Using ERA-Interim reanalysis dataset to assess the changes of ground surface freezing and thawing condition on the Qinghai–Tibet Plateau

It is important to assess the freezing and thawing condition of ground surface for understanding the impacts of frozen ground on surface and subsurface hydrology, the surface energy and moisture balance, ecosystem conservation, and engineering construction on the Qinghai–Tibet Plateau (QTP). However, assessing the changes of ground surface freezing and thawing condition on the QTP still remains a challenge owing to data sparseness and discontinuous observations. The annual ground surface freezing index (GFI) and ground surface thawing index (GTI) could be used to predict changes of the thermal regime of permafrost and can be good indicators of climate change on the QTP, which has important engineering applications. In this study, we first calibrated the reanalysis ground surface temperature (GST) data using the methods of elevation correction on the QTP. After calibration, the quality of reanalysis data has been improved significantly. For the annual time series, the root mean square error decreased from 7.7 to 1.6 °C, the absolute value of mean bias error decreased from 7.5 to 0.0 °C, and the correlation coefficient increased from 0.62 to 0.86. Second, we estimated the annual and seasonal spatial distributions of GST. The spatial distribution of spring and autumn GST closely resembled the annual mean pattern. The long-term mean GFI and GTI from the calibrated reanalysis dataset were 1322.3 and 2027.9 °C/day, respectively. The GFI and GTI were presented as latitude and elevation zonation; it can also be seen that permafrost mostly occurred in the high GFI and low GTI regions. Estimating the GFI and GTI precisely will be utilized to model the permafrost distribution and estimate active layer thickness in the future.