Articles | Volume 14, issue 2
Earth Syst. Sci. Data, 14, 865–884, 2022
https://doi.org/10.5194/essd-14-865-2022

Special issue: Extreme environment datasets for the three poles

Earth Syst. Sci. Data, 14, 865–884, 2022
https://doi.org/10.5194/essd-14-865-2022
Data description paper
24 Feb 2022
Data description paper | 24 Feb 2022

New high-resolution estimates of the permafrost thermal state and hydrothermal conditions over the Northern Hemisphere

Youhua Ran et al.

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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. 
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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.