Climate warming changes in heat fluxes within the atmosphere-surface cover-soil system and affects the thermal state of permafrost. A comparison of heat fluxes from the atmosphere to the soil during the period with positive air temperatures and from the soil to the atmosphere during the cold period makes it possible to assess the permafrost stability. Snow and moss cover are important factors influencing heat fluxes. The influence of surface fluxes on heat fluxes is estimated based on mathematical modeling and numerical experiments on the model. The processing of data from field measurements of soil temperature made it possible to determine the heat fluxes for the cold and partially warm periods of the year. A comparison of the data from model calculations and measurements of heat fluxes showed a satisfactory agreement. The difference between them from December to February did not exceed 4%; in November and March, 9 and 8%, respectively. In 2023/24, during the period with negative air temperatures lasting 255 days with an average air temperature of -7 degrees C, soil heat losses amounted to 76.5 and 92.3 MJ/m2 with snow thickness of 1.14 and 0.63 m, respectively; the average values of heat fluxes from October to March were 4.9 and 5.9 W/m2. According to model calculations, with an average daily positive air temperature of 6.8 degrees C, the loss by the soil in winter is 10 MJ/m2 less than the heat flux into the soil in summer, which leads to permafrost degradation. At snow cover depth of 0.5 m, the heat input into the soil in summer coincides with the heat loss in winter. With a higher snow cover depth, the heat flux from the soil to the atmosphere decreases, soil cooling decreases, and permafrost degradation will occur. The same processes will occur when the snow cover is 1-m-deep and the moss cover is less than 3-cm-thick. For a moss cover of greater thickness, the thermal stability of permafrost rocks is preserved. Numerical experiments on the model estimated the heat fluxes and the thickness of the active layer for different snow and moss cover thicknesses and atmospheric air temperatures.

Climate change occurs more rapidly at high latitudes, making polar ecosystems highly vulnerable to environmental changes. Plants respond to these conditions by altering the fluxes of water vapor (H2O) and carbon dioxide (CO2). This study analyzed the seasonal variability of the Net Ecosystem Exchange (NEE) of CO2, as well as the sensible (H) and latent (LE) heat fluxes, in two ecosystems in north-central Siberia: a subarctic palsa mire near Igarka, and a mature larch forest near Tura. The flux responses to variations in atmospheric parameters were also assessed. Experimental data were collected from 2019 to 2023 using eddy covariance methods. The results showed that both permafrost ecosystems consistently served as net atmospheric CO2 sinks during the growing seasons, despite significant year-to-year meteorological variations. From 2019 to 2023, summer NEE ranged from -62.9 to -120.2 gC m-2 in the Igarka palsa mire and from -63.5 to -83.6 gC m-2 in the Tura larch forest. During summer periods characterized by prolonged insufficient soil moisture, higher air temperatures, and limited precipitation, the palsa mire exhibited reduced CO2 uptake (i.e., less negative NEE) and Gross Primary Production (GPP) compared to the larch forest. These results suggest that larch forests may be more resilient to climate change than palsa mires. This resilience is primarily linked to deep-rooted water access and conservative stomatal control in larch, whereas palsa mire vegetation depends strongly on surface moisture availability. H and LE fluxes exhibited significant interannual variations, primarily due to variations in incoming solar radiation and precipitation. No significant LE decrease occurred during periods of low precipitation in 2019 and 2020 when drought conditions were observed at both stations during the summer. Maximum H and LE flux rates occurred in June and July when net radiation values were at their maximum for both ecosystems. These findings underscore the urgent need for ecosystem-specific climate strategies, as differential resilience could significantly impact future carbon dynamics in the rapidly warming Arctic.

With global warming and intensified rainfall, the heat and moisture transfer processes within frozen subgrades beneath asphalt pavements have become increasingly complex, posing risks to highway stability in cold regions. This study developed a multi-physics coupled indoor simulation system based on a typical asphalt highway structure on the Qinghai-Tibet Plateau to examine subgrade responses under solar radiation, wind, and rainfall. Results showed that rainfall shifted the dominant depth of moisture migration from 7 cm to 12 cm, with moisture at 2 cm and 7 cm increasing rapidly by 2.67 % and 1.58 %, respectively. A nonlinear decrease-increase pattern was observed at 12 cm due to the capillary barrier effect. Evaporative latent heat significantly suppressed surface warming, reducing the temperature rise at 2 cm by 59.2 %, and delayed heat transfer to deeper layers (reductions of 54.5 %-64.7 %). A cumulative heat flux prediction model, incorporating solar radiation, evaporation, convection, and surface wetting, showed high accuracy (R-2 = 0.981 and 0.952; relative errors: 4.1 % and 9.6 %). Sensitivity analysis identified the surface wetting rate coefficient (beta) and evaporation attenuation coefficient (gamma) as dominant factors (F > 6.0). These findings improve understanding of rainfall-induced thermal effects and offer guidance for climate-resilient road infrastructure in permafrost regions.

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

Little is known about the mechanism of climate-vegetation coverage coupled changes in the Tibetan Plateau (TP) region, which is the most climatically sensitive and ecologically fragile region with the highest terrain in the world. This study, using multisource datasets (including satellite data and meteorological observations and reanalysis data) revealed the mutual feedback mechanisms between changes in climate (temperature and precipitation) and vegetation coverage in recent decades in the Hengduan Mountains Area (HMA) of the southeastern TP and their influences on climate in the downstream region, the Sichuan Basin (SCB). There is mutual facilitation between rising air temperature and increasing vegetation coverage in the HMA, which is most significant during winter, and then during spring, but insignificant during summer and autumn. Rising temperature significantly enhances local vegetation coverage, and vegetation greening in turn heats the atmosphere via enhancing net heat flux from the surface to the atmosphere. The atmospheric heating anomaly over the HMA thickens the atmospheric column and increases upper air pressure. The high pressure anomaly disperses downstream via the westerly flow, expands across the SCB, and eventually increases the SCB temperature. This effect lasts from winter to the following spring, which may cause the maximum increasing trend of the SCB temperature and vegetation coverage in spring. These results are helpful for estimating future trends in climate and eco-environmental variations in the HMA and SCB under warming scenarios, as well as seasonal forecasting based on the connection between the HMA eco-environment and SCB climate.

The impact of moderately absorbing aerosols on the energy budget over Central Europe is discussed, based on experimental observations and numerical simulations obtained for the summer of 2015. Aerosol events, defined as aerosol optical depth (AOD) at 500 nm greater than 0.15, especially in August, are mostly attributed to transport of biomass burning (BB) from Eastern Europe. Shortwave (SW) aerosol radiative forcings (ARF) at the surface and the top of the atmosphere (TOA) are estimated from ensembles of ten and eight observational and model-based approaches, respectively. Different measuring methods, including unmanned aviation system (UAS) and ground-based measurements, radiative transfer models, including MOTRAN and FuLiou, and parameterisations of aerosol optical properties regarding full vertical profiles, columnar and surface properties, are used in these approaches. The mean ARF is-15.9 +/- 2.1 W/ m2,-9.1 +/- 1.4 W/m2, and 7.0 +/- 1.0 W/m2, respectively, for the Earth's surface, TOA, and atmosphere under clear conditions for June-August 2015. During an aerosol event with AOD peak of about 0.6 at 500 nm, the daily mean surface, TOA, and atmosphere ARF are around-30,-18, and 13 W/m2, respectively. The mean ARF differences between all methods are about 4.0 W/m2 for the surface and about 2.3 W/m2 for the TOA, which correspond to 23% of ensemble means. Aerosols are also shown to have a significant impact on observed surface sensible and latent heat fluxes for the study period. Flux sensitivity to AOD for a solar zenith angle of 45? is-70 +/- 41 W/ m2/tau 500,-112 +/- 56 W/m2/tau 500, and-119 +/- 19 W/m2/tau 500, respectively, for sensible, latent, and net SW and longwave (LW) radiation flux. When averaged over day time, sensitivities of sensible heat, latent heat fluxes, and net radiation fluxes to AOD are reduced by about 50%, 20%, and 70%, respectively.

The ground surface soil heat flux (G(0)) is very important to simulate the changes of frozen ground and the active layer thickness; in addition, the freeze-thaw cycle will also affect G(0) on the Tibetan Plateau (TP). As G(0) could not be measured directly and soil heat flux is difficult to be observed on the TP in situ due to its high altitude and cold environment, most of previous studies have directly applied existing remote sensing-based models to estimate G(0) without assessing whether the selected model is the best one of those models for those study regions. We use in-situ observation data collected at 12 sites combined with Moderate Resolution Imaging Spectroradiometer (MODIS) data (MOD13Q1, MODLT1D, MOD09CMG, and MCD15A2H) and the China meteorological forcing dataset (CMFD-SRad and CMFD-LRad) to validate the main models during the freeze-thaw process. The results show that during the three stages (complete freezing (CF), daily freeze-thaw cycle (DFT), and complete thawing (CT)) of the freeze-thaw cycle, the root mean square error (RMSE) between the models' G(0) simulated value and the corresponding G(0) measured value is the largest in the CT phase and smallest in the CF phase. The simulated results of the second group schemes (SEBAL, Ma, SEBAL(adj), and Ma(adj)) were slightly underestimated, more stable, and closer to the measured values than the first group schemes (Choudhury, Clawson, SEBS, Choudhury(adj), Clawson(adj), and SEBSadj). The Ma(adj) scheme is the one with the smallest RMSE among all the schemes and could be directly applied across the entire TP. Then, four possible reasons leading to the errors of the main schemes were analyzed. The soil moisture affecting the ratio G(0)/R-n and the phase shift between G(0) and net radiation R-n are not considered in the schemes directly; the scheme cannot completely and correctly capture the direction of G(0); and the input data of the schemes to estimate the regional G(0) maybe bring some errors into the simulated results. The results are expected to provide a basis for selecting remote sensing-based models to simulate G(0) in frozen ground dynamics and to calculate evapotranspiration on the TP during the freeze-thaw process. The scheme Ma(adj) suitable for the TP was also offered in the study. We proposed several improvement directions of remote sensing-based models in order to enhance understanding of the energy exchange between the ground surface and the atmosphere.

Peatlands in the Western Boreal Plains act as important water sources in the landscape. Their persistence, despite potential evapotranspiration (PET) often exceeding annual precipitation, is attributed to various water storage mechanisms. One storage element that has been understudied is seasonal ground ice (SGI). This study characterized spring SGI conditions and explored its impacts on available energy, actual evapotranspiration, water table, and near surface soil moisture in a western boreal plains peatland. The majority of SGI melt took place over May 2017. Microtopography had limited impact on melt rates due to wet conditions. SGI melt released 139mm in ice water equivalent (IWE) within the top 30cm of the peat, and weak significant relationships with water table and surface moisture suggest that SGI could be important for maintaining vegetation transpiration during dry springs. Melting SGI decreased available energy causing small reductions in PET (<10mm over the melt period) and appeared to reduce actual evapotranspiration variability but not mean rates, likely due to slow melt rates. This suggests that melting SGI supplies water, allowing evapotranspiration to occur at near potential rates, but reduces the overall rate at which evapotranspiration could occur (PET). The role of SGI may help peatlands in headwater catchments act as a conveyor of water to downstream landscapes during the spring while acting as a supply of water for the peatland. Future work should investigate SGI influences on evapotranspiration under differing peatland types, wet and dry spring conditions, and if the spatial variability of SGI melt leads to spatial variability in evapotranspiration.

The variations in land surface heat fluxes affect the ecological environment, hydrological processes and the stability of surface engineering structures in permafrost regions of the Qinghai-Tibetan Plateau (QTP). Based on observation data from a meteorological station in the Tanggula site in 2005, which is located in a permafrost region on the QTP, the performances of seventeen selected the phase 5 of the Coupled Model Intercomparison Project (CMIP5) were evaluated. The results showed that these simulations did not perform well using sensible heat flux, downward shortwave radiation or upward shortwave radiation, and differences exist among the models. The average multimodel ensemble results were similar to the observed land surface heat fluxes. The results revealed that the monthly average latent heat flux and the net radiation were small in December and January and large in May, June and July. The fluctuation in the soil heat flux was well correlated with the net radiation, and the sensible heat flux was negative in January and December in northwest of the Plateau. The latent heat flux was the strongest over the southeastern QTP from May to August, and it decreased over the northwestern QTP. In contrast, the sensible heat flux was the weakest over the southeastern QTP, and it gradually increased and became dominant over the northwestern QTP. The results also indicated that there was a good correlation between the surface heating field intensity and the net radiation, with a correlation coefficient of 0.99; this indicates stronger heating over the eastern QTP than over the western QTP and stronger heating over the southern QTP than over the northern QTP. Furthermore, the Bowen ratio was higher during the freezing and thawing stages than that during the completely thawed stage. This ratio was larger over the central and northeastern QTP and smaller along the northwest edge of the QTP, which was lower (range from -0.81 to 4.86) due to the overestimation of precipitation, a smaller difference between the simulated monthly average surface temperature and the observed air temperature, and a decrease in wind speed when using the CMIP5 models in the permafrost region of the QTP. This research provides a foundation for understanding land surface heat flux characteristics in the permafrost regions on the QTP under climate change.