Climate Change Attribution Using Empirical Decomposition of Climatic Data
Craig Loehle, Nicola Scafetta

TL;DR
This study uses empirical decomposition of climatic data to distinguish natural cycles from anthropogenic effects, suggesting current models underestimate natural variability and project less warming than previously thought.
Contribution
It introduces a novel empirical model based on solar cycles to better separate natural and human-induced climate influences.
Findings
Natural 60-year cycles significantly influence temperature trends.
Anthropogenic contribution to warming since 1970 is about half of IPCC estimates.
Projected 21st-century warming is less than 1°C.
Abstract
The climate change attribution problem is addressed using empirical decomposition. Cycles in solar motion and activity of 60 and 20 years were used to develop an empirical model of Earth temperature variations. The model was fit to the Hadley global temperature data up to 1950 (time period before anthropogenic emissions became the dominant forcing mechanism), and then extrapolated from 1951 to 2009. After subtraction of the model, the residuals showed an approximate linear upward trend after 1942. Herein we assume that the residual upward warming observed during the second half of the 20th century has been mostly induced by a worldwide rapid increase of anthropogenic emissions, urbanization and land use change. The warming observed before 1942 is relatively small and it is assumed to have been mostly naturally induced by a climatic recovery since the Little Ice Age of the 17th century…
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