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

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.

Climate change is expected to cause extensive vegetation changes in the Arctic: deciduous shrubs are already expanding, in response to climate warming. The results from transect studies suggest that increasing shrub cover will impact significantly on the surface energy balance. However, little is known about the direct effects of shrub cover on permafrost thaw during summer. We experimentally quantified the influence of Betula nana cover on permafrost thaw in a moist tundra site in northeast Siberia with continuous permafrost. We measured the thaw depth of the soil, also called the active layer thickness (ALT), ground heat flux and net radiation in 10 m diameter plots with natural B. nana cover (control plots) and in plots in which B. nana was removed (removal plots). Removal of B. nana increased ALT by 9% on average late in the growing season, compared with control plots. Differences in ALT correlated well with differences in ground heat flux between the control plots and B. nana removal plots. In the undisturbed control plots, we found an inverse correlation between B. nana cover and late growing season ALT. These results suggest that the expected expansion of deciduous shrubs in the Arctic region, triggered by climate warming, may reduce summer permafrost thaw. Increased shrub growth may thus partially offset further permafrost degradation by future temperature increases. Permafrost models need to include a dynamic vegetation component to accurately predict future permafrost thaw.