Preprints
https://doi.org/10.5194/essd-2022-206
https://doi.org/10.5194/essd-2022-206
 
06 Jul 2022
06 Jul 2022
Status: this preprint is currently under review for the journal ESSD.

A new 2010 permafrost distribution map over the Qinghai-Tibet Plateau based on subregion survey maps: a benchmark for regional permafrost modeling

Zetao Cao1, Zhuotong Nan1,2, Jianan Hu1, Yuhong Chen1, and Yaonan Zhang3 Zetao Cao et al.
  • 1Key Laboratory of Ministry of Education on Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China
  • 2Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • 3National Cryosphere Desert Data Center, Lanzhou 730000, China

Abstract. Permafrost over the Qinghai-Tibet Plateau (QTP) has gained increasing attention due to its high sensitivity to climate change. Numerous spatial modeling studies have been conducted on the QTP to assess the status of permafrost, project future changes in permafrost, and diagnose contributors to permafrost degradation. Due to very limited number of observation stations on the QTP, these modeling studies are often hampered by the lack of validation references, calibration targets, and model constraints, whereas a high-quality permafrost distribution map can be a good option as a benchmark for spatial simulation results. Existing permafrost distribution maps on the QTP can hardly serve this purpose. An ideal benchmark map for spatial modeling should be methodologically sound, have sufficient accuracy, and be based on observations collected in specific mapping years, rather than all historical data spanning several decades. Therefore, in this study, we created a new permafrost distribution map over the QTP in 2010 through a novel permafrost mapping approach with satellite-derived ground surface thawing/freezing indices as input and survey-based subregion permafrost maps as constraints. This approach was further improved in this study to reduce parametric equifinality. It accounts for the effects of local factors by incorporating into the model an empirical soil parameter whose values are optimally estimated through spatial clustering and parameter optimization constrained by survey-based subregion permafrost maps. This new map shows a total permafrost area of about 1.086×106 km2 (41.2 % of the QTP area) and seasonally frozen ground of about 1.447×106 km2 (54.9 %) in 2010, excluding glaciers and lakes. Validations using survey-based subregion permafrost maps (Kappa = 0.74) and borehole records (Overall Accuracy = 0.85 and Kappa = 0.43) showed higher accuracy of this map than two recent maps. Inspection of regions with obvious distinctions between the maps affirms that the permafrost distribution on this map is more realistic than on the Zou et al. (2017) map. Due to the excellent accuracy demonstrated, this map can serve as a benchmark map of sufficient quality to constrain/validate land surface models and as a historical reference when projecting future permafrost changes on the QTP in the context of global warming.

Zetao Cao et al.

Status: open (until 07 Sep 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-206', Jan Beutel, 10 Aug 2022 reply

Zetao Cao et al.

Data sets

Dataset associated with the article "A new 2010 permafrost distribution map over the Qinghai-Tibet Plateau based on subregion survey maps: a benchmark for regional permafrost modelling" Zetao Cao https://doi.org/10.6084/m9.figshare.19642362

Zetao Cao et al.

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Short summary
This study provides a new 2010 permafrost distribution map of the Qinghai-Tibet Plateau, using an effective mapping approach based entirely on satellite temperature data, well constrained by survey-based subregion maps, and considering 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 excellent accuracy of this map.