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Study: Little chance that global warming is natural

Statistical analysis of temperature data affirms climate models

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Warmer than average temperatures prevailed across most of the globe in March 2014.

Staff Report

FRISCO — A new statistical analysis of temperature records dating back to 1500 suggests it’s more than 99 percent certain that the past century of global warming is caused by the emission of heat-trapping, industrial-age greenhouse gases. The study was published online April 6 in the journal Climate Dynamics.

In a press release, the McGill University researchers said the study doesn’t use complex computer models to estimate the effects of greenhouse-gas emissions. Instead, it examines historical data to assess the competing hypothesis that warming over the past century is due to natural long-term variations in temperature. The results all but rule out  the possibility that global warming in the industrial era is just a natural fluctuation in the earth’s climate.

“This study will be a blow to any remaining climate-change deniers,” said McGill University physics professor Shaun Lovejoy. “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 may be ruled out “with confidence levels great than 99%, 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 says.

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

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’s findings effectively complement those of the International Panel on Climate Change (IPCC), 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 degrees Celsius. That range is more precise than — but in line with — the IPCC’s prediction that temperatures would rise by 1.5 to 4.5 degrees Celsius 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 said. “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,” he concluded.

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3 Responses

  1. Regardless of the other issues surrounding climate change (e.g., the actual impact of a 1-2% rise in average global temperature over the next 50-100 years, etc.), this article attempts to address the cause for average increases over the last 100-200 years. Unfortunately, there is no possible way that it can make an honest claim to be 99.99% confident in its analysis. The authors basically did a statistical analysis of temperature data over the last 500+, applying the null hypothesis to determine whether man was or was not the contributing factor. Even assuming that their statistics were flawless, he authors start with one massive problem that completely undermines their final conclusion. (And given that they don’t discuss that, it leaves suspect even more of their work.) The massive problem is that they cannot determine with certainty what the actual temperatures were at any time over the last 500 years, prior to modern temperature recording techniques. Since climate scientists generally estimate that there has been about a 0.8 degree (C) rise in temperature since 1880, that means that the input data (average yearly temperatures since 1500) for the current authors’ statistical analysis has to be accurate to a much higher degree of precision than 0.8 degrees. Even if scientists truly believed that they could estimate the average annual temperature of a given year 500 years ago to that degree of accuracy (which no self-respecting scientist would) that would be nothing more than a belief based on no accurate empirical proof. As such, the input data itself has to impart some variation in the statistical degree of confidence (and it’s pretty obvious that it would have to be a large variation). The authors’ results probably showed a 99.9% degree of statistical confidence in their rejection of the null hypothesis (that man is not the cause), GIVEN a 100% confidence level in their input data. But since there is no possible way that they can be 100% confident in their input data, their final conclusion cannot be valid. So their statements that their study shows with 99.9% confidence that man has been the contributing factor in global warming is deceitful. And note that I make no statements here as to my belief about causes, affects, and degree of climate change in the past , present, and future. However, I do take exception to so-called scientists who distort the results of their research to deceive the general public. (And this includes any media source that blindly repeats these claims, if they know better.)

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