Whilst permafrost change is widely concerned in the context of global warming, lack of observations becomes one of major limitations for conducting large-scale and long-term permafrost change research. Reanalysis/assimilation data in theory can make up for the lack of observations, but how they characterize permafrost extent and active layer thickness remains unclear. Here, we investigate the near-surface permafrost extent and active layer thickness characterized by seven reanalysis/assimilation datasets (CFSR, MERRA-2, ERA5, ERA5-Land, GLDAS-CLSMv20, GLDAS-CLSMv21, and GLDAS-Noah). Results indicate that most of reanalysis/assimilation data have limited abilities in characterizing near-surface permafrost extent and active layer thickness. GLDAS-CLSMv20 is overall optimal in terms of comprehensive performance in characterizing both present-day near-surface permafrost extent and active layer thickness change. The GLDAS-CLSMv20 indicates that near-surface permafrost extent decreases by -0.69 x 106 km2 decade-1 and active layer deepens by 0.06 m decade-1 from 1979 to 2014. Change in active layer is significantly correlated to air temperature, precipitation, and downward longwave radiation in summer, but the correlations show regional differences. Our study implies an imperative to advance reanalysis/assimilation data's abilities to reproduce permafrost, especially for reanalysis data.

Hydrologic-land surface models (H-LSMs) offer a physically-based framework for representing and predicting the present and future states of the extensive high-latitude permafrost areas worldwide. Their primary challenge, however, is that soil temperature data are severely limited, and traditional model validation, based only on streamflow, can show the right fit to these data for the wrong reasons. Here, we address this challenge by (1) collecting existing data in various forms including in-situ borehole data and different large-scale permafrost maps in addition to streamflow data, (2) comprehensively evaluating the performance of an H-LSM with a wide range of possible process parametrizations and initializations, and (3) assessing possible trade-offs in model performance in concurrently representing hydrologic and permafrost dynamics, thereby pointing to the possible model deficiencies that require improvement. As a case study, we focus on the sub-arctic Liard River Basin in Canada, which typifies vast northern sporadic and discontinuous permafrost regions. Our findings reveal that different process parameterizations tend to align with different data sources or variables, which largely exhibit inconsistencies among themselves. We further observe that a model may fail to represent permafrost occurrence yet seemingly fit streamflows adequately. Nonetheless, we demonstrate that accurately representing essential permafrost dynamics, including the active soil layer and insulation effects from snow cover and soil organic matter, is crucial for developing high-fidelity models in these regions. Given the complexity of processes and the incompatibility among different data sources/variables, we conclude that employing an ensemble of carefully designed model parameterizations is essential to provide a reliable picture of the current conditions and future spatio-temporal co-evolution of hydrology and permafrost.

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.

Permafrost, widely distributed in the Northern Hemisphere, plays a vital role in regulating heat and moisture cycles within ecosystems. In the last four decades, due to global warming, permafrost degradation has accelerated significantly in high latitudes and altitudes. However, the impact of permafrost degradation on vegetation remains poorly understood to date. Based on active layer thickness (ALT) monitoring data, meteorological data and normalized difference vegetation index (NDVI) data, we found that most ALT-monitored sites in the Northern Hemisphere show an increasing trend in NDVI and ALT. This suggests an overall increase in NDVI from 1980 to 2021 while permafrost degradation has been occurring. Permafrost degradation positively influences NDVI growth, with the intensity of the effects varying across land cover types and permafrost regions. Furthermore, based on Mann-Kendall trend test, we detected abrupt changes in NDVI and environmental factors, further confirming that there is a strong consistency between the abrupt changes of ALT and NDVI, and the consistency between the abrupt change events of ALT and NDVI is stronger than that of air temperature and precipitation. These findings work toward a better comprehending of permafrost effects on vegetation growth in the context of climate change. Our research focuses on the influence of permafrost degradation on vegetation in high-latitude and high-altitude regions of the Northern Hemisphere. By analyzing permafrost monitoring and vegetation data, we have observed a widespread occurrence of permafrost degradation and vegetation greening in recent years across the Northern Hemisphere. Our analysis has revealed a strong connection between permafrost degradation and vegetation greening in permafrost areas, and the impact varies with different vegetation and permafrost types. In addition, we further investigated the consistency of abrupt changes in the vegetation growth with various environmental factors. It can be seen that despite the significant influence of air temperature changes on vegetation growth in permafrost regions of the Northern Hemisphere, the abrupt change of vegetation growth is consistent with the abrupt change in the process of permafrost degradation, indicating that vegetation growth displays a heightened sensitivity to permafrost degradation. These findings provide valuable insights into the ecological consequences of permafrost changes in high-latitude and high-altitude areas under the influence of climate change. Vegetation in the Northern Hemisphere shows a greening trend, and permafrost shows a degradation trend Permafrost degradation positively influences vegetation growth, with the intensity of the effects varying by vegetation and permafrost types Abrupt changes in vegetation growth are more consistent with abrupt permafrost degradation than with meteorological factors

The active layer, acting as an intermediary of water and heat exchange between permafrost and atmosphere, greatly influences biogeochemical cycles in permafrost areas and is notably sensitive to climate fluctuations. Utilizing the Chinese Meteorological Forcing Dataset to drive the Community Land Model, version 5.0, this study simulates the spatial and temporal characteristics of active layer thickness (ALT) on the Tibetan Plateau (TP) from 1980 to 2020. Results show that the ALT, primarily observed in the central and western parts of the TP where there are insufficient station observations, exhibits significant interdecadal changes after 2000. The average thickness on the TP decreases from 2.54 m during 1980-1999 to 2.28 m during 2000-2020. This change is mainly observed in the western permafrost region, displaying a sharp regional inconsistency compared to the eastern region. A persistent increasing trend of ALT is found in the eastern permafrost region, rather than an interdecadal change. The aforementioned changes in ALT are closely tied to the variations in the surrounding atmospheric environment, particularly air temperature. Additionally, the area of the active layer on the TP displays a profound interdecadal change around 2000, arising from the permafrost thawing and forming. It consistently decreases before 2000 but barely changes after 2000. The regional variation in the permafrost active layer over the TP revealed in this study indicates a complex response of the contemporary climate under global warming.

Revegetation is an effective approach for restoring extremely degraded grassland (DG) in the Qinghai-Tibetan Plateau (QTP). However, little is known about its effects on permafrost stability. Our study investigated changes in the characteristics of DG and revegetated grassland (RG) in alpine permafrost regions of the QTP by means of in situ monitoring and sampling. Compared with DG, soil temperature was lower in warm months and slightly higher in cool months both at 2 and 10 cm depths after revegetation, while soil moisture generally decreased. Revegetation advanced the onset and increased the duration of completely frozen stage. The number of freeze-thaw days decreased at 2 cm but increased at 10 cm depth. The freeze-thaw strength weakened at 2 cm depth in spring and autumn, and at 10 cm depth in autumn, but increased at 10 cm depth in spring. The thawing index at the two depths and active layer thickness in RG were also significantly lower than those in DG. Revegetation significantly affected the particle size distribution and stability of soil aggregates by increasing the proportion of large macroaggregates. Thus, revegetation can effectively improve the permafrost stability of degraded grassland in the QTP and enhance the service functions of alpine grassland ecosystems.

Permafrost stability is significantly influenced by the thermal buffering effects of snow and active-layer peat soils. In the warm season, peat soils act as a barrier to downward heat transfer mainly due to their low thermal conductivity. In the cold season, the snowpack serves as a thermal insulator, retarding the release of heat from the soil to the atmosphere. Currently, many global land models overestimate permafrost soil temperature and active layer thickness (ALT), partially due to inaccurate representations of soil organic matter (SOM) density profiles and snow thermal insulation. In this study, we evaluated the impacts of SOM and snow schemes on ALT simulations at pan-Arctic permafrost sites using the Energy Exascale Earth System Model (E3SM) land model (ELM). We conducted simulations at the Circumpolar Active Layer Monitoring (CALM) sites across the pan-Arctic domain. We improved ELM-simulated site-level ALT using a knowledge-based hierarchical optimization procedure and examined the effects of precipitation-phase partitioning methods (PPMs), snow compaction schemes, and snow thermal conductivity schemes on simulated snow depth, soil temperature, ALT, and CO2 fluxes. Results showed that the optimized ELM significantly improved agreement with observed ALT (e.g. RMSE decreased from 0.83 m to 0.15 m). Our sensitivity analysis revealed that snow-related schemes significantly impact simulated snow thermal insulation levels, soil temperature, and ALT. For example, one of the commonly used snow thermal conductivity schemes (quadratic Sturm or SturmQua) generally produced warmer soil temperatures and larger ALT compared to the other two tested schemes. The SturmQua scheme also amplified the model's sensitivity to PPMs and predicted deeper ALTs than the other two snow schemes under both current and future climates. The study highlights the importance of accurately representing snow-related processes and peat soils in land models to enhance permafrost dynamics simulations.

This research presents a comprehensive environmental assessment of a small mountain permafrost catchment of the Anmangynda River in the Upper Kolyma Highland (Northeastern Asia) over the period of 2021-2023. The study reveals significant diversity in climatic, geocryological, and hydrogeological conditions within this confined area, emphasizing the need for extensive field data collection and monitoring in vast permafrost regions with limited data availability. Key findings include variations in ground temperature, maximum seasonal thaw depth, and depths of zero annual amplitudes of ground temperature at different elevations and landscape types. Groundwater and surface flow dynamics within spring aufeis basins exhibit complex geocryological regimes influenced by icing processes. The presence of aufeis and its impact on local hydrology highlight the ecological significance of this phenomenon. Future research should focus on long-term trends in permafrost dynamics and their relationship with climate change, as well as the ecological effects of aufeis formation on local ecosystems. The study underscores the importance of a multi-faceted approach to environmental assessment, incorporating various environmental parameters and processes, to gain a comprehensive understanding of the intricate interactions within the cryosphere and their responses to changing climate conditions. Such knowledge is essential for addressing broader questions related to climate change, ecosystem resilience, and sustainable resource management in Northeastern Siberia.

Permafrost degradation on the Qinghai-Tibet Plateau (QTP) has significant impacts on climate, hydrology, and engineering and environmental systems. To understand the temporal and spatial characteristics of permafrost on the QTP, we quantified the variation in active layer thickness (ALT), permafrost thermal state, and future permafrost change under different scenarios using observational data, reanalysis data, and the numerical permafrost model. Generally, ALT ranged from 0.5 to 6.0 m with an average of 2.39 m, and mean annual ground temperature (at a depth of zero annual amplitude for ground temperature) mainly ranged between 0 and -3 degrees C with an average of -0.85 degrees C. The soil temperatures in different layers based on the ERA5-Land data revealed even stronger increasing trends, for example, 0.245, 0.245, 0.244, and 0.238 degrees C/decade at depths of 0-7, 7-28, 28-100, and 100-289 cm from 1980 to 2021, compared to those during the period from 1960 to 2021, which were 0.153, 0.156, 0.155, and 0.149 degrees C/decade, respectively. The average warming trends in annual mean soil temperature were 0.153 and 0.243 degrees C/decade from 1960 to 2021 and 1980 to 2021, respectively. The average rate of thickening of the ALT among the 10 active layer observation sites was 2.84 cm/year. There was a significant warming trend in ground temperature above similar to 15 m with warming of 0.063 to 0.120, 0.026 to 0.182, 0.101 to 0.314, and 0.189 to 0.303 degrees C/decade at the QTB01, QTB06, QTB08, and XDTGT sites, respectively, and yearly minimum ground temperatures exhibited stronger warming trends than maximum ground temperatures. In addition, the simulation revealed significant increases in ground temperature at the Xidatan (XDT) and Tanggula (TGL) sites under both historical and future Representative Concentration Pathway (RCP) scenarios, but the increases in ground temperature were significantly greater at TGL than XDT. These findings provide important information for understanding the variability in permafrost degradation processes and improving simulations of permafrost change under climate change on the QTP.

Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. We found that higher values of RH (up to 40 %) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30 % maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physicallybased predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling