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

Abstract

We proposed the implementation of the multiple regression to create a statistical model for description of the climate change under the influence of specified climate-impacting factors. This model provides not only estimates of the temporal evolution of global temperature, but also a set of corresponding confidence intervals with a given level of statistical significance (probability). The elimination of the linear trend of climatic temperature series (CRUTEM) and atmospheric CO 2 concentration allows objectively and quantitatively assess the impact of natural climate change factors. The global CRUTEM temperature responds quasi-synchronously to fluctuations in the average surface temperature of the North Atlantic (AMO index), but with a delay of about 15 years – on changes in solar activity (Wolf numbers). The linear trend of increasing CO 2 concentrations in the atmosphere explains almost all the interannual variability and reflects the linear trend of global temperature, but it covers a part of its interannual variability.