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Quantitative Estimates of the Impact of the Most Important Factors on Global Climate Change over the Past 150 Years

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We propose using multiple regression to create a statistical model for describing climate change under the influence of specified climate-forming factors. This model provides not only estimates of the temporal evolution of global temperature, but also a set of corresponding confidence intervals with a high level of statistical significance (probability). Eliminating the linear trend of climatic temperature series (CRUTEM) and atmospheric CO2 concentration allows an objective quantitative assessment of the impact of natural factors on climate change. The global CRUTEM temperature responds quasi-synchronously to the fluctuations in the average surface temperature of the North Atlantic (AMO index); however, to changes in solar activity (Wolf numbers), it does so with a delay of approximately 15 years. The linear trend of increasing CO2 concentration in the atmosphere explains almost all the interannual variability and reflects the linear trend of global temperature, but covers only part of its interannual variability.

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Correspondence to O. M. Pokrovsky.

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Translated by M. Chubarova

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Pokrovsky, O.M. Quantitative Estimates of the Impact of the Most Important Factors on Global Climate Change over the Past 150 Years. Izv. Atmos. Ocean. Phys. 55, 1182–1188 (2019).

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