTP. We evaluated it with borehole observations and other maps, and all evidence indicates that this map has excellent accuracy.
Martin Hoelzle, Christian Hauck, Tamara Mathys, Jeannette Noetzli, Cécile Pellet, and Martin Scherler
Earth Syst. Sci. Data, 14, 1531–1547, https://doi.org/10.5194/essd-14-1531-2022, https://doi.org/10.5194/essd-14-1531-2022, 2022
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With ongoing climate change, it is crucial to understand the interactions of the individual heat fluxes at the surface and within the subsurface layers, as well as their impacts on the permafrost thermal regime. A unique set of high-altitude meteorological measurements has been analysed to determine the energy balance at three mountain permafrost sites in the Swiss Alps, where data have been collected since the late 1990s in collaboration with the Swiss Permafrost Monitoring Network (PERMOS).
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.
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.
Olga Makarieva, Andrey Shikhov, Nataliia Nesterova, and Andrey Ostashov
Earth Syst. Sci. Data, 11, 409–420, https://doi.org/10.5194/essd-11-409-2019, https://doi.org/10.5194/essd-11-409-2019, 2019
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Aufeis is formed through a complex interconnection between river water and groundwater. The dynamics of aufeis assessed by the analysis of remote sensing data can be viewed as an indicator of groundwater changes in warming climate which are otherwise difficult to be observed naturally in remote arctic areas. The spatial geodatabase developed shows that aufeis formation conditions may have changed between the mid-20th century and the present in the Indigirka River basin.
Julia Boike, Jan Nitzbon, Katharina Anders, Mikhail Grigoriev, Dmitry Bolshiyanov, Moritz Langer, Stephan Lange, Niko Bornemann, Anne Morgenstern, Peter Schreiber, Christian Wille, Sarah Chadburn, Isabelle Gouttevin, Eleanor Burke, and Lars Kutzbach
Earth Syst. Sci. Data, 11, 261–299, https://doi.org/10.5194/essd-11-261-2019, https://doi.org/10.5194/essd-11-261-2019, 2019
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Long-term observational data are available from the Samoylov research site in northern Siberia, where meteorological parameters, energy balance, and subsurface observations have been recorded since 1998. This paper presents the temporal data set produced between 2002 and 2017, explaining the instrumentation, calibration, processing, and data quality control. Furthermore, we present a merged dataset of the parameters, which were measured from 1998 onwards.
David Holl, Christian Wille, Torsten Sachs, Peter Schreiber, Benjamin R. K. Runkle, Lutz Beckebanze, Moritz Langer, Julia Boike, Eva-Maria Pfeiffer, Irina Fedorova, Dimitry Y. Bolshianov, Mikhail N. Grigoriev, and Lars Kutzbach
Earth Syst. Sci. Data, 11, 221–240, https://doi.org/10.5194/essd-11-221-2019, https://doi.org/10.5194/essd-11-221-2019, 2019
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We present a multi-annual time series of land–atmosphere carbon dioxide fluxes measured in situ with the eddy covariance technique in the Siberian Arctic. In arctic permafrost regions, climate–carbon feedbacks are amplified. Therefore, increased efforts to better represent these regions in global climate models have been made in recent years. Up to now, the available database of in situ measurements from the Arctic was biased towards Alaska and records from the Eurasian Arctic were scarce.
Kang Wang, Elchin Jafarov, Irina Overeem, Vladimir Romanovsky, Kevin Schaefer, Gary Clow, Frank Urban, William Cable, Mark Piper, Christopher Schwalm, Tingjun Zhang, Alexander Kholodov, Pamela Sousanes, Michael Loso, and Kenneth Hill
Earth Syst. Sci. Data, 10, 2311–2328, https://doi.org/10.5194/essd-10-2311-2018, https://doi.org/10.5194/essd-10-2311-2018, 2018
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Ground thermal and moisture data are important indicators of the rapid permafrost changes in the Arctic. To better understand the changes, we need a comprehensive dataset across various sites. We synthesize permafrost-related data in the state of Alaska. It should be a valuable permafrost dataset that is worth maintaining in the future. On a wider level, it also provides a prototype of basic data collection and management for permafrost regions in general.
Michael Prince, Alexandre Roy, Ludovic Brucker, Alain Royer, Youngwook Kim, and Tianjie Zhao
Earth Syst. Sci. Data, 10, 2055–2067, https://doi.org/10.5194/essd-10-2055-2018, https://doi.org/10.5194/essd-10-2055-2018, 2018
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This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the EASE-Grid 2.0 with a resolution of 36 km. To evaluate the product, we compared it with the resampled 37 GHz FT Earth Science Data Record during the overlapping period between 2011 and 2014. The FT-AP ensures, with the SMAP mission that is still in operation, an L-band passive FT monitoring continuum with NASA’s space-borne radiometers, for a period beginning in August 2011.
Julia Boike, Inge Juszak, Stephan Lange, Sarah Chadburn, Eleanor Burke, Pier Paul Overduin, Kurt Roth, Olaf Ippisch, Niko Bornemann, Lielle Stern, Isabelle Gouttevin, Ernst Hauber, and Sebastian Westermann
Earth Syst. Sci. Data, 10, 355–390, https://doi.org/10.5194/essd-10-355-2018, https://doi.org/10.5194/essd-10-355-2018, 2018
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A 20-year data record from the Bayelva site at Ny-Ålesund, Svalbard, is presented on meteorology, energy balance components, surface and subsurface observations. This paper presents the data set, instrumentation, calibration, processing and data quality control. The data show that mean annual, summer and winter soil temperature data from shallow to deeper depths have been warming over the period of record, indicating the degradation and loss of permafrost at this site.
Andrew G. Fountain, Juan C. Fernandez-Diaz, Maciej Obryk, Joseph Levy, Michael Gooseff, David J. Van Horn, Paul Morin, and Ramesh Shrestha
Earth Syst. Sci. Data, 9, 435–443, https://doi.org/10.5194/essd-9-435-2017, https://doi.org/10.5194/essd-9-435-2017, 2017
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We present detailed surface elevation measurements for the McMurdo Dry Valleys, Antarctica, and surroundings, derived from aerial lidar surveys flown in the austral summer of 2014–2015 as part of an effort to understand landscape changes over the past decade. Lidar return density varied from 2 to > 10 returns per square meter with an average of about 5 returns per square meter. vertical and horizontal accuracies are estimated to be 7 cm and 3 cm, respectively.
Sina Muster, Kurt Roth, Moritz Langer, Stephan Lange, Fabio Cresto Aleina, Annett Bartsch, Anne Morgenstern, Guido Grosse, Benjamin Jones, A. Britta K. Sannel, Ylva Sjöberg, Frank Günther, Christian Andresen, Alexandra Veremeeva, Prajna R. Lindgren, Frédéric Bouchard, Mark J. Lara, Daniel Fortier, Simon Charbonneau, Tarmo A. Virtanen, Gustaf Hugelius, Juri Palmtag, Matthias B. Siewert, William J. Riley, Charles D. Koven, and Julia Boike
Earth Syst. Sci. Data, 9, 317–348, https://doi.org/10.5194/essd-9-317-2017, https://doi.org/10.5194/essd-9-317-2017, 2017
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Waterbodies are abundant in Arctic permafrost lowlands. Most waterbodies are ponds with a surface area smaller than 100 x 100 m. The Permafrost Region Pond and Lake Database (PeRL) for the first time maps ponds as small as 10 x 10 m. PeRL maps can be used to document changes both by comparing them to historical and future imagery. The distribution of waterbodies in the Arctic is important to know in order to manage resources in the Arctic and to improve climate predictions in the Arctic.
Youngwook Kim, John S. Kimball, Joseph Glassy, and Jinyang Du
Earth Syst. Sci. Data, 9, 133–147, https://doi.org/10.5194/essd-9-133-2017, https://doi.org/10.5194/essd-9-133-2017, 2017
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A new freeze–thaw (FT) Earth system data record (ESDR) was developed from satellite passive microwave remote sensing that quantifies the daily landscape frozen or non-frozen status over a 25 km resolution global grid and 1979–2014 record. The FT-ESDR shows favorable accuracy and performance, enabling new studies of climate change and frozen season impacts on surface water mobility and ecosystem processes.
Cited articles
Aalto, J., Karjalainen, O., Hjort, J., and Luoto, M.: Statistical
forecasting of current and future Circum-Arctic ground temperatures and
active layer thickness, Geophys. Res. Lett., 45, 4889–4898, 2018.
Abu-Hamdeh, N. H.: Thermal properties of soils as affected by density and
water content, Biosyst Eng., 86, 97–102, 2003.
Ali, S. N., Quamar, M. F., Phartiyal, B., and Sharma, A.: Need for
permafrost researches in Indian Himalaya, J. Clim. Chang., 4, 33–36,
2018.
Allard, M., Sarrazin, D., and L'Hérault, E.: Borehole and
near-surface ground temperatures in northeastern Canada, Version 1.3
(1988–2014), Nordicana D [data set], https://doi.org/10.5885/45291SL-34F28A9491014AFD,
2015.
Awad, M. and Khanna, R.: Support Vector Regression, in: Efficient Learning
Machines, Apress, Berkeley, CA, https://doi.org/10.1007/978-1-4302-5990-9_4, 2015.
Bergen, K. J., Johnson, P. A., Maarten, V., and Beroza, G. C.: Machine
learning for data-driven discovery in solid Earth
geoscience, Science, 363, eaau0323, https://doi.org/10.1126/science.aau0323, 2019.
Biskaborn, B. K., Lanckman, J.-P., Lantuit, H., Elger, K., Streletskiy, D. A., Cable, W. L., and Romanovsky, V. E.: The new database of the Global Terrestrial Network for Permafrost (GTN-P), Earth Syst. Sci. Data, 7, 245–259, https://doi.org/10.5194/essd-7-245-2015, 2015.
Biskaborn, B. K., Smith, S. L., Noetzli, J., Matthes, H., Vieira, G.,
Streletskiy, D. A., and Allard, M.: Permafrost is warming at a global
scale, Nat. Commun., 10, 264, https://doi.org/10.1038/s41467-018-08240-4, 2019.
Blackett, R.: Utah Temperature-Depth Log Compilation, Utah Geological Survey
[data set],
http://search.geothermaldata.org/dataset/utah-temperature-depth-log-compilation (last access: 20 August 2015),
2013.
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, 2001.
Brown, J., Ferrians, O., Heginbottom, J. A., and Melnikov, E.: Circum-Arctic Map of Permafrost and Ground-Ice Conditions, Version 2, Boulder, Colorado USA, NSIDC: National Snow and Ice Data Center [data set], https://doi.org/10.7265/skbg-kf16, 2002.
Brown, J., Hinkel, K. M., and Nelson, F. E.: The circumpolar active layer
monitoring (CALM) program: research designs and initial results, Polar
Geogr., 24, 166–258, 2000.
Cao, B., Gruber, S., Zhang, T., Li, L., Peng, X., Wang, K., Zheng, L., Shao,
W., and Guo, H.: Spatial variability of active layer thickness detected by
ground-penetrating radar in the Qilian Mountains, Western China, J. Geophys.
Res. Earth. Surf., 122, 574–591, 2017.
Cao, B., Zhang, T., Peng, X., Mu, C., Wang, Q., Zheng, L., and Zhong, X.:
Thermal characteristics and recent changes of permafrost in the upper
reaches of the Heihe River basin, Western China, J. Geophys. Res.-Atmos., 123, 7935–7949, 2018.
Cao, B., Zhang, T., Wu, Q., Sheng, Y., Zhao, L., and Zou, D.: Permafrost
zonation index map and statistics over the Qinghai-Tibet Plateau based on
field evidence, Permafrost Periglac. Process., 30, 178–194, 2019.
Chadburn, S. E., Burke, E. J., Cox, P. M., Friedlingstein, P., Hugelius, G.,
and Westermann, S.: An observation-based constraint on permafrost loss as a
function of global warming, Nat. Clim. Change, 7, 340–344, 2017.
Chang, X. L.: Thermal effect of vegetation and snow cover on the underlying
permafrost and soils in the active layer in the northern Da Xiang'anling
Mountains, Northeastern China, PhD thesis, Univ. Chinese Acad. Sci.,
1–138, https://d.wanfangdata.com.cn/thesis/Y2031477 (last access: 18 July 2020), 2011 (in Chinese, English abstract).
Chen, T. Q. and Guestrin, C.: XGBoost: A Scalable Tree Boosting System, in:
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining, ACM, New York, NY, USA, 785–794, https://doi.org/10.1145/2939672.2939785, 2016.
Cheng, G.: Problems on zonation of high-altitude permafrost, Acta. Geogr.
Sin., 39, 185–193, 1984 (in Chinese).
Cheng, G.: A roadbed cooling approach for the construction of Qinghai–Tibet
Railway, Cold Reg. Sci. Technol., 42, 169–176, 2005.
Cheng, G. and Jin, H. J.: Permafrost and groundwater on the Qinghai-Tibet
Plateau and in northeast China, Hydrogeol. J., 21, 5–23, 2013.
Cheng, G. and Wu, T.: Responses of permafrost to climate change and their
environmental significance, Qinghai-Tibet Plateau, J. Geophys. Res. Earth.
Surf., 112, 93–104, 2007.
Crow, H. L., Good, R. L., Hunter, J. A., Burns, R. A., Reman, A., and
Russell, H. A. J.: Borehole geophysical logs in unconsolidated sediments
across Canada, Geological Survey of Canada [data set], Open File 7591,
https://doi.org/10.4095/295753, 2015.
Curran, J., Rancan, H., and French, M.: New Jersey Well Logs, New
Jersey Geological and Water Survey [data set],
http://search.geothermaldata.org/dataset/new-jersey-well-logs (last access: 20 January 2016), 2013.
Czajkowski, J.: Washington Well Logs. Washington Division of Geology and
Earth Resources, Department of Natural Resources [data set],
http://search.geothermaldata.org/dataset/washington-well-logs (last access: 10 January 2016), 2012.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach,
H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M.,
Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart,
F.: The ERA-Interim reanalysis: configuration and performance of the data
assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, 2011.
Dvornikov, Y., Leibmann, M., Heim, B., Bartsch, A., Haas, A., Khomutov, A.,
Gubarkov, A., Mikhaylova, M., Mullanurov, D., Widhalm, B., Skorospekhova,
T., and Fedorova, I.: Geodatabase and WebGIS project for long-term
permafrost monitoring at the Vaskiny Dachi research station, Yamal,
Russia, Polarforschung, 85, 107–115, 2016.
Ednie, M., Chartrand, J., Smith, S. L., Duchesne, C., and Riseborough, D. W.:
Report on 2011 Field Activities and Collection of Ground Thermal and Active
Layer Data in the Mackenzie Corridor Completed Under Northwest Territories
Science Licence #14918, Geological Survey of Canada [data
set], Open File 7231, https://doi.org/10.4095/291982, 2012.
ESA: Land Cover CCI Product User Guide Version 2.0, http://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf, (last access: 4 March 2021), 2017.
Fick, S. E. and Hijmans, R. J.: WorldClim 2: new 1km spatial resolution
climate surfaces for global land areas, Int. J. Climatol., 37,
4302–4315, 2017.
Friedman, J. H.: Greedy function approximation: a gradient boosting
machine, Ann. Stat., 29, 1189–1232, 2001.
Gallo, K., Hale, R., Tarpley, D., and Yu, Y.: Evaluation of the relationship
between air and land surface temperature under clear-and cloudy-sky
conditions, J. Appl. Meteorol. Climatol., 50, 767–775, 2011.
Gao, T., Zhang, T., Cao, L., Kang, S., and Sillanpää, M.: Reduced
winter runoff in a mountainous permafrost region in the northern Tibetan
Plateau, Cold Reg. Sci. Technol., 126, 36–43, 2016.
Geological Survey of Norway (NGU): Permafrost Svalbard, The NORPERM Permafrost Database [data
set], http://geo.ngu.no/kart/permafrost_svalbard (last access: 23 April 2017), 2016.
Geophysical Institute Permafrost Laboratory (GIPL): Site Information and
Historical Data Access, http://permafrost.gi.alaska.edu/sites_list (last access: 26 January 2016), 2010.
Gosnold, W.: Nebraska Temperature-Depth Data and Profiles, University of
North Dakota [data set],
http://search.geothermaldata.org/dataset/nebraska-temperature-depth-data-and-profiles (last access: 10 March 2016),
2013.
Gruber, S.: Derivation and analysis of a high-resolution estimate of global permafrost zonation, The Cryosphere, 6, 221–233, https://doi.org/10.5194/tc-6-221-2012, 2012.
Harris, C., Haeberli, W., Vonder Mühll, D., and King, L.: Permafrost
monitoring in the high mountains of Europe: the PACE project in its global
context, Permafrost Periglac. Process., 12, 3–11, 2001.
Harrison III, W. B.: Michigan Well Log Observation Data, Western Michigan
University – Geosciences Department [data set],
http://search.geothermaldata.org/dataset/michigan-well-log-observation-data (last access: 10 March 2016),
2012.
Hastie, T. J. and Tibshirani, R. J.: Generalized additive models, Routledge, https://doi.org/10.1201/9780203753781, 2017.
He, R., Jin, H., Chang, X., Wang, Y., and Wang, L.: Freeze-thaw processes of
active-layer soils in the Nanweng'he River National Natural Reserve in the
Da Xing'anling Mountains, northern Northeast China, Sci. Cold. Arid.
Reg., 10, 104–113, 2018.
Heginbottom, J. A.: Permafrost mapping: a review, Prog. Phys. Geogr., 26,
623–642, 2002.
Heginbottom, J. A., Brown, J., Melnikov, E. S., and Ferrians Jr, O. J.:
Circumarctic map of permafrost and ground ice conditions, Proc. Int. Conf.
Permafrost. Natl. Snow Ice Data Cent./World Data Cent. Glaciol., Boulder,
CO, 2, 1132–1136, 1993.
Hengl, T., Mendes de Jesus, J., Heuvelink, G. B., Ruiperez Gonzalez, M.,
Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng,
X., Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R.
A., Batjes, N. H., Leenaars, J. G., and Ribeiro, E., Wheeler, I., Mantel,
S., and Kempen, B.: SoilGrids250m: Global gridded soil information based on
machine learning, PLoS One, 12, https://doi.org/10.1371/journal.pone.0169748, 2017.
Hjort, J., Karjalainen, O., Aalto, J., Westermann, S., Romanovsky, V. E.,
Nelson, F. E., Etzelmüller, B., and Luoto, M.: Degrading permafrost puts
Arctic infrastructure at risk by mid-century, Nat. Commun., 9, 5147, https://doi.org/10.1038/s41467-018-07557-4, 2018.
Hori, M., Sugiura, K., Kobayashi, K., Aoki, T., Tanikawa, T., Kuchiki, K.,
Niwano, M., and Enomoto, H.: A 38-year (1978–2015) Northern Hemisphere daily
snow cover extent product derived using consistent objective criteria from
satellite-borne optical sensors, Remote Sens. Environ., 191, 402–418, 2017.
Huang, S., Pollack, H. N., and Shen, P.-Y.: Temperature trends over
the past five centuries reconstructed from borehole temperatures, Nature,
403, 756–758, 2000.
Jin, H., Lü, L., and He, R.: A new aridity-based classification of
permafrost zones on the Tibetan Plateau, J. Glaciol. Geocryol., 36,
1049–1057, 2014 (in Chinese, English abstract).
Justice, C. O., Townshend, J. R. G., Vermote, E. F., Masuoka, E., Wolfe, R.
E., Saleous, N., Roy, D. P., and Morisette, J. T.: An overview of MODIS Land
data processing and product status, Remote Sens. Environ., 83, 3–15,
2002.
Karatzoglou, A., Meyer, D., and Hornik, K.: Support vector machines in R, J.
Stat. Softw., 15, 1–28, 2006.
Karjalainen, O., Aalto, J., Luoto, M., Westermann, S., Romanovsky, V. E., Nelson, F. E., Etzelmüller, B., and Hjort, J.: Circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments, Sci. Data, 6, 1–16, 2019.
Kellerer-Pirklbauer, A., Bartsch, A., Gitschthaler, C., Reisenhofer, S.,
Weyss, G., Riedl, C., and Avian, M.: A national strategy for a long-term
monitoring of permafrost and periglacial processes and their relationship to
natural hazard prevention in Austria, EGUGA, 18, EPSC2016-15245, 2016.
Kelley, S.: New Mexico Temperature-Depth Logs and Graphic Profiles, New
Mexico Bureau of Geology & Mineral Resources [data set],
http://search.geothermaldata.org/dataset/new-mexico-temperature-depth-logs-and-graphic-profiles (last access: 1 April 2016),
2011.
Lehner, B. and Döll, P.: Development and validation of a global database
of lakes, reservoirs and wetlands, J. Hydrol., 296, 1–22, 2004.
Li, J., Sheng, Y., Chen, J., Zhang, B., Wu, J., and Zang, X.: Characteristics
of ground temperatures and influencing factors of permafrost development and
distribution in the source region of Datong River, Prog. Geogr., 30,
827–836, 2011 (in Chinese, English abstract).
Li, J., Sheng, Y., and Wu, J.: Mapping frozen soil distribution and modeling
permafrost stability in the Source Area of the Yellow River, Sci. Geogr.
Sin., 36, 588–596, 2016 (in Chinese, English abstract).
Li, X., Jin, H., He, R., Huang, Y., Wang, H., Luo, D., Jin, X., Lv, L.,
Wang, L., Li, W., Wei, C., Chang, X., Yang, S., and Yu, S.: Effects of forest
fires on the permafrost environment in the northern Da Xing'anling (Hinggan)
mountains, Northeast China, Permafrost Periglac. Process., 30, 163–177,
2019.
Li, X., Che, T., Li, X., Wang, L., Duan, A., Shangguan, D., Pan, X., Fang,
M., and Bao, Q.: CASEarth Poles: Big data for the Three Poles, B. Am.
Meteorol. Soc., 101, E1475–E1491, 2020a.
Li, X., Jin, H., Wang, H., Wu, X., Huang, Y., He, R., Luo, D., and Jin, X.:
Distributive features of soil carbon and nutrients in permafrost regions
affected by forest fires in northern Da Xing'anling (Hinggan) Mountains, NE
China, Catena, 185, 104304, https://doi.org/10.1016/j.catena.2019.104304, 2020b.
Liaw, A. and Wiener, M.: Classification and regression by randomForest, R
News, 2, 18–22, 2002.
Liu, G. Y., Wang. W., Zhao, L., Chen, J., Pang, Q. Q., Wang, Z. W., and Du, E.
J.: Using transient electromagnetic method to sound permafrost depth in the
West Kunlun Mountains, J. Glaciol. Geocryol., 37, 38–48, 2015 (in
Chinese, English abstract).
Luo, D., Wu, Q., Jin, H., Marchenko, S. S., Lü, L., and Gao, S.: Recent
changes in the active layer thickness across the northern
hemisphere, Environ. Earth Sci., 75, 555, https://doi.org/10.1007/s12665-015-5229-2, 2016.
Luo, D., Jin, H., Jin, X., He, R., Li, X., Muskett, R. R., and Romanovsky, V.
E.: Elevation-dependent thermal regime and dynamics of frozen ground in the
Bayan Har Mountains, northeastern Qinghai-Tibet Plateau, southwest China,
Permafrost Periglac. Process., 29, 257–270, 2018a.
Luo, D., Jin, H., Wu, Q., Bense, V. F., He, R., Ma, Q., and Lü, L.:
Thermal regime of warm-dry permafrost in relation to ground surface
temperature in the Source Areas of the Yangtze and Yellow rivers on the
Qinghai-Tibet Plateau, SW China, Sci. Total Environ., 618, 1033–1045, 2018b.
Luo, D. L.: Monitoring, mapping and modeling of permafrost and active layer
processes in the Sources Areas of the Yellow River (SAYR) on Northeastern
Qinghai-Tibet Plateau, PhD thesis, Univ. Chinese Acad. Sci., 1–119, 2012
(in Chinese, English abstract).
Maine Geological Survey: Maine Well Headers, National Geothermal Data System [data set],
http://search.geothermaldata.org/dataset/maine-well-headers (last access: 16 April 2016), 2014.
Mair, V., Zischg, A., Lang, K., Tonidandel, D., Krainer, K.,
Kellerer-Pirklbauer, A., Deline, P., Schoeneich, P., Cremonese, E.,
Pogliotti, P., Gruber, S., and Böckli, L.: PermaNET-Permafrost Long-term
Monitoring Network: Synthesis report, Int. Res. Soc. INTERPRAEVENT, 2011.
Nelson, F. E.: Permafrost zonation in eastern Canada: a review of published
maps, Phys. Geogr., 10, 231–246, 1989.
Nevada Bureau of Mines and Geology: Nevada Borehole Temperatures, National Geothermal Data System
[data set],
http://search.geothermaldata.org/dataset/nevada-borehole-temperatures (last access: 20 April 2016), 2014.
Niewendorp, C. A.: Oregon Well Logs, Oregon Department of Geology and
Mineral Industries [data set],
http://search.geothermaldata.org/dataset/oregon-well-logs (last access: 11 April 2016), 2012.
Noetzli, J., Gruber, S., Kohl, T., Salzmann, N., and Haeberli, W.:
Three-dimensional distribution and evolution of permafrost temperatures in
idealized high-mountain topography, J. Geophys. Res., 112, F02S13,
https://doi.org/10.1029/2006JF000545, 2017.
NSF Arctic Data Center: Network of Permafrost Observatories in Western
Alaska, Arctic Data Center [data set], https://doi.org/10.18739/A2D934,
2014.
Obu, J., Westermann, S., Bartsch, A., Berdnikov, N., Christiansen, H. H.,
Dashtseren, A., Delaloye, R., Elberling, B., Etzelmüller, B., Kholodov,
A., Khomutov, A., Kääb, A., Leibman, M. O., Lewkowicz, A. G., Panda,
S. K., Romanovsky, V., Way, R. G., Westergaard-Nielsen, A., Wu, T., Yamkhin,
J., and Zou, D.: Northern Hemisphere permafrost map based on TTOP modelling
for 2000–2016 at 1 km2 scale, Earth-Sci. Rev., 193, 299–316, 2019.
Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G.,
Heim, B., Hugelius, G., Irrgang, A., Kääb, A. M., Kroisleitner, C.,
Matthes, H., Nitze, I., Pellet, C., Seifert, F. M., Strozzi, T.,
Wegmüller, U., Wieczorek, M., and Wiesmann, A.: ESA Permafrost Climate
Change Initiative (Permafrost_cci): Permafrost Ground
Temperature for the Northern Hemisphere, v3.0, NERC EDS Centre for
Environmental Data Analysis,
https://doi.org/10.5285/b25d4a6174de4ac78000d034f500a268, 2021.
Ødegård, R. S., Isaksen, K., Eiken, T., and Sollid, J.
L.: MAGST in Mountain Permafrost, Dovrefjell, Southern
Norway, 2001–2006, Ninth International Conference on Permafrost,
University of Alaska Fairbanks, USA, in: Proceedings Volume 2, edited by: Kane D. L. and Hinkel, K. M., Institute of Northern Engineering, University of Alaska Fairbanks, 1311–1315,
ISBN 978-0-9800179-3-9, 2008.
Paetzhold, R. F.: Monthly Summaries of Soil Temperature and Soil Moisture at
Sites in China, Boulder, Colorado USA, NSIDC: National Snow and Ice Data
Center [data set], https://doi.org/10.7265/67qf-zj58, 2003.
Pan, H. L. and Mahrt, L.: Interaction between soil hydrology and
boundary-layer development, Bound. Lay. Meteorol., 38, 185–202, 1987.
Peter, M.: Modeling of permafrost temperatures in the Lena River Delta,
Siberia, based on remote sensing products, MS thesis, University of
Leipzig, hdl: 10013/epic.45589.d001, https://epic.awi.de/id/eprint/38041/ (last
access: 28 July 2019), 2015.
Qiao, Y., Zhao, L., Pang, Q., Chen, J., Zou, D., and Gao, Z.:
Characteristics of permafrost in Gerze county on the Tibetan Plateau, J.
Glaciol. Geocryol., 37, 1453–1460, 2015 (in Chinese, English abstract).
Qin, Y., Wu, T., Zhao, L., Wu, X., Li, R., Xie, C., and Liu, G.: Numerical
modeling of the active layer thickness and permafrost thermal state across
Qinghai-Tibetan Plateau, J. Geophys. Res.-Atmos., 122, 11–604, 2017.
Ran, Y., Li, X., Cheng, G., Zhang, T., Wu, Q., Jin, H., and Jin, R.:
Distribution of permafrost in China: an overview of existing permafrost
maps, Permafrost Periglac. Process., 23, 322–333, 2012.
Ran, Y., Li, X., and Cheng, G.: Climate warming over the past half century has led to thermal degradation of permafrost on the Qinghai–Tibet Plateau, The Cryosphere, 12, 595–608, https://doi.org/10.5194/tc-12-595-2018, 2018.
Ran, Y., Li, X., Cheng, G., Che, J., Aalto, J., Karjalainen, O., Hjort, J.,
Luoto, M., Jin, H., Obu, J., Hori, M., Yu, Q., and Chang, X.: High-resolution
datasets of permafrost thermal state and hydrothermal zonation in the
Northern Hemisphere, National Tibetan Plateau Data Center [data set],
https://doi.org/10.11888/Geocry.tpdc.271190, 2021a.
Ran, Y., Li, X., Cheng, G., Nan, Z., Che, J., Sheng, Y., Wu, Q., Jin, H.,
Luo, D., Tang, Z., and Wu, X.: Mapping the permafrost stability on the
Tibetan Plateau for 2005–2015, Sci. China: Earth Sci., 64, 62–79,
2021b.
Riseborough, D.: The effect of transient conditions on an equilibrium
permafrost-climate model, Permafrost Periglac. Process., 18, 21–32, 2007.
Riseborough, D., Shiklomanov, N., Etzelmüller, B., Gruber, S., and
Marchenko, S.: Recent advances in permafrost modelling, Permafrost Periglac.
Process., 19, 137–156, 2008.
Romanovsky, V. E. and Osterkamp, T. E.: Permafrost monitoring system in
Alaska: structure and results, Kriosfera Zemli, 5, 59–68, 2001 (in Russian).
Romanovsky, V. E., Smith, S. L., and Christiansen, H. H.: Permafrost thermal
state in the polar Northern Hemisphere during the international polar year
2007–2009: a synthesis, Permafrost Periglac. Process., 21, 106–116,
2010.
Schuur, E. A., Vogel, J. G., Crummer, K. G., Lee, H., Sickman, J. O., and
Osterkamp, T. E.: The effect of permafrost thaw on old carbon release and
net carbon exchange from tundra, Nature, 459, 556–559, 2009.
Sheng, Y., Li, J., Wu, J. C., Ye, B. S., and Wang, J.: Distribution patterns
of permafrost in the upper area of Shule River with the application of GIS
technique, J. China Univ. Min. Technol., 39, 32–39, 2010.
Sherstiukov, A.: Dataset of daily soil temperature up to 320 cm depth based
on meteorological stations of Russian Federation, RIHMI-WDC, 176,
224–232, 2012.
Shur, Y. L. and Jorgenson, M. T.: Patterns of permafrost formation and
degradation in relation to climate and ecosystems, Permafrost Periglac.
Process., 18, 7–19, 2007.
Smith, S. L. and Ednie, M.: Ground thermal data collection along the Alaska
Highway easement (KP 1559-1895) Yukon, summer 2014, Geological Survey of
Canada [data set], Open File 7762, https://doi.org/10.4095/295974, 2015.
Smith, S. L., Burgess, M. M., Riseborough, D., and Mark Nixon, F.: Recent
trends from Canadian permafrost thermal monitoring network sites, Permafrost
Periglac. Process., 16, 19–30, 2005.
Smith, S. L., Romanovsky, V. E., Lewkowicz, A. G., Burn, C. R., Allard, M.,
Clow, G. D., Yoshikawa, K., and Throop, J.: Thermal state of permafrost in
North America: a contribution to the international polar year, Permafrost
Periglac. Process., 21, 117–135, 2010.
Smith, S. L., Riseborough, D. W., Ednie, M., and Chartrand, J.: A Map and
Summary Database of Permafrost Temperatures in Nunavut, Canada, Geological
Survey of Canada [data set], Open File 7393, https://doi.org/10.4095/292615,
2013.
Streletskiy, D. A., Tananaev, N. I., Opel, T., Shiklomanov, N. I., Nyland,
K. E., Streletskaya, I. D., and Shiklomanov, A. I.: Permafrost hydrology in
changing climatic conditions: seasonal variability of stable isotope
composition in rivers in discontinuous permafrost, Environ. Res. Lett.,
10, 095003, https://doi.org/10.1088/1748-9326/10/9/095003, 2015.
Sun, Z. Z., Ma, W., Dang, H. M., Yun, H. B., and Wu, G. L.: Characteristics
and causes of embankment deformation for Qinghai-Tibet Railway in permafrost
regions, Rock Soil Mech., 34, 2667–2671, 2013 (in Chinese, English
abstract).
Tarnocai, C., Canadell, J. G., Schuur, E. A. G., Kuhry, P., Mazhitova, G.,
and Zimov, S.: Soil organic carbon pools in the northern circumpolar
permafrost region, Global Biogeochem. Cy., 23, https://doi.org/10.1029/2008GB003327, 2009.
Trabucco, A. and Zomer, R.: Global Aridity Index and Potential
Evapotranspiration (ET0) Climate Database v2, figshare [data set],
https://doi.org/10.6084/m9.figshare.7504448.v3, 2019.
Trenberth, K. E. and Shea, D. J.: Relationships between precipitation and
surface temperature, Geophys. Res. Lett., 32, https://doi.org/10.1029/2005GL022760, 2005.
University of North Dakota: Temperature at Depth Database, NGDS [data set],
http://geothermal.smu.edu/static/DownloadFilesButtonPage.htm (last access: 15 May 2016), 2014.
Van Everdingen, R. O.: Multi-Language Glossary of Permafrost and Related
Ground-Ice Terms, International Permafrost Association, https://globalcryospherewatch.org/reference/glossary_docs/Glossary_of_Permafrost_and_Ground-Ice_IPA_2005.pdf (last access: 2 April 2019), 2005.
Vapnik, V.: The Nature of Statistical Learning Theory, https://doi.org/10.1007/978-1-4757-2440-0, Springer, NY,
1995.
Virginia Division of Geology and Mineral Resources: Georgia Well Logs, NGDS [data
set], http://search.geothermaldata.org/dataset/georgia-well-logs (last access: 11 May 2016), 2012a.
Virginia Division of Geology and Mineral Resources: Virginia Well Logs, NGDS [data
set], http://search.geothermaldata.org/dataset/virginia-well-logs (last access: 11 May 2016), 2012b.
Wang, Q., Zhang, T., Wu, J., Peng, X., Zhong, X., Mu, C., and Cheng, G.:
Investigation on permafrost distribution over the upper reaches of the Heihe
River in the Qilian Mountains, J. Glaciol. Geocryol., 35, 19–25, 2013
(in Chinese, English abstract).
Wani, J. M., Thayyen, R. J., Gruber, S., Ojha, C. S. P., and Stumm, D.:
Single-year thermal regime and inferred permafrost occurrence in the upper
Ganglass catchment of the cold-arid Himalaya, Ladakh, India, Sci. Total
Environ., 703, 134631, https://doi.org/10.1016/j.scitotenv.2019.134631, 2020.
Wolfe, S. A., Smith, S. L., Chartrand, J., Kokelj, S., Palmer, M., and
Stevens, C. W.: Geotechnical Database and Descriptions of
Permafrost Monitoring Sites Established 2006–10 in the Northern Mackenzie
Corridor, Northwest Territories, Geological Survey of Canada
[data set], Open File 6677, https://doi.org/10.4095/287167, 2010.
Wood, S. N.: Fast stable restricted maximum likelihood and marginal
likelihood estimation of semiparametric generalized linear models, J. R.
Stat. Soc. Ser. B, 73, 3–36, 2011.
Wu, J., Yu, S., Yu, H., and Li, J.: Permafrost in the middleeast section of
Qilian Mountains (II): Characters of permafrost, J. Glaciol. Geocryol., 29,
426–432, 2007 (in Chinese with English abstract).
Wu, Q., Zhu, Y., and Liu, Y.: Application of the permafrost table
temperature and thermal offset forecast model in the Tibetan Plateau, J.
Glaciol. Geocryol., 24, 614–617, 2002 (in Chinese with English abstract).
Wu, Q., Hou, Y., Yun, H., and Liu, Y.: Changes in active-layer thickness and
near-surface permafrost between 2002 and 2012 in alpine ecosystems,
Qinghai–Xizang (Tibet) Plateau, China, Glob. Planet. Change, 124, 149–155,
2015.
Xiang, Y., Xiao, Z. Q., Ling, S. L., Wang, J. D., and Song, J. L.:
Validation of Global LAnd Surface Satellite (GLASS) leaf area index product,
Int. J. Remote Sens., 18, 573–584, 2014.
Xiao, Z., Liang, S., Wang, J., Chen, P., Yin, X., Zhang, L., and Song, J.:
Use of general regression neural networks for generating the GLASS leaf area
index product from time-series MODIS surface reflectance, IEEE T.
Geosci. Remote, 52, 209–223, 2014.
Xie, Y. L., Yu, Q. H., You, Y. H., Zhang, Z. Q., and Gou, T. T.: The changing process
and trend of ground temperature around tower foundations of Qinghai-Tibet
Power Transmission line, Sci. Cold Arid Reg., 11,
13–20, 2019.
Yoshikawa, K. and Hinzman, L. D.: Shrinking thermokarst ponds and
groundwater dynamics in discontinuous permafrost near Council, Alaska,
Permafrost Periglac. Process., 14, 151–160, 2003.
Yu, H., Wu, Q. B., and Liu, Y. Z.: The long-term monitoring system on
permafrost regions along the Qinghai-Tibet Railway, J. Glaciol. Geocryol.,
30, 475–481, 2008 (in Chinese, English abstract).
Yu, Q., You, Y., Yan, H., and Liu X.: Distribution and characteristics of
permafrost in Nalati Mountain, western Tianshan Mountains in China, J.
Glaciol. Geocryol., 35, 10–18, 2013 (in Chinese, English abstract).
Zhang, T., Heginbottom, J. A., Barry, R. G., and Brown, J.: Further
statistics on the distribution of permafrost and ground ice in the Northern
Hemisphere, Polar Geogr., 24, 126–131, 2000.
Zhang, T., Barry, R. G., Knowles, K., Heginbottom, J. A., and Brown, J.:
Statistics and characteristics of permafrost and ground-ice distribution in
the Northern Hemisphere, Polar Geogr., 31, 47–68, 2008.
Zhang, X. M., Nan, Z. T., Wu, J. C., Du, E. J., Wang, T., and You, Y. H.:
Modeling permafrost distribution in Wenquan Area over Qinghai-Tibet Plateau
by using multivariate adaptive regression splines, J. Glaciol. Geocryol.,
33, 1088–1097, 2011 (in Chinese, English abstract).
Zhao, J., Luo, T., Li, R., Wei, H., Li, X., Du, M., and Tang, Y.:
Precipitation alters temperature effects on ecosystem respiration in Tibetan
alpine meadows, Agric. For. Meteorol., 252, 121–129, 2018.
Zhao, L., Zou, D., Hu, G., Wu, T., Du, E., Liu, G., Xiao, Y., Li, R., Pang, Q., Qiao, Y., Wu, X., Sun, Z., Xing, Z., Sheng, Y., Zhao, Y., Shi, J., Xie, C., Wang, L., Wang, C., and Cheng, G.: A synthesis dataset of permafrost thermal state for the Qinghai–Tibet (Xizang) Plateau, China, Earth Syst. Sci. Data, 13, 4207–4218, https://doi.org/10.5194/essd-13-4207-2021, 2021.
Zhao, L., Liu, G. Y., Jiao, K. Q., Li, R., Qiao, Y. P., and Ping, C. L.:
Variation of the permafrost in the Headwaters of the Urumqi River in the
Tianshan Mountains since 1991, J. Glaciol. Geocryol., 32, 223–230, 2010a.
Zhao, L., Wu, Q., Marchenko, S. S., and Sharkhuu, N.: Thermal state of
permafrost and active layer in Central Asia during the International Polar
Year, Permafrost Periglac. Process., 21, 198–207, 2010b.
Zhao, S. P., Nan, Z. T., Huang, Y. B., and Zhao, L.: The application and
evaluation of simple permafrost distribution models on the Qinghai–Tibet
Plateau, Permafrost Periglac. Process., 28, 391–404, 2017.
Zhao, X., Liang, S., Liu, S., Yuan, W., Xiao, Z., Liu, Q., Cheng, J., Zhang,
X., Tang, H., Zhang, X., Liu, Q., Zhou, G., Xu, S., and Yu, K.: The Global
Land Surface Satellite (GLASS) remote sensing data processing system and
products, Remote Sens., 5, 2436–2450, 2013.
Short summary
Datasets including ground temperature, active layer thickness, the probability of permafrost occurrence, and the zonation of hydrothermal condition with a 1 km resolution were released by integrating unprecedentedly large amounts of field data and multisource remote sensing data using multi-statistical\machine-learning models. It updates the understanding of the current thermal state and distribution for permafrost in the Northern Hemisphere.
Datasets including ground temperature, active layer thickness, the probability of permafrost...
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