Search

Permafrost in Mongolia is located in the transition zone between high-latitude and high-altitude permafrost regions of the Northern Hemisphere, with large temperature differences and complex subsurface characteristics. In this study, the reliability of the skin temperature data from the ERA5-Land product covering Mongolia is assessed via site observations. The ERA5-Land skin temperature dataset shows a cold bias, which is more pronounced in the cold season. Following calibration based on elevation differences, significant improvements are observed at both the annual scale (92 % improvement in RMSE (root mean square error) and 98 % improvement in MBE (mean bias error)) and the seasonal scale (78 % improvement in RMSE and 82 % improvement in MBE). Additionally, the spatial variations in the surface freezing index (SFI) and surface thawing index (STI) are most pronounced in the central and northeastern Mongolia. The SFI exhibits a significant decreasing trend of 7.16 °C·d/year, while the STI shows a significant increasing trend of 4.49 °C·d/year. Furthermore, the permafrost extent in Mongolia is simulated from 1950 to 2022 using the frost number (Fn) model and the temperature on top of permafrost (TTOP) model. The validated results indicate that the accuracy of the Fn model is relatively high, with an overall accuracy of 0.9 and a Kappa coefficient of 0.47. The permafrost extent in Mongolia has declined from 734.7 × 103 km2 in the 1950 s to 480.1 × 103 km2 in the 2010 s, with a prominent decrease of 3.2 × 103 km2/decade after 1994. According to the variations in permafrost extent during past 72 years, the Hovsgol and Khentii Mountain ranges have experienced significant permafrost degradation.

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 × 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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

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 × 10 6  km 2 , and the results showed some discrepancies between published and simulated permafrost extent mainly located in isolated permafrost regions., (Copyright © 2019 Elsevier B.V. All rights reserved.)