In Central Asia, the ground thermal regime is strongly affected by the interplay between topographic factors and ecosystem properties. In this study, we investigate the governing factors of the ground thermal regime in an area in Central Mongolia, which features discontinuous permafrost and is characterized by grassland and forest ecosystems. Miniature temperature dataloggers were used to measure near-surface temperatures at c. 100 locations throughout the 6 km2 large study area, with the goal to obtain a sample of sites that can represent the variability of different topographic and ecosystem properties. Mean annual near-surface ground temperatures showed a strong variability, with differences of up to 8 K. The coldest sites were all located in forests on north-facing slopes, while the warmest sites are located on steep south-facing slopes with sparse steppe vegetation. Sites in forests show generally colder near-surface temperatures in spring, summer and fall compared to grassland sites, but they are warmer during the winter season. The altitude of the measurement sites did not play a significant role in determining the near-surface temperatures, while especially solar radiation was highly correlated. In addition, we investigated the suitability of different hyperspectral indices calculated from Sentinel-2 as predictors for annual average near-surface ground temperatures. We found that especially indices sensitive to vegetation properties, such as the Normalized Difference Vegetation Index (NDVI), show a strong correlation. The presented observations provide baseline data on the spatiotemporal patterns of the ground thermal regime which can be used to train or validate modelling and remote sensing approaches targeting the impacts of climate change.

The absence of vegetation in most ice-free areas of Antarctica makes the soil surface very sensitive to atmosphere dynamics, especially in the western sector of the Antarctic Peninsula, an area within the limits of the permafrost zone. To evaluate the possible effects of regional warming on frozen soils, we conducted an analysis of ground surface temperatures (GSTs) from 2007 to 2021 from different monitoring sites in Livingston and Deception islands (South Shetlands archipelago, Antarctica). The analysis of the interannual evolution of the GST and their daily regimes and the freezing and thawing indexes reveals that climate change is showing impacts on seasonal and perennially frozen soils. Freezing Degree Days (FDD) have decreased while Thawing Degree Day (TDD) have increased during the study period, resulting in a balance that is already positive at the sites at lower elevations. Daily freeze-thaw cycles have been rare and absent since 2014. Meanwhile, the most common thermal regimes are purely frozen - F1 (daily temperatures = +0.5 degrees C). A decrease in F1 days has been observed, while the IS and T1 days increased by about 60 days between 2007 and 2021. The annual number of days with snow cover increased between 2009 and 2014 and decreased since then. The GST and the daily thermal regimes evolution point to general heating, which may be indicative of the degradation of the frozen soils in the study area.

Atmospheric conditions, topsoil properties and land cover conditions play essential roles in ground surface temperature (GST), surface air temperature (SAT) and their differences (GST-SAT). They determine the strength of the thermal forcing of the lower atmospheric boundary and the distributions of frozen ground in cold regions. However, the relative importance of these factors at various time scales and the underlying physical mechanisms remain less well understood. Here, we investigate the spatiotemporal patterns of GST-SAT and examine 11 potential factors in three categories in influencing the GST-SAT variations from 1983 to 2019 over the Tibetan Plateau (TP) using boosted regression tree models. The results show that the TP has experienced asynchronous warming in GST and SAT since 2001: a warming hiatus in SAT but continued warming in GST, resulting in a significantly increasing trend in GST-SAT. The relative importance of the three categories that influence the GSTSAT spatial variation was: atmospheric variables (56.1 %) > shallow soil properties (24.4 %) > interfacial land cover features (19.5 %). The importance of the factors also varied with the combinations of annual, seasonal, daily, day-time and night-time time scales, manifested by positive or negative effects. The interdecadal changes of net radiation, precipitation, wind speed and soil moisture amplified the asynchronous warming between air and shallow ground over the TP since the 2000s. These findings provide an in-depth understanding of the spatiotemporal variations of GST-SAT and the underlying mechanisms. This study will benefit the development of the Earth system models on the TP.

As a major parameter in the energy balance of the ground surface, temperature represents the level of exchange of energy and moisture between the ground and air. The Qinghai-Tibet Plateau (QTP) has the permafrost region with the highest altitude and the largest area in low-middle latitude of the world. The variation in ground surface temperature has an impact on the existence and development of the permafrost. Therefore, the analysis of the ground surface temperature in the QTP is significant to reflect the energy exchange in permafrost regions. This paper collected solar radiation data and calculated the conversion coefficient from total solar radiation to long-wave radiation of the ground surface on different underlying surfaces. The ground surface temperature was inversely calculated and modified based on the reception of solar radiation on different underlying surfaces. A simplified calculation model of ground surface temperature was built to reflect the ground surface temperature on different underlying surfaces of the QTP. The calculation results were compared with MODIS and showed good fitness, providing a systematic and reliable method for calculating the ground surface temperature on the QTP. The above model plays a significant role in the estimation of soil moisture, ground surface energy and water balance.

Numerous studies were published in the last two decades to evaluate and project the permafrost changes in its thermal state, mainly based on the soil temperature datasets from the Coupled Model Intercomparison Project (CMIP), and discuss the impacts of permafrost changes on regional hydrological, ecological and climatic systems and even carbon cycles. However, limited monitored soil temperature data are available to validate the CMIP outputs, resulting in the over-projection of future permafrost changes in CMIP3 and CMIP5. Moreover, future permafrost changes in CMIP6, particularly over the Qinghai -Tibet Plateau (QTP), where permafrost covers more than 40% of its territory, are still un-known. To address this gap, we evaluated and calibrated the monthly ground surface temperature (GST; 5 cm below the ground surface), which was often used as the upper boundary to simulate and project permafrost changes derived from 19 CMIP6 Earth System Models (ESMs) against in situ measurements over the QTP. We generated the monthly GST series from 1900 to 2014 for five sites based on the linear calibration models and validated them through the three other sites using the same calibration methods. Results showed that all of the ESMs could capture the dynamics of in situ GST with high correlations (r > 0.90). However, large errors were detected with a broad range of centred root-mean-square errors (1.14-4.98 degrees C). The Top 5 model ensembles (MME5) performed better than most individual ESMs and averaged multi-model ensembles (MME19). The calibrated GST performed better than the GST obtained from MME5. Both annual and seasonal GSTs exhibited warming trends with an average annual rate of 0.04 degrees C per decade in the annual GST. The average seasonal warming rate was highest in winter and spring and lowest in summer. This reconstructed GST data series could be used to simulate the long-term permafrost temperature over the QTP.

Permafrost on the Tibetan Plateau (TP) is controlled by high-elevation and the complex hydrothermal processes and energy balance on the ground surface. To successfully model or map permafrost distribution, it is necessary to parameterize near-surface air or land-surface temperatures (Ta or LST) to ground surface temperature (GST) at local-, meso-, or macro-scale. Here, a long-term experimental observation (November 2010 to December 2018) was conducted for understanding the differences between Ta and GST at a plot with 26 sites at Chalaping to the south of the Sisters Lakes in the Source Area of the Yellow River, northeastern TP. Results show that GST varies considerably within an area of about 3.5 km2 under the combined thermal influences of surface vegetation, soil moisture conditions, and microtopography. Mean annual GST (MAGST) ranged from -0.55 to -3.02 degrees C, with an average of -1.35 +/- 0.63 degrees C. The surface offset varied from 1.01 to 3.90 degrees C, with an average of 2.72 +/- 0.70 degrees C. The difference between monthly Ta and monthly GST decreased from 4.64 +/- 2.09 degrees C in January to 1.09 +/- 1.34 degrees C in July and then gradually increased to 5.61 +/- 2.53 degrees C in November. The active layer thickness (ALT) calculated with the ground-surface thawing index ranged from 0.85 to 1.95 m, with an average of 1.51 +/- 0.33 m. Annual freezing N-factors and annual thawing N-factors were averaged at 0.58 +/- 0.12 and 1.31 +/- 0.28, respectively. Although weakly, hourly and daily GST values are positively correlated to NDVI, while ALT negatively correlated with NDVI. This study demonstrates the complex thermal regimes on the ground surface, even within a small area despite the relatively consistent topography. It will likely facilitate the parameterization of the upper thermal boundary of permafrost modeling or mapping on the TP where the landscapes are characterized by extensive presence of dwarf alpine meadow and alpine steppe, further contributing to the study in ecosystem feedbacks to the regional climate change.

Snow cover distribution has a profound impact on ground temperature, on thickness of the active layer, and on permafrost. The purpose of this study was to evaluate the effects of snow cover on soil thermal regimes in West Siberia and to characterize the meso- and micro-scale spatial variation of winter ground surface temperature (GST). Maximum snow cover thickness (> 80 cm) and duration (similar to 8 months) were recorded for the lower elevation areas and in the forest site (using a vertical array of Muttons). Shallow snow cover and a late snow formation characterized open raised areas with shallow permafrost. Our results indicate that 20 cm snow cover thickness is the minimum for generating a significant insulating effect. Date of snow cover formation with thickness > 20 cm had the strongest influence on soil temperature regimes. We found a significant negative correlation between winter GST and elevation. This relationship is indirectly controlled by snow cover redistribution. We additionally have shown that elevation, n-factor and winter GST are the variables most significantly affecting thaw depth in permafrost-affected soils. This research dictates the need for taking into account snowfall, and its redistribution due to the variability of local factors, in predicting the effects of climate change on soil temperatures and active layer depth. According to long-term meteorological data for West Siberia, a temporal trend in snowfall is not observed. Nevertheless, considerable interannual fluctuations in snow cover thickness can lead to interannual variations in the soil thermal regimes.

Ecology, hydrology, and natural resources in the source areas of the Yangtze and Yellowrivers (SAYYR) are closely linked to interactions between climate and permafrost. However, a comprehensive study of the interactions is currently hampered by sparsely-and unevenly-distributed monitoring sites and limited field investigations. In this study, the thermal regime of warm-dry permafrost in the SAYYR was systematically analyzed based on extensive data collected during 2010-2016 of air temperature (T-a), ground surface temperature (GST) and ground temperature across a range of areas with contrasting land-surface characteristics. Mean annual T-a (MAAT) and mean annual GST (MAGST) were regionally averaged at -3.19 +/- 0.71 degrees C and -0.40 +/- 1.26 degrees C. There is a close relationship between GST and T-a (R-2= 0.8477) as obtained by a linear regression analysis with all available daily averages. The mean annual temperature at the bottom of the active layer (T-TOP) was regionally averaged at -0.72 +/- 1.01 degrees C and mostly in the range of -1.0 degrees C and 0 degrees C except at Chalaping (similar to-2.0 degrees C). Surface offset (MAGST-MAAT) was regionally averaged at 2.54 +/- 0.71 degrees C. Thermal offset (TTOP-MAGST) was regionally averaged at -0.17 +/- 0.84 degrees C, which was generally within-0.5 degrees C and 0.5 degrees C. Relatively consistent thermal conductivity between the thawed and frozen states of the soils may be responsible for the small thermal offset. Active layer thickness was generally smaller at Chalaping than that on other parts of the QTP, presumably due to smaller climatic continentality index and the thermal dampening of surface temperature variability under the presence of dense vegetation and thick peaty substrates. We conclude that the accurate mapping of permafrost on the rugged elevational QTP could be potentially obtained by correlating the parameters of GST, thermal offset, and temperature gradient in the shallow permafrost. (c) 2017 Elsevier B.V. All rights reserved.

Surface temperature is critical for the simulation of climate change impacts on the ecology, environment, and particularly permafrost in the cryosphere. Virtually, surface temperatures are different in the near-surface air temperature (T-a) measured at a screen-height of 1.5-2 m, the land surface temperature (LST) on the top canopy layer, and the ground surface temperature (GST) 0-5 cm beneath the surface cover. However, not enough attention has been concentrated on the difference in these surface temperatures. This study aims at quantifying the distinction of surface temperatures by the comparisons and numerical simulations of observational field data collected in a discontinuous permafrost region on the northeastern Qinghai-Tibet Plateau (QTP). We compared the hourly, seasonal and yearly differences between T omega, IST, GST, and ground temperatures, as well as the freezing and thawing indices, the N-factors, and the surface and thermal offsets derived from these temperatures. The results showed that the peak hourly LST was reached earliest, closely followed by the hourly T-a. Mean annual LST (MALST) was moderately comparable to mean annual T-a (MAAT), and both were lower than mean annual GST (MAGST). Surface offsets (MAGST-MAAT) were all within 3.5 degrees C, which are somewhat consistent with other parts of the QTP but smaller than those in the Arctic and Subarctic regions with dense vegetation and thick, long-duration snow cover. Thermal offsets, the mean annual differences between the ground surface and the permafrost surface, were within -0.3 degrees C, and one site was even reversed, which may be relevant to equally thawed to frozen thermal conductivities of the soils. Even with identical T-a (comparable to MAAT of -3.27 and -3.17 degrees C), the freezing and thawing processes of the active layer were distinctly different, due to the complex influence of surface characteristics and soil, textures. Furthermore, we employed the Geophysical Institute Permafrost Lab (GIPL) model to numerically simulate the dynamics of ground temperature driven by T-a, LST, and GST, respectively. Simulated results demonstrated that GST was a reliable driving indicator for the thermal regime of frozen ground, even if no thermal effects of surface characteristics were taken into account. However, great biases of mean annual ground temperatures, being as large as 3 degrees C, were induced on the basis of simulations with LST and T-a when the thermal effect of surface characteristics was neglected. We conclude that quantitative calculation of the thermal effect of surface characteristics on GST is indispensable for the permafrost simulations based on the T-a datasets and the LST products-that derived from thermal infrared remote sensing.

Multiple studies demonstrate Northwest Alaska and the Alaskan North Slope are warming. Melting permafrost causes surface destabilization and ecological changes. Here, we use thermistors permanently installed in 1996 in a borehole in northwestern Alaska to study past, present, and future ground and subsurface temperature change, and from this, forecast future permafrost degradation in the region. We measure and model Ground Surface Temperature (GST) warming trends for a 10 year period using equilibrium Temperature-Depth (TD) measurements from borehole T96-012, located near the Red Dog Mine in northwestern Alaska part of the Arctic ecosystem where a continuous permafrost layer exists. Temperature measurements from 1996 to 2006 indicate the subsurface has clearly warmed at depths shallower than 70 m. Seasonal climate effects are visible in the data to a depth of 30 m based on a visible sinusoidal pattern in the TD plots that correlate with season patterns. Using numerical models constrained by thermal conductivity and temperature measurements at the site, we show that steady warming at depths of similar to 30 to 70 m is most likely the direct result of longer term (decadal-scale) surface warming. The analysis indicates the GST in the region is warming at similar to 0.44 +/- 0.05 degrees C/decade, a value consistent with Surface Air Temperature (SAT) warming of similar to 1.0 +/- 0.8 degrees C/decade observed at Red Dog Mine, but with much lower uncertainty. The high annual variability in the SAT signal produces significant uncertainty in SAT trends. The high annual variability is filtered out of the GST signal by the low thermal diffusivity of the subsurface. Comparison of our results to recent permafrost monitoring studies suggests changes in latitude in the polar regions significantly impacts warming rates. North Slope average GST warming is similar to 0.9 +/- 0.5 degrees C/decade, double our observations at RDM, but within error. The RDM warming rate is within the warming variation observed in eastern Alaska, 0.36-0.71 degrees C/decade, which suggests changes in longitude produce a smaller impact but have warming variability likely related to ecosystem, elevation, microclimates, etc. changes. We also forward model future warming by assuming a 1D diffusive heat flow model and incorporating latent heat effects for permafrost melting. Our analysis indicates similar to 1 to 4 m of loss at the upper permafrost boundary, a similar to 145 +/- 100% increase in the active layer thickness by 2055. If warming continues at a constant rate of similar to 0.44 +/- 0.05 degrees C/decade, we estimate the 125 m thick zone of permafrost at this site will completely melt by similar to 2150. Permafrost is expected to melt by similar to 2200, similar to 2110, or similar to 2080, if the rate of warming is altered to 0.25, 0.90, or 2.0 degrees C/decade, respectively, as an array of different climate models suggest. Since our model assumes no advection of heat (a more efficient heat transport mechanism), and no accelerated warming, our current prediction of complete permafrost loss by 2150 may overestimate the residence time of permafrost in this region of Northwest Alaska. (C) 2016 The Authors. Published by Elsevier B.V.