Freeze-thaw cycles (FTC) alter soil function through changes to physical organization of the soil matrix and biogeochemical processes. Understanding how dynamic climate and soil properties influence FTC may enable better prediction of ecosystem response to changing climate patterns. In this study, we quantified FTC occurrence and frequency across 40 National Ecological Observatory Network (NEON) sites. We used site mean annual precipitation (MAP) and mean annual temperature (MAT) to define warm and wet, warm and dry, and cold and dry climate groupings. Site and soil properties, including MAT, MAP, maximum-minimum temperature difference, aridity index, precipitation as snow (PAS), and organic mat thickness, were used to characterize climate groups and investigate relationships between site properties and FTC occurrence and frequency. Ecosystem-specific drivers of FTC provided insight into potential changes to FTC dynamics with climate warming. Warm and dry sites had the most FTC, driven by rapid diurnal FTC close to the soil surface in winter. Cold and dry sites were characterized by fewer, but longer-duration FTC, which mainly occurred in spring and increased in number with higher organic mat thickness (Spearman's rho = 0.97, p < 0.01). The influence of PAS and MAT on the occurrence of FTC depended on climate group (binomial model interaction p (chi(2)) < 0.05), highlighting the role of a persistent snowpack in buffering soil temperature fluctuations. Integrating ecosystem type and season-specific FTC patterns identified here into predictive models may increase predictive accuracy for dynamic system response to climate change.

Introduction: Permafrost and seasonally frozen soil are widely distributed on the Qinghai-Tibetan Plateau, and the freezing-thawing cycle can lead to frequent phase changes in soil water, which can have important impacts on ecosystems.Methods: To understand the process of soil freezing-thawing and to lay the foundation for grassland ecosystems to cope with complex climate change, this study analyzed and investigated the hydrothermal data of Xainza Station on the Northern Tibet from November 2019 to October 2021.Results and Discussion: The results showed that the fluctuation of soil temperature showed a cyclical variation similar to a sine (cosine) curve; the deep soil temperature change was not as drastic as that of the shallow soil, and the shallow soil had the largest monthly mean temperature in September and the smallest monthly mean temperature in January. The soil water content curve was U-shaped; with increased soil depth, the maximum and minimum values of soil water content had a certain lag compared to that of the shallow soil. The daily freezing-thawing of the soil lasted 179 and 198 days and the freezing-thawing process can be roughly divided into the initial freezing period (November), the stable freezing period (December-early February), the early ablation period (mid-February to March), and the later ablation period (March-end of April), except for the latter period when the average temperature of the soil increased with the increase in depth. The trend of water content change with depth at all stages of freezing-thawing was consistent, and negative soil temperature was one of the key factors affecting soil moisture. This study is important for further understanding of hydrothermal coupling and the mechanism of the soil freezing-thawing process.

Improved modeling of permafrost active layer freeze-thaw plays a crucial role in understanding the response of the Arctic ecosystem to the accelerating warming trend in the region over the past decades. However, modeling the dynamics of the active layer at diurnal time scale remains challenging using the traditional models of freeze-thaw processes. In this study, a physically based analytical model is formulated to simulate the thaw depth of the active layer under changing boundary conditions of soil heat flux. Conservation of energy for the active layer leads to a nonlinear integral equation of the thaw depth using a temperature profile approximated from the analytical solution of the heat transfer equation forced by ground heat flux. Temporally variable ground heat flux is estimated using non-gradient models when field observations are not available. Validation of the proposed model conducted against field data obtained from three Arctic forest and tundra sites demonstrates that the model is able to simulate both thaw depth and soil temperature profiles accurately. The model has the potential to estimate regional variability of the thaw depth for permafrost related applications. The seasonally thawed layer on top of the permafrost (active layer) is a key component of the Arctic system affected by the strong warming trend over the past decades. This soil layer experiences a pronounced seasonal cycle of freezing and thawing processes caused by the availability of Sun's energy. Mathematical modeling of the thaw depth of the active layer has remained challenging. This study formulates a novel model for the simulation of the diurnal cycle of thawing process. The formulation is developed using innovative models of heat flux that goes into the soil and soil temperature profile. Ground heat flux is derived from available energy at the land surface using a theory of surface heat flux partition. The soil temperature profile is expressed using ground heat flux within the active layer. The proposed model has been validated against field observations during thawing season. The model simulation and field observations of the thaw depth are in a good agreement at three Arctic study sites with forest and tundra surface conditions. The proposed formulation can be used for modeling freeze-thaw cycles of the active layer at the regional scales since data on surface available energy can be obtained from remote sensing observations. The proposed model is highly effective in modeling thawing depth at higher time resolution and representing the soil energy budget Non-gradient models demonstrate a strong capability to model soil energy budget in data-sparse harsh environments

Ground heat flux (G0) is a key component of the land-surface energy balance of high-latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G0 is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstruct G0 across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using available G0 data (measured or modeled) for snow-free period as a reference. When observed G0 is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state-of-the-art uncertainty quantification methods, the developed G0 reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies. Ground heat flux is the energy that goes into or comes out from belowground that controls the soil freeze-thaw process in high-latitude regions. Its changes under climate warming will influence variations in the soil's seasonal thawing depth and permafrost thickness and spatial extent. Available data on ground heat flux are very sparse from both direct field measurements and large-scale model outputs in the Arctic. This study combines detailed modeling and uncertainty quantification methods to accurately reconstruct the ground heat flux from shallow soil temperature observations and estimates from predictive models, which are more readily available for the Arctic. Since the approach relies on several assumptions, we also quantify the uncertainty of the estimated ground heat flux. The reconstructed ground heat fluxes using the method developed in this study match well with the fluxes observed or derived from the predictive model. The soil properties inferred from the developed process are also consistent with the values observed for typical soils. Ground heat flux is reconstructed from various types of shallow soil temperature and auxiliary data using an analytical heat transfer model Uncertainty quantification methods are applied to infer model parameters and increase simulation efficiency drastically The efficacy of the proposed ground heat flux reconstruction framework is shown by agreement between simulation and observation

Litter decomposition represents a major path for atmospheric carbon influx into Arctic soils, thereby controlling below-ground carbon accumulation. Yet, little is known about how tundra litter decomposition varies with microenvironmental conditions, hindering accurate projections of tundra soil carbon dynamics with future climate change. Over 14 months, we measured landscape-scale decomposition of two contrasting standard litter types (Green tea and Rooibos tea) in 90 plots covering gradients of micro-climate and -topography, vegetation cover and traits, and soil characteristics in Western Greenland. We used the tea bag index (TBI) protocol to estimate relative variation in litter mass loss, decomposition rate (k) and stabilisation factor (S) across space, and structural equation modelling (SEM) to identify relationships among environmental factors and decomposition. Contrasting our expectations, microenvironmental factors explained little of the observed variation in both litter mass loss, as well as k and S, suggesting that the variables included in our study were not the major controls of decomposer activity in the soil across the studied tundra landscape. We use these unexpected findings of our study combined with findings from the current literature to discuss future avenues for improving our understanding of the drivers of tundra decomposition and, ultimately, carbon cycling across the warming Arctic.

Accurate initial soil conditions play a crucial role in simulating soil hydrothermal and surface energy fluxes in land surface process modeling. This study emphasized the influence of the initial soil temperature (ST) and soil moisture (SM) conditions on a land surface energy and water simulation in the permafrost region in the Tibetan Plateau (TP) using the Community Land Model version 5.0 (CLM5.0). The results indicate that the default initial schemes for ST and SM in CLM5.0 were simplistic, and inaccurately represented the soil characteristics of permafrost in the TP which led to underestimating ST during the freezing period while overestimating ST and underestimating SLW during the thawing period at the XDT site. Applying the long-term spin-up method to obtain initial soil conditions has only led to limited improvement in simulating soil hydrothermal and surface energy fluxes. The modified initial soil schemes proposed in this study comprehensively incorporate the characteristics of permafrost, which coexists with soil liquid water (SLW), and soil ice (SI) when the ST is below freezing temperature, effectively enhancing the accuracy of the simulated soil hydrothermal and surface energy fluxes. Consequently, the modified initial soil schemes greatly improved upon the results achieved through the long-term spin-up method. Three modified initial soil schemes experiments resulted in a 64%, 88%, and 77% reduction in the average mean bias error (MBE) of ST, and a 13%, 21%, and 19% reduction in the average root-mean-square error (RMSE) of SLW compared to the default simulation results. Also, the average MBE of net radiation was reduced by 7%, 22%, and 21%.

Seasonal snow cover has an important impact on the difference between soil- and air temperature because of the insulation effect, and is therefore a key parameter in ecosystem models. However, it is still uncertain how specific variations in soil moisture, vegetation composition, and surface air warming, combined with snow dynamics such as compaction affect the difference between soil- and air temperature. Here, we present an analysis of 8 years (2012-2020) of snow dynamics in an Arctic ecosystem manipulation experiment (using snow fences) on Disko Island, West Greenland. We explore the snow insulation effect under different treatments (mesic tundra heath as a dry site and fen area as a wet site, snow addition from snow fences, warming using open top chambers, and shrub removal) on a plot-level scale. The snow fences significantly changed the inter-annual variation in snow depths and -phenology. The maximum annual mean snow depths were 90 cm on the control side and 122 cm on the snow addition side during all study years. Annual mean snow cover duration across 8 years was 234 days on the control side and 239 days on the snow addition side. The difference between soil- and air temperature was significantly higher on the snow addition side than on the control side of the snow fences. Based on a linear mixed-effects model, we conclude that the snow depth was the decisive factor affecting the difference between soil- and air temperature in the snow cover season (p < 0.0001). The change rate of the difference between soil- and air temperature, as a function of snow depth, was slower during the period before maximum snow depth than during the period between the day with maximum snow depth until snow ending day. During the snow-free season, the effects of the open top chambers were stronger than the effects of the shrub removal, and the combination of both contributed to the highest soil temperature in the dry site, but the warming effect of open top chambers was limited and shrub removal warmed soil temperature in the wet site. The warming effects of open top chambers and shrub removal were weakened on the snow addition side, which indicates a lagged effect of snow on soil temperature. This study quantifies important dynamics in soil-air temperature offsets linked to both snow and ecosystem changes mimicking climate change and provides a reference for future surface process simulations.

Soil water content (SWC) and soil temperature (ST) are important indicators of environmental change in permafrost regions. In this study, we conducted soil sampling at 89 locations in the Three Rivers Headwaters Region (TRHR) to investigate the individual and synergistic effects of environmental factors on SWC and ST. We used multivariable regression and random forest modelling to analyse the data. The results show that SWC and ST were higher in the southeast TRHR than in the northwest and higher in surface layers than deeper soil layers. The most important factors affecting SWC in the 0-20 cm and 20-40 cm soil layers were soil bulk density and precipitation, while bulk density was the most important factor in the 40-60 cm layer, and soil bulk density and steppe vegetation were the most important factors in the 60-80 cm layer. For ST, altitude, temperature and slope gradient were the drivers in the 0-20 cm surface layer, while altitude and temperature were the most critical drivers in the 20-40 cm, 40-60 cm and 60-80 cm layers. Overall, bulk density and altitude were the key environmental factors influencing SWC and ST values, respectively. The outcomes of this study provide valuable insights into the environmental factors that impact the SWC and ST in permafrost regions, which can guide decision-making processes for sustainable soil management in the context of climate change.

Impacts of increased winter snowfall and warmer summer air temperatures on nitrous oxide (N2O) dynamics in arctic tundra are uncertain. Here we evaluate surface N2O dynamics in both wet and dry tundra in West Greenland, subjected to field manipulations with deepened winter snow and summer warming. The potential denitrification activity (PDA) and potential net N2O production (N2Onet) were measured to assess denitrification and N2O consumption potential. The surface N2O fluxes averaged 0.49 +/- 0.42 and 2.6 +/- 0.84 mu g N2O-N m- 2 h-1, and total emissions were 212 +/- 151 and 114 +/- 63 g N2O-N scaled to the entire study area of 0.15 km2, at the dry and wet tundra, respectively. The experimental summer warming, and in combination with deepened snow, significantly increased N2O emissions at the dry tundra, but not at the wet tundra. The deepened snow increased winter soil temperatures and growing season soil N availability (DON, NH4+-N or NO3- -N), but no main effect of deepened snow on N2O fluxes was found at either tundra ecosystem. The mean PDA was 5- and 121-fold higher than the N2Onet at the dry and wet tundra, respectively, suggesting that N2O might be reduced and emitted as dinitrogen (N2). Overall, this study reveals modest but evident surface N2O fluxes from tundra ecosystems in Western Greenland, and suggests that projected increases in winter precipitation and summer air temperatures may increase N2O emissions, particularly at the dry tundra dominating in this region.

Known as the roof of the world , 50%-56% area of the Qinghai-Tibet Plateau (QTP) is covered by seasonal frozen ground (SFG), which has an important impact on local and global climate change, terrestrial ecosystems, and regional energy and hydrological cycles. In this study, long-term observational data of air and soil water (precipitation and soil moisture) and heat [surface air temperature (SAT) and soil temperature (ST)] at 30 meteorological stations were used to study the temporal and spatial changes of SFG and their possible causes for the central-eastern QTP (CEQTP). The results showed that latitude and altitude are the key factors affecting the spatial distributions of seasonal freeze-thaw activities of CEQTP. The stations with deeper freeze depths and more freeze days are mainly located in high-altitude and high-latitude regions, and those with shallower freeze depths and fewer freeze days are mainly located in the low-altitude and low-latitude regions of the southern QTP. This may be the reason that latitude and altitude are the key factors determining the temperature distribution on the CEQTP. SAT, ST, precipitation, and soil moisture are all significant correlations with the freeze depth, freeze days, freeze start date (FSD) and thaw end date (TED), and the abrupt change years of them are also consistent; they are the important factors affecting the freeze-thaw changes (FTCs) of SFG. Among them, ST is the key factor influencing the FTCs of SFG, and the variations of monthly average soil temperature (MAST) at 0-320 cm depths are the inverse of those of the monthly average freeze depth and freeze days during the year. Using the MAST data at 0-320 cm depths and the 0? ST threshold, the soil freeze-thaw processes at different depths on the CEQTP are revealed. Affected by global warming, SAT and ST at different depths on the CEQTP have shown the upward trends since the 1980s. Additionally, precipitation and soil moisture have also increased substantially, especially since the late 1990s. Enhancement of warming and wetting conditions from the land surface to the deep soil have accelerated the thawing of SFG, and led to the delay of FSD and the advance of TED, which further caused the reduction of freeze depth and freeze days of SFG on the QTP, especially since the late 1990s.