Thawing permafrost alters climate not only through carbon emissions but also via energy-water feedback and atmospheric teleconnections. This review focuses on the Tibetan Plateau, where strong freeze-thaw cycles, intense radiation, and complex snow-vegetation interactions constitute non-carbon climate responses. We synthesize recent evidence that links freeze-thaw cycles, ground heat flux dynamics, and soil moisture hysteresis to latent heat feedback, monsoon modulation, and planetary wave anomalies. Across these pathways, both observational and simulation studies reveal consistent signals of feedback amplification and nonlinear threshold behavior. However, most Earth system models underrepresent these processes due to simplifications in freezethaw processes, snow-soil-vegetation coupling, and cross-seasonal memory effects. We conclude by identifying priority processes to better simulate multi-scale cryosphere-climate feedback, especially under continued climate warming in high-altitude regions.

This study employs the Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) technique, along with in situ hydrothermal data, to explore the details and mechanisms of permafrost ground surface deformation in the hinterland Tibetan Plateau. Through analyzing GNSS data collected from November 2021 to April 2024, seasonal deformation of up to approximately 5 cm, caused by active layer freeze-thaw cycles, was identified. Additionally, more than 2 years of continuous monitoring revealed a clear ground subsidence rate of 2.7 cm per year due to permafrost thawing. We compared the GNSS-IR monitored deformation with simulated deformation using in situ soil moisture and temperature profiles at 5-220 cm depth and found that the correlation reached 0.9 during the active-layer thawing and freezing period; we also observed that following an exceptionally thawing season, the subsequent thawing season experiences notably greater thaw subsidence. Furthermore, we analyzed the differences in GNSS-IR monitoring results with and without the inclusion of Beidou Navigation Satellite System (BDS) signals, and found that the inclusion of BDS signals reduced the standard deviation of GNSS-IR results by an average of 0.24 mm on snow-free periods, but increased by an average of 0.12 mm during the snow cover periods. This may be due to the longer wavelength of the BDS signal, which exhibits greater diffraction through snow and reduces signal reflectivity compared to other satellite systems. The research results demonstrate the potential and ability of continuous GNSS-IR ground surface deformation monitoring in revealing and exploring the hydrothermal processes within permafrost under climate change.

Accurate understanding and modeling of soil hydrothermal dynamics in permafrost regions is essential for reliably assessing future permafrost changes and their impacts. However, the inadequate representation of soil water-heat transport processes in current land surface models (LSMs) introduces large uncertainty in simulating permafrost dynamics, particularly on the Qinghai-Tibet Plateau (QTP). In this study, we modified the parameterizations of soil thermal conductivity, unfrozen water and soil evaporation resistance in version 5.0 of the Community Land Model (CLM5.0) and assessed their effects on soil hydrothermal dynamics in permafrost regions on the QTP using in-situ measurements the depths of 10-40 cm. The results showed that soil temperature was more sensitive to the modified soil thermal conductivity and unfrozen water schemes, with average RMSE reduced by approximately 0.60 degrees C compared to the default CLM5.0. Soil moisture was mainly affected the unfrozen water scheme during freezing and by the optimized soil evaporation resistance scheme during thawing, with maximum accuracy improvements of 8% and 25%, respectively. All three schemes significantly improved soil thermal conductivity simulations, reducing RMSE over 80%. Overall, our modifications remarkably reduced simulation errors compared to the default schemes, improving the average accuracy soil temperature, soil moisture and soil thermal conductivity by approximately 16%, 21% and 81% respectively. Additionally, this study emphasized the importance of accurately representing permafrost-related processes in LSMs, as they significantly affected simulation results. Specifically, soil thermodynamics is strongly sensitive to subtle changes in soil moisture transport processes, such as the hysteresis effect unfrozen water content, and parameterizations of snowpack and vegetation. Therefore, future work should focus on enhancing the accurate representations of these processes and optimized parameters in LSMs to improve the simulation accuracy in permafrost regions on the QTP. This study enhanced the understanding of soil hydrothermal processes in LSMs and provided valuable insights for the future model development for permafrost regions under the context of climate change.

Accurate estimate of active layer thickness (ALT) is crucial for understanding permafrost and ecosystem responses to climate change. Interferometric Synthetic Aperture SAR (InSAR) technology can detect active layer freeze-thaw induced surface deformation with high accuracy, facilitating more accurate ALT estimation at the regional scale. Previous studies revealed a positive relationship between ALT and seasonal deformation in poorly drained Arctic soils. However, whether such relationship still holds in arid permafrost regions such as the Qinghai-Tibet Plateau (QTP) remains uncertain. Through synthesizing extensive field observations and remote sensing data, we find an overall negative correlation (r = -0.53, p < 0.01) between ALT and seasonal deformation in QTP, which tends to become more negative with sparser vegetation and drier soils, in contrast to the Arctic. After normalizing the climatic effect on ALT, we observe a decreasing sensitivity of seasonal deformation to active-layer changes with drier soils. Our study reveals a non-linear relationship between ALT and seasonal deformation across different permafrost regions, which helps to inform future development of InSAR-based permafrost applications.

The freeze-thaw (F-T) cycle of the active layer (AL) causes the frost heave and thaw settlement deformation of the terrain surface. Accurately identifying its amplitude and time characteristics is important for climate, hydrology, and ecology research in permafrost regions. We used Sentinel-1 SAR data and small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology to obtain the characteristics of F-T cycles in the Zonag Lake-Yanhu Lake permafrost-affected endorheic basin on the Qinghai-Tibet Plateau from 2017 to 2019. The results show that the seasonal deformation amplitude (SDA) in the study area mainly ranges from 0 to 60 mm, with an average value of 19 mm. The date of maximum frost heave (MFH) occurred between November 27th and March 21st of the following year, averaged in date of the year (DOY) 37. The maximum thaw settlement (MTS) occurred between July 25th and September 21st, averaged in DOY 225. The thawing duration is the thawing process lasting about 193 days. The spatial distribution differences in SDA, the date of MFH, and the date of MTS are relatively significant, but there is no apparent spatial difference in thawing duration. Although the SDA in the study area is mainly affected by the thermal state of permafrost, it still has the most apparent relationship with vegetation cover, the soil water content in AL, and active layer thickness. SDA has an apparent negative and positive correlation with the date of MFH and the date of MTS. In addition, due to the influence of soil texture and seasonal rivers, the seasonal deformation characteristics of the alluvial-diluvial area are different from those of the surrounding areas. This study provides a method for analyzing the F-T cycle of the AL using multi-temporal InSAR technology.

The current spatial atmospheric forcing data cannot accurately depict the actual conditions of the Qinghai-Tibet Plateau (QTP), where monitoring stations are scarce and unevenly distributed. This deficiency in atmospheric data hinders accurate simulation of plateau permafrost changes on the plateau. In this study, we develop a new approach to evaluate regional permafrost changes, which does not rely on spatially distributed meteorological data but instead uses the regional climate change processes or temperature change rates. Centred on a transient heat conduction permafrost model, this approach was applied to the Qinghai Hoh Xil National Nature Reserve (referred to as Hoh Xil) within the QTP from 1960 to 2015, using the rate of air temperature change provided by the Wudaoliang Meteorological Station, the only national station in Hoh Xil. Simulation results showed that the difference between the simulated and observed change rates of mean annual ground temperature (MAGT) was less than 0.04 degrees C per decade from 2001 to 2015 at five long-term monitoring sites. The simulated ground temperature profiles in four boreholes from various permafrost zones revealed an error of less than 0.7 degrees C below 5 m in depth. Model validation demonstrates the reliability of this approach for predicting long-term permafrost changes. Future regional permafrost changes were further simulated based on the latest warming scenarios (BCC-CSM2-MR) from the Coupled Model Intercomparison Project Phase 6. Predictions revealed significant differences in the regional permafrost degradation rate under different climate warming scenarios. Under the most severe warming scenario (SSP58.5), permafrost in the study area is projected to still cover 72.2% of the total area by 2100, with most of the Hoh Xil's permafrost becoming warm (MAGT > 1 degrees C) permafrost. This approach not only facilitates the simulation of frozen ground changes in areas with few meteorological monitoring stations but also provides a new perspective for using coarse-resolution palaeoclimate data to investigate permafrost formation and evolution over long time scales.

Permafrost in the Northern Hemisphere has been degrading under climate change, affecting climatic, hydrological, and ecological systems. To reveal the temporal and spatial characteristics of permafrost degradation under climate change, we quantified permafrost thermal states and active layer thicknesses using observational data covering various periods and different areas of the Northern Hemisphere. The soil temperatures at 20 cm depth in the circumpolar Arctic permafrost regions were much lower than in the Qinghai-Tibet Plateau. The thaw period is 114 days in the circumpolar permafrost regions compared to 167 days in the Qinghai-Tibet Plateau. The active layer thickness (ALT) was largest in transitional permafrost regions and sporadic permafrost regions, and lowest in the high latitude permafrost regions and continuous permafrost regions, and the ALT generally exhibited an increasing trend. The average ALT was 1.7 m, and increased by 3.6 cm per year in the Northern Hemisphere. The mean annual ground temperature (MAGT) was largest in the high-altitude permafrost regions and isolated permafrost regions, and lowest in the high latitude permafrost regions and continuous permafrost regions. The warming rate of the MAGT was largest in the high latitude regions and lowest in the high altitude regions, and gradually increased from isolated permafrost regions to continuous permafrost regions, with an average warming rate of 0.3 degrees C per decade for the whole Northern Hemisphere. These findings provide important information for understanding the variability in permafrost degradation processes across different regions under climate change.

Soil organic carbon (SOC) is very important in the vulnerable ecological environment of the Third Pole; however, data regarding the spatial distribution of SOC are still scarce and uncertain. Based on multiple environmental variables and soil profile data from 458 pits (depth of 0-1 m) and 114 cores (depth of 0-3 m), this study uses a machine-learning approach to evaluate the SOC storage and spatial distribution at a depth interval of 0-3m in the frozen ground area of the Third Pole region. Our results showed that SOC stocks (SOCSs) exhibited a decreasing spatial pattern from the southeast towards the northwest. The estimated SOC storage in the upper 3m of the soil profile was 46.18 Pg for an area of 3.27 x 10(6) km(2), which included 21.69 and 24.49 Pg for areas of permafrost and seasonally frozen ground`, respectively. Our results provide information on the storage and patterns of SOCSs at a 1 km resolution for areas of frozen ground in the Third Pole region, thus providing a scientific basis for future studies pertaining to Earth system models.

Warming-induced carbon loss via ecosystem respiration (R-e) is probably intensifying in the alpine grassland ecosystem of the Tibetan Plateau owing to more accelerated warming and the higher temperature sensitivity of R-e (Q(10)). However-little is known about the patterns and controlling factors of Q(10) on the plateau, impeding the comprehension of the intensity of terrestrial carbon-climate feedbacks for these sensitive and vulnerable ecosystems. Here, we synthesized and analyzed multiyear observations from 14 sites to systematically compare the spatiotemporal variations of Q(10) values in diverse climate zones and ecosystems, and further explore the relationships between Q(10) and environmental factors. Moreover-structural equation modeling was utilized to identify the direct and indirect factors predicting Q(10) values during the annual-growing, and non-growing seasons. The results indicated that the estimated Q(10) values were strongly dependent on temperature- generally, with the average Q(10) during different time periods increasing with air temperature and soil temperature at different measurement depths (5 cm, 10 cm, 20 cm). The Q(10) values differentiated among ecosystems and climatic zones, with warming-induced Q(10) declines being stronger in colder regions than elsewhere based on spatial patterns. NDVI was the most cardinal factor in predicting annual Q(10) values, significantly and positively correlated with Q(10). Soil temperature (T-s) was identified as the other powerful predictor for Q(10), and the negative Q(10)-T-s relationship demonstrates a larger terrestrial carbon loss potentiality in colder than in warmer regions in response to global warming. Note that the interpretations of the effect of soil moisture on Q(10) were complicated, reflected in a significant positive relationship between Q(10) and soil moisture during the growing season and a strong quadratic correlation between the two during the annual and non-growing season. These findings are conducive to improving our understanding of alpine grassland ecosystem carbon-climate feedbacks under warming climates.

Empirical orthogonal function (EOF) and correlation analyses were employed to investigate the winter and spring snow depth in Eurasia and its relationship with Eastern China precipitation based on the observed and reanalyzed data from 1980 to 2016. The results show that the winter and spring snow cover in Eurasia not only highlights a decreasing trend due to global warming (the first EOF mode, its variance accounted for 24.4% and 22.6% of the total variance) but also exhibits notable interdecadal variation (the second EOF mode, its variance accounted for 10.2% and 11.5% of the total variance). The second EOF mode of winter snow depth in Eurasia is characterized by a west-east dipole pattern. It was observed that the spatial correlation pattern between the EOF2 of Eurasian snow depth and summer precipitation in China closely resembles the meridional quadrupole structure of the third EOF mode of summer precipitation in China. This pattern is characterized by excessive rainfall in Northeast China and the lower-middle reaches of the Yangtze River, and less rainfall over the Yellow River basin and southern China. The EOF mode of spring snow depth not only reflects the declining trend but also regulates precipitation in Eastern China. The possible mechanisms by which snow depth causes changes in soil moisture and subsequently affects atmospheric circulation are then explored from the perspective of the hydrological effects of snow cover. Decreased (Increased) snow depth in Eurasia during the winter and spring directly leads to diminished (increased) soil moisture while increasing (decreasing) net radiation and sensible heat flux at the surface. The meridional distribution of surface temperature also exhibits a dipole pattern, leading to enhanced subtropical westerly jet in the upper troposphere. The Eurasian snow cover anomalies pattern triggered an anomalous mid-latitude Eurasian wave train, which strengthened significantly in the Western Siberian Plain. It then splits into two branches, one continuing to propagate eastward at high latitudes and the other shifting towards East Asia, thereby impacting precipitation in Eastern China. This work indicates that the second EOF mode of Eurasian snow cover can impact the precipitation variability in Eastern China during the same period and in summer on an interdecadal scale.