The present work is a continuation of an interdecadal climate change study based on the surface data from meteorological stations in the South Urals. Mean monthly air temperature and monthly atmospheric precipitation data from 17 stations covering 1936-2019 were used to determine anomalies' variability. The results show that positive temperature anomalies prevail in January, May, July, September, November, and December. Negative temperature anomalies are more common for February, March, April, June, August, October, specific seasons, and annual air temperature anomalies. An equal number of anomalies of both signs are characteristic for the annual precipitation, namely negative anomalies at most meteorological stations prevail in the winter season, positive anomalies outweigh in the summer season.
Local climate changes differ significantly from global trends and require tailored mitigation practices. Here, we analyze the surface temperature data from the network of meteorological stations in the Southern Urals and the numerical experiments over the period from 1979 to 2012. The isolated greenhouse effect was evaluated using the global atmospheric general circulation model (ECHAM5). Simulations with constant concentrations of CO2 and CH4 at the level of the 1980s describe the real values of surface temperature better than scenarios in which the concentration of greenhouse gases changed according to observations.
In the article the analysis of monthly average near-surface air temperature for the period of 1940-2015 is presented, based on the observations on meteorological stations in the Southern Urals. For the study of the regional structure of the near-surface air temperatures a method of empirical orthogonal components (EOS). Correlation analysis has been performed of the defined EOC for the winter and summer seasons against indexes of the primary large-scale modes of natural climate variability of the Northern hemisphere.
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