Journal
CRYOSPHERE
Volume 11, Issue 6, Pages 2527-2542Publisher
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/tc-11-2527-2017
Keywords
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Funding
- National Major Scientific Project of China Cryospheric Change and Impacts Research [2013CBA01803]
- Creative Research Groups of National Natural Science Foundation of China [41421061]
- key project of the Chinese Academy of Sciences [KJZD-EW-G03-02]
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The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid-and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated this map using various ground-based data sets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and soil properties (moisture content and bulk density). The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution. Permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06 x 10(6) km(2) (0.97-1.15 x 10(6) km(2), 90% confidence interval) (40 %), 1.46 x 10(6) (56 %), and 0.03 x 10(6) km(2) (1 %), respectively, excluding glaciers and lakes. Ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) were used to validate the model. Validation results showed that the kappa coefficient varied from 0.38 to 0.78 with a mean of 0.57 for the five IRs and 0.62 to 0.74 with a mean of 0.68 within the three transects. Compared with earlier studies, the TTOP modelling results show greater accuracy. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.
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