Ehstoday 1606 Smokestack
Ehstoday 1606 Smokestack
Ehstoday 1606 Smokestack
Ehstoday 1606 Smokestack
Ehstoday 1606 Smokestack

Analysis: 99% Probability that Manmade Emissions Have Caused Climate Change

April 16, 2014
A physics professor at McGill University in Montreal claims that his analysis of temperature data since the year 1500 all but rules out the possibility that global warming is just a natural fluctuation in the earth’s climate.

One of the coldest winters in recent memory has provided plenty of fodder for global-warming skeptics. However, a physics professor at McGill University in Montreal claims that his analysis of temperature data since the year 1500 all but rules out the possibility that global warming is just a natural fluctuation in the earth’s climate.

Professor Shaun Lovejoy asserts that his new study, published online in the journal Climate Dynamics, represents a new approach to answering the question of whether global warming in the industrial era is the result of manmade 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 says. “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.”

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 can be ruled out “with confidence levels great than 99 percent, and most likely greater than 99.9 percent.”

'Multi-Proxy Climate Reconstructions'

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 manmade climate influences – a simplification that he says is justified by the tight relationship between global economic activity and the emission of greenhouse gases and particulate pollution.

“This allows the new approach to implicitly include the cooling effects of particulate pollution that are still poorly quantified in computer models,” Lovejoy says.

While his new study makes no use of the huge computer models commonly used by scientists to estimate the magnitude of future climate change, Lovejoy asserts that his findings effectively complement those of the International Panel on Climate Change, he says.

His study predicts – with 95 percent confidence – that a doubling of carbon-dioxide levels in the atmosphere would cause the climate to warm by between 2.5 and 4.2 C. Lovejoy points out that the range is more precise than – but in line with -- the International Panel on Climate Change’s prediction that temperatures would rise by 1.5 to 4.5 C if CO2 concentrations double.

“We’ve had a fluctuation in average temperature that’s just huge since 1880 – on the order of about 0.9 degrees Celsius,” Lovejoy says. “This study shows that the odds of that being caused by natural fluctuations are less than one in a hundred and are likely to be less than one in a thousand. While the statistical rejection of a hypothesis can’t generally be used to conclude the truth of any specific alternative, in many cases – including this one – the rejection of one greatly enhances the credibility of the other.”

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