The monitoring of permafrost is important for assessing the effects of global environmental changes and maintaining and managing social infrastructure, and remote sensing is increasingly being used for this wide-area monitoring. However, the accuracy of the conventional method in terms of temperature factor and soil factor needs to be improved. To address these two issues, in this study, we propose a new model to evaluate permafrost with a higher accuracy than the conventional methods. In this model, the land surface temperature (LST) is used as the upper temperature of the active layer of permafrost, and the temperature at the top of permafrost (TTOP) is used as the lower temperature. The TTOP value is then calculated by a modified equation using precipitation-evapotranspiration (PE) factors to account for the effect of soil moisture. This model, referred to as the TTOP-LST zero-curtain (TLZ) model, allows us to analyze subsurface temperatures for each layer of the active layer, and to evaluate the presence or absence of the zero-curtain effect through a time series analysis of stratified subsurface temperatures. The model was applied to the Qinghai-Tibetan Plateau and permafrost was classified into seven classes based on aspects such as stability and seasonality. As a result, it was possible to map the recent deterioration of permafrost in this region, which is thought to be caused by global warming. A comparison with the mean annual ground temperature (MAGT) model using local subsurface temperature data showed that the average root mean square error (RMSE) value of subsurface temperatures at different depths was 0.19 degrees C, indicating the validity of the TLZ model. A similar analysis based on the TLZ model is expected to enable detailed permafrost analysis in other areas.

In deglaciating environments, rock mass weakening and potential formation of rock slope instabilities is driven by long-term and seasonal changes in thermal- and hydraulic- boundary conditions, combined with unloading due to ice melting. However, in-situ observations are rare. In this study, we present new monitoring data from three highly instrumented boreholes, and numerical simulations to investigate rock slope temperature evolution and micrometer-scale deformation during deglaciation. Our results show that the subsurface temperatures are adjusting to a new, warmer surface temperature following ice retreat. Heat conduction is identified as the dominant heat transfer process at sites with intact rock. Observed non-conductive processes are related to groundwater exchange with cold subglacial water, snowmelt infiltration, or creek water infiltration. Our strain data shows that annual surface temperature cycles cause thermoelastic deformation that dominate the strain signals in the shallow thermally active layer at our stable rock slope locations. At deeper sensors, reversible strain signals correlating with pore pressure fluctuations dominate. Irreversible deformation, which we relate with progressive rock mass damage, occurs as short-term (hours to weeks) strain events and as slower, continuous strain trends. The majority of the short-term irreversible strain events coincides with precipitation events or pore pressure changes. Longer-term trends in the strain time series and a minority of short-term strain events cannot directly be related to any of the investigated drivers. We propose that the observed increased damage accumulation close to the glacier margin can significantly contribute to the long-term formation of paraglacial rock slope instabilities during multiple glacial cycles.