A synthesis dataset of permafrost thermal state for the Qinghai-Tibet (Xizang) Plateau, China

Permafrost has great influences on the climatic, hydrological, and ecological systems on the Qinghai-Tibet Plateau (QTP). The changing permafrost and its impact have been attracting great attention worldwide like never before. More observational and modeling approaches are needed to promote an understanding of permafrost thermal state and climatic conditions on the QTP. However, limited data on the permafrost thermal state and climate background have been sporadically reported in different pieces of literature due to the difficulties of accessing and working in this region where the weather is severe, environmental conditions are harsh, and the topographic and morphological features are complex. From the 1990s, we began to establish a permafrost monitoring network on the QTP. Meteorological variables were measured by automatic meteorological systems. The soil temperature and moisture data were collected from an integrated observation system in the active layer. Deep ground temperature (GT) was observed from boreholes. In this study, a comprehensive dataset consisting of long-term meteorological, GT, soil moisture, and soil temperature data was compiled after quality control from an integrated, distributed, and multiscale observation network in the permafrost regions of QTP. The dataset is helpful for scientists with multiple study fields (i.e., climate, cryospheric, ecology and hydrology, meteorology science), which will significantly promote the verification, development, and improvement of hydrological models, land surface process models, and climate models on the QTP.

Automated summary

The permafrost on the Qinghai-Tibet Plateau has significant impacts on climatic, hydrological, and ecological systems which have attracted global attention. Limited data have been reported due to challenges in working in this harsh region, but a monitoring network has been established to provide comprehensive datasets for verification and improvement of models in various scientific fields.