The Antarctic continent is a crucial area for ultimate determination of permafrost extent on Earth, and its solution depends on the theoretical assumptions adopted. In fact, it ranges from 0.022 x 10(6) to 14 x 10(6) km(2). This level of inaccuracy is unprecedented in the Earth sciences. The novelty of the present study consists in determining the extent of Antarctic permafrost not based exclusively on empirical studies but on universal criteria resulting from the definition of permafrost as the thermal state of the lithosphere, which was applied for the first time to this continent. The area covered by permafrost in Antarctica is ca. 13.9 million km(2), that is its entire surface. This result was also made possible due to the first clear determination of the boundaries and area of the continent. The Antarctic area includes (a) rocky subsurface with (b) continental ice-sheets and (c) shelf glaciers, which, due to their terrigenous origin and belonging to the lithosphere, belongs to the continent in the same way. Antarctica is covered by continuous permafrost, either in a frozen or in a cryotic state. This also significantly influences delimitation of the global extent of permafrost, which can therefore be defined much more accurately. The proposed ice reclassification and its transfer from the hydrosphere to the lithosphere will allow the uniform treatment of ice in the Earth sciences, both on Earth and on other celestial bodies.

Under the continuing influence of global warming, resolving the inconsistency of permafrost degradation rates and quantifying the spatial distribution characteristics are critical for high-altitude water cycle processes. The dynamics of permafrost degradation are mainly manifested in soil temperature, which can be measured with high accuracy and high temporal resolution. This study considered the influence of soil thermal conductivity (K) by periodic land surface temperature (LST), improved the static output of the temperature at the top of permafrost (TTOP) model, and verified the reliability of the TTOP model improvement by the Kappa coefficient. The results showed that from 2000 to 2020, the extent of dynamically simulated permafrost was 5.42 x 10(5) km(2) less than that of static simulated permafrost, and the linear degradation rate doubled. The degraded permafrost showed an increasing degradation from southeast to northwest. Among them, the degradation in the Nujiang River and the Changjiang River north of the Nyainqentanglha Mountain has exacerbated the permafrost degradation in the hinterland of the Qiangtang Plateau. Based on the AWI-CM-1-1-MR LST from CMIP6, SSP126 to SSP585 dynamic simulation results of permafrost indicate that the extent will decrease by 11.35 % by 2100. Overall, the extent and rate of permafrost degradation, considering high spatiotemporal resolution, were twice as fast as expected. Our results will inform policymakers with a more accurate spatiotemporal distribution of frozen soil types in high-altitude regions and characteristics of permafrost degradation within the watershed.

Due to sparse data and discontinuous time observations in the circum-Arctic region, freezing index and thawing index, as useful indicators, are widely used in permafrost distribution, climate changes and cold-region engineering analysis. However, previous researches on freezing/thawing index over this region were estimated based on mean monthly air temperature. In this paper, we analyzed the spatial and temporal variations of the freezing/thawing index over the circum-Arctic from 1901 to 2015 based on the daily datasets, besides monthly datasets. The results showed that freezing index had a downward changing trend and thawing index had an upward trend during 1901-2015. More important, the change trend in freezing/thawing index after 1988 was more significant than before. Furthermore, different freezing/thawing index based on daily datasets and the monthly datasets were assessed and compared according to daily data from 17 meteorological stations, comprehensive relative errors evaluation implied that freezing/thawing based on daily datasets was more accurate generally, although both of other datasets were available in calculating the freezing/thawing index. As the daily datasets are better in calculating annual freezing/thawing index, therefore, the permafrost extent was estimated by a climate-based predictive model combined with snow depth data from Canadian Meteorological Centre (CMC). Finally, considering that the published permafrost map of the circum-Arctic only shows the past permafrost distribution, but it cannot reflect the permafrost distribution after 2000 under the climate warming. Hence, we simulated the current (mean from 2000 to 2015) permafrost area which is 19.96 x 10(6) km(2), and the results showed some discrepancies between published and simulated permafrost extent mainly located in isolated permafrost regions. (c) 2019 Elsevier B.V. All rights reserved.

This study quantitatively evaluated how insulation by snow depth (SND) affected the soil thermal regime and permafrost degradation in the pan-Arctic area, and more generally defined the characteristics of soil temperature (T-SOIL) and SND from 1901 to 2009. This was achieved through experiments performed with the land surface model CHANGE to assess sensitivity to winter precipitation as well as air temperature. Simulated T-SOIL, active layer thickness (ALT), SND, and snow density were generally comparable with in situ or satellite observations at large scales and over long periods. Northernmost regions had snow that remained relatively stable and in a thicker state during the past four decades, generating greater increases in T-SOIL. Changes in snow cover have led to changes in the thermal state of the underlying soil, which is strongly dependent on both the magnitude and the timing of changes in snowfall. Simulations of the period 2001-2009 revealed significant differences in the extent of near-surface permafrost, reflecting differences in the model's treatment of meteorology and the soil bottom boundary. Permafrost loss was greater when SND increased in autumn rather than in winter, due to insulation of the soil resulting from early cooling. Simulations revealed that T-SOIL tended to increase over most of the pan-Arctic from 1901 to 2009, and that this increase was significant in northern regions, especially in northeastern Siberia where SND is responsible for 50 % or more of the changes in T-SOIL at a depth of 3.6 m. In the same region, ALT also increased at a rate of approximately 2.3 cm per decade. The most sensitive response of ALT to changes in SND appeared in the southern boundary regions of permafrost, in contrast to permafrost temperatures within the 60 degrees N-80 degrees N region, which were more sensitive to changes in snow cover. Finally, our model suggests that snow cover contributes to the warming of permafrost in northern regions and could play a more important role under conditions of future Arctic warming.

There is mounting evidence that permafrost degradation has occurred over the past century. However, the amount of permafrost lost is uncertain because permafrost is not readily observable over long time periods and large scales. This paper uses JULES, the land surface component of the Hadley Centre global climate model, driven by different realisations of twentieth century meteorology to estimate the pan-arctic changes in near-surface permafrost. Model simulations of permafrost are strongly dependent on the amount of snow both in the driving meteorology and the way it is treated once it reaches the ground. The multi-layer snow scheme recently adopted by JULES significantly improves its estimates of soil temperatures and permafrost extent. Therefore JULES, despite still having a small cold bias in soil temperatures, can now simulate a near-surface permafrost extent which is comparable to that observed. Changes in snow cover have been shown to contribute to changes in permafrost and JULES simulates a significant decrease in late twentieth century pan-Arctic spring snow cover extent. In addition, large-scale modelled changes in the active layer are comparable with those observed over northern Russia. Simulations over the period 1967-2000 show a significant loss of near-surface permafrost-between 0.55 and 0.81 million km(2) per decade with this spread caused by differences in the driving meteorology. These runs also show that, for the grid cells where the active layer has increased significantly, the mean increase is similar to 10 cm per decade. The permafrost degradation discussed here is mainly caused by an increase in the active layer thickness driven by changes in the large scale atmospheric forcing. However, other processes such as thermokarst development and river and coastal erosion may also occur enhancing permafrost loss.