Articles | Volume 16, issue 3
https://doi.org/10.5194/essd-16-1425-2024
© Author(s) 2024. 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-16-1425-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Mar 2024
Data description paper |
| 15 Mar 2024
| 15 Mar 2024
An observational network of ground surface temperature under different land-cover types on the northeastern Qinghai–Tibet Plateau
Raul-David Şerban
CORRESPONDING AUTHOR
Faculty of Agricultural, Environmental and Food Sciences, Free University of Bozen-Bolzano, Bolzano 39100, Italy
Institute for Alpine Environment, Eurac Research, Bolzano 39100, Italy
National Key Laboratory of Cryosphere Science and Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Huijun Jin
CORRESPONDING AUTHOR
National Key Laboratory of Cryosphere Science and Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
School of Civil Engineering and Transportation, Permafrost Institute, and China-Russia Joint Laboratory of Cold Regions Engineering and Environment, Northeast Forestry University, Harbin 150090, China
Mihaela Şerban
Applied Geomorphology and Interdisciplinary Research Centre, Department of Geography, West University of Timişoara, Timişoara 300223, Romania
Giacomo Bertoldi
Institute for Alpine Environment, Eurac Research, Bolzano 39100, Italy
Dongliang Luo
National Key Laboratory of Cryosphere Science and Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Qingfeng Wang
National Key Laboratory of Cryosphere Science and Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
National Key Laboratory of Cryosphere Science and Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Ruixia He
National Key Laboratory of Cryosphere Science and Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Xiaoying Jin
School of Civil Engineering and Transportation, Permafrost Institute, and China-Russia Joint Laboratory of Cold Regions Engineering and Environment, Northeast Forestry University, Harbin 150090, China
Xinze Li
National Key Laboratory of Cryosphere Science and Frozen Soils Engineering, 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
College of Engineering, China University of Petroleum-Beijing, Karamayi 834000, China
Jianjun Tang
School of Civil Engineering and Transportation, Permafrost Institute, and China-Russia Joint Laboratory of Cold Regions Engineering and Environment, Northeast Forestry University, Harbin 150090, China
Hongwei Wang
National Key Laboratory of Cryosphere Science and Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
School of Civil Engineering and Transportation, Permafrost Institute, and China-Russia Joint Laboratory of Cold Regions Engineering and Environment, Northeast Forestry University, Harbin 150090, China
Data sets
Multiscale observation of topsoil temperature below different landcover types on northeastern Qinghai-Tibet Plateau (2019-2020) Raul-David Șerban and Huijun Jin https://doi.org/10.11888/Cryos.tpdc.272945
Short summary
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.
A particular observational network for ground surface temperature (GST) has been established on...
Special issue
Altmetrics
Final-revised paper
Preprint