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Study:
Contrarian Climate Studies Contain Notable Scientific Errors

A new study published in the journal Theoretical and Applied Climatology examines contrarian climate science — the 3 percent of studies questioning the existence and human causes of climate change — and finds they include critical mistakes in selection and interpretation of data.The authors tried to replicate the results of 38 examples of contrarian climate research, selected for their high visibility and their arrival at different conclusions than consensus climate studies.

By Brynn McNally | Published 9 years ago | About a 3 minute read

A new study published in the journal Theoretical and Applied Climatology examines contrarian climate science — the 3 percent of studies questioning the existence and human causes of climate change — and finds they include critical mistakes in selection and interpretation of data.

The authors tried to replicate the results of 38 examples of contrarian climate research, selected for their high visibility and their arrival at different conclusions than consensus climate studies.

“Our hypothesis was that the chosen contrarian paper was valid, and our approach was to try to falsify this hypothesis by repeating the work with a critical eye,” co-author Rasmus Benestad wrote in a blog post for Real Climate.

The authors said the most common mistake shared by the studies was cherry-picking data, or ignoring important contextual information that did not support the conclusion. For example, one study found evidence that the moon and solar cycles affect the Earth’s climate. However, when the group tried to replicate those results, they found the study’s model to work only for the particular 4,000-year cycle that the study examined.

“However, for the 6,000 years’ worth of earlier data they threw out, their model couldn’t reproduce the temperature changes,” co-author Dana Nuccitelli wrote in The Guardian. “The authors argued that their model could be used to forecast future climate changes, but there’s no reason to trust a model forecast if it can’t accurately reproduce the past.”

Other studies overlooked well-established principles in physics to make a model fit their conclusion.

“Good modeling will constrain the possible values of the parameters being used so that they reflect known physics, but bad ‘curve fitting’ doesn’t limit itself to physical realities,” Nuccitelli continued.

The paper notes that the errors likely aren’t intentional. They offer several possibilities for the mistakes. For example, many authors of the contrarian studies were new to climate science and potentially ignorant of important contextual information. In addition, many of the papers were published in journals that don’t typically publish climate science, so peer review may have been lacking.

Reproducibility is essential to science, the paper emphasizes — both for consensus studies and contrarian ones.

“Science is never settled, and both the scientific consensus and alternative hypotheses should be subject to ongoing questioning, especially in the presence of new evidence and insights,” it says.

“True and universal answers should, in principle, be replicated independently, especially if they have been published in the peer-reviewed scientific literature.”

This new research helps to put climate change skeptics in perspective. While a recent poll of Americans found over 60 percent are convinced that human actions can cause significant changes to global climate, deniers are a dwindling but vocal group. Understanding the assumptions shaping their views may be key to bridging the divide in the climate conversation.