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Soil Temperature in the Yamalo-Nenets Autonomous Okrug Based on ERA5 Reanalysis Data and CMIP6 Models
https://doi.org/10.7868/S2412376526020113
Abstract
The relevance of this study is determined by the current pace of climate change in the Arctic region and the threats associated with the degradation of permafrost (PF), which results in the landscape transformation, infrastructure damage and the release of greenhouse gases. The analysis of changes of the surface air temperatures (SAT) and permafrost (PFT) in the Yamalo-Nenets Autonomous Okrug during the period 1980–2020 was carried out using data of weather stations, measurements in thermometric boreholes, the ERA5 reanalysis, and CMIP6 climate models. The CMIP6 model ensemble was evaluated by comparing the SAT values with the ERA5 reanalysis data using three criteria: the error in the mean SAT, the standard deviation errors, and a fraction of points where the sign of the linear SAT trend corresponded to the trend obtained from ERA5 data. The selected models were used to analyze the simulation of average monthly PFT with depth from the surface to 3 meters, using the root-mean-square error (MSE) and the index of agreement (AI) between observational data and models. It is shown that ERA5 qualitatively reproduces the SAT in the study region (correlation up to 0.95), but with limitations in assessing the PRT values, especially at greater depths. The reanalysis underestimates instrumental PFT values by 1.5–2.5°C and also fails to reproduce certain extremes. The CMIP6 models demonstrate significant variations in the quality of simulation of the PRT regimes depending on the location and depth. The GFDL-CM4 model stands out as the most reliable for estimating the PR temperature profile in the region, with MSE values of 1–13, AI values of 84–98%, and a significant correlation (0.87–0.97) between the annual temperature trend of the mean monthly temperature (MMT) across various soil horizons and observational data from two boreholes. This study emphasizes the need for a comprehensive use of observational and model data, with careful evaluation of their quality, to predict the influence of climate change on the permafrost zone and the associated risks for ecosystems and infrastructure in the Yamalo-Nenets Autonomous Okrug.
About the Authors
E. Yu. ShtolRussian Federation
Moscow
D. D. Bokuchava
Russian Federation
Moscow
G. N. Kraev
Russian Federation
Moscow
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Supplementary files
For citation: Shtol E.Y., Bokuchava D.D., Kraev G.N. Soil Temperature in the Yamalo-Nenets Autonomous Okrug Based on ERA5 Reanalysis Data and CMIP6 Models. Ice and Snow. 2026;66(2):379–396. https://doi.org/10.7868/S2412376526020113
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