Deducing Multi-decadal Anthropogenic Global Warming Trends Using Multiple Regression Analysis

To unmask the anthropogenic global warming trend imbedded in the climate data, multiple linear re-gression analysis is often employed to filter out short-term fluctuations caused by El Niño–Southern Oscil-lation (ENSO), volcano aerosols, and solar forcing. These fluctuations are unimportant as far as their impact on the deduced multidecadal anthropogenic trends is concerned: ENSO and volcano aerosols have very little multidecadal trend. Solar variations do have a secular trend, but it is very small and uncertain. What is important, but is left out of all multiple regression analysis of global warming so far, is a long-period oscillation called the Atlantic multidecadal oscillation (AMO). When the AMO index is included as a regressor (i.e., explanatory variable), the deduced multidecadal anthropogenic global warming trend is so impacted that previously deduced anthropogenic warming rates need to be substantially revised. The deduced net an-thropogenic global warming trend has been remarkably steady and statistically significant for the past 100 yr. 1