Comment on essd-2022-206

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this map can serve as a benchmark map of sufficient quality to constrain/validate land surface models and as a historical reference when projecting future permafrost changes on the QTP in the context of global warming.