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"

Dataset description

This dataset provides the data associated with the article:  Cao, Z.; Nan, Z.; Hu, J.; Chen, Y.; Zhang, Y.  A new 2010 permafrost distribution map over the Qinghai-Tibet Plateau based on subregion survey maps: a benchmark for regional permafrost modelling.

This dataset contains a new 2010 permafrost distribution map over the Qinghai-Tibet Plateau and the data used in the mapping. All data are provided as GeoTIFF(.tif) files. The spatial resolution is 1 km, and the geographic coordinate system is WGS_1984.

• 1. "permafrost_distribution_map_2010_QTP.tif" is the 2010 permafrost distribution map over the Qinghai-Tibet Plateau.
• 2. "soil_cluster_QTP.tif" is the spatial distribution of the resulting soil clusters on the Qinghai-Tibet Plateau.
• 3. "DDT_mean_annual.tif" contains annual thawing indices on the QTP averaged from 2005-2010 derived from MODIS LST data.
• 4. "DDF_mean_annual.tif" contains annual freezing indices on the QTP averaged from 2005-2010 derived from MODIS LST data.

Abstract

Permafrost over the Qinghai-Tibet Plateau (QTP) has received increasing attention due to its high sensitivity to climate change, and numerous spatial modelling studies have been conducted on the QTP to project the future permafrost changes, evaluate permafrost physics, and diagnose permafrost degradation contributors based on land surface models. But due to limited observation stations on the QTP, these modeling studies are often challenged by the lack of validation references, calibration targets, and modeling constraints, while a high-quality permafrost distribution map can be a good option as a benchmark for the spatial simulation result. However, existing permafrost distribution maps on the QTP often fail to serve as a benchmark. An ideal benchmark map is supposed to be characterized as an independent map based on observation instead of land surface models, an accurate map with consideration of local factors and constraints during the mapping process, and a representative map based on data from particular mapping years instead of all the historical data from decades thus can provide the calibration target and the constraint for transient models. Therefore, in this study, we created a new permafrost distribution map over QTP in 2010 through a novel permafrost mapping approach with satellite data as inputs and survey-based subregion permafrost maps as constraints. This approach was further improved in this study to reduce parametric equifinality. The ground surface thawing/freezing indices, as driving data for the mapping approach, were derived from remotely sensed land surface temperature data. The mapping approach takes the effects of local factors into account by incorporating a permafrost-related soil parameter in the model whose values are optimally estimated through spatial clustering based on environmental variables and parameter optimization technique with the survey-based subregion permafrost maps as an optimization objective. This new map indicates a total permafrost area of about 1.086×106 km2 (41.2% of the QTP) and seasonally frozen ground of about 1.447×106 km2 (54.9% of the QTP) in 2010 with glaciers and lakes excluded. The validations against survey-based subregion permafrost maps (Kappa coefficient = 0.74) and borehole records (Overall Accuracy = 0.85 and Kappa coefficient = 0.43) indicated better accuracy of this map than two recent maps. Additional supporting evidence also found the permafrost distribution in this map more reasonable than the peer map. With the proven better accuracy, this map is capable of serving as a benchmark map at sufficient quality for land surface models, especially as a historical constraint for future modeling studies on the QTP to avoid excessive deviation.