The study, by McGill University physics professor Shaun Lovejoy, represents a new approach to the question of whether global warming in the industrial era has been caused largely by man-made emissions from the burning of fossil fuels.
Rather than using complex computer models to estimate the effects of greenhouse-gas emissions, Lovejoy examines historical data to assess the competing hypothesis: that warming over the past century is due to natural long-term variations in temperature.
"This study will be a blow to any remaining climate-change deniers," Lovejoy said.
"Their two most convincing arguments - that the warming is natural in origin, and that the computer models are wrong - are either directly contradicted by this analysis, or simply do not apply to it," he said.
Lovejoy's study applies statistical methodology to determine the probability that global warming since 1880 is due to natural variability.
His conclusion: the natural-warming hypothesis may be ruled out "with confidence levels great than 99 percent, and most likely greater than 99.9 percent."
To assess the natural variability before much human interference, the new study uses "multi-proxy climate reconstructions" developed by scientists in recent years to estimate historical temperatures, as well as fluctuation-analysis techniques from nonlinear geophysics.
The climate reconstructions take into account a variety of gauges found in nature, such as tree rings, ice cores, and lake sediments. And the fluctuation-analysis techniques make it possible to understand the temperature variations over wide ranges of time scales.
For the industrial era, Lovejoy's analysis uses carbon-dioxide from the burning of fossil fuels as a proxy for all man-made climate influences - a simplification justified by the tight relationship between global economic activity and the emission of greenhouse gases and particulate pollution, he said.
"This allows the new approach to implicitly include the cooling effects of particulate pollution that are still poorly quantified in computer models," he added.
The study is published online in the journal Climate Dynamics.