Rather than relying on climate change models that could be the basis of expansive and costly regulations, policymakers should instead question those models, focusing on the legitimacy of their underlying assumptions.
So said The Heritage Foundation’s chief statistician at a recent climate change conference in Las Vegas that preceded the international summit in Glasgow, Scotland, that concludes today.
While the Biden administration continues to pursue regulatory policies based on a concept known as the “social cost of carbon,” increased carbon dioxide emissions have led to a “greening of the planet,” Kevin Dayaratna, principal statistician and data scientist for The Heritage Foundation, said in his presentation at the Heartland Institute’s 14th International Climate Change Conference.
The nonprofit, Illinois-based free market think tank attracted dozens of scientists, economists, and academics from across the globe to the conference, which ran from Oct. 15 to 17.
The Heartland Institute is a co-sponsor of the Nongovernmental International Panel on Climate Change, which has brought together scientists, researchers, and scholars from across the globe who dispute U.N. findings that point to catastrophic climate change. Dayaratna is among the researchers who have advised policymakers to refrain from enacting anti-carbon measures in the name of averting climate change.
“Regardless of one’s predictions on the extent of human influence on climate change, commonly proffered solutions by lawmakers here, such as carbon taxes and ‘cap and trade,’ will have no meaningful impact on altering the climate anyway, as we’ve demonstrated in prior Heritage Foundation research,” Dayaratna told The Daily Signal, the news outlet of The Heritage Foundation.
Dubious Assumptions on Social Cost of Carbon
The social cost of carbon is typically defined as “the economic damages per metric ton of carbon dioxide emissions,” according to Dayaratna’s slide presentation at the Heartland conference.
There are three statistical models the Obama administration used to measure the long-term economic impact of carbon dioxide emissions over a particular time horizon, Dayaratna explained. They are the DICE model, the FUND model, and the PAGE model.
The Biden administration recently reinstituted Obama-era climate-modeling exercises that attempt to calculate the social cost of carbon. But an “honest cost/benefit analysis” of carbon dioxide emissions is not possible under current modeling practices, Dayaratna said. That’s because the assumptions built into the climate models overstate recent warming trends while failing to account for the positive attributes of carbon dioxide, the data analyst told his audience.
“The benefits of CO2 may outweigh the damages,” Dayaratna said.
“In fact, when more realistic assumptions about how sensitive the climate is to carbon dioxide emissions are plugged into the climate models, many of the damages disappear from the forecasts,” he added.
“Is global warming necessarily a bad thing?” he asked, answering his own question: “CO2 in the atmosphere can increase agricultural productivity.”
One of Dayaratna’s slide presentations included a satellite image of “the Greening of the Earth” that occurred from 1982 to 2009. The Heritage Foundation statistician also cited a newspaper article in The Guardian dating back to 2004 that described how Pentagon officials told then-President George W. Bush that climate change over the following 20 years could “bring the planet to the edge of anarchy” and that “nuclear conflict, mega-droughts, famine, and widespread rioting will erupt across the world.”
The fact that those predictions of catastrophe have not materialized demonstrates that there’s still much to learn about climate change and that climate models such as those used to calculate the social cost of carbon are “highly sensitive to assumptions” that may not be accurate, Dayaratna warned.
“‘Settled science’ is an oxymoron,” he said. “Science is never settled.”
Understating Benefits of Carbon Dioxide
Dayaratna is the co-author of a peer-reviewed research article that explores “the implications of recent empirical findings about CO2 fertilization and climate sensitivity on the social cost of carbon in the FUND model.”
He and his colleagues selected the FUND model because, unlike the other models, the FUND model accounts for the possibility of agricultural benefits.
Nevertheless, they conclude that even the FUND model understates the benefits of carbon dioxide.
There is “overwhelming evidence that CO2 increases do have a beneficial effect on plant growth, so models that fail to take these benefits into account overstate the [social cost of carbon],” the research article says. “The recent literature on global greening and the response of agricultural crops to enhanced CO2 availability suggests that the productivity boost is likely stronger than that parameterized in FUND.”
After making “reasonable” adjustments to “agricultural productivity specifications” in combination with “moderate warming” forecasts that can be plugged into climate models, Dayaratna finds that there are “social benefits” to what he describes as the “lukewarming” the planet has experienced.
“There has indeed been man-made global warming, but the extent to which humans have contributed to it over the last century has been vastly overstated,” Dayaratna told The Daily Signal in an interview.
To use a term coined by Pat Michaels of the Competitive Enterprise Institute, I like to refer to it as ‘lukewarming.’ The climate models also greatly overstate the amount of warming that is likely to occur going forward. Human CO2 emissions are indeed responsible for some warming, but much of it is the result of natural influences and this ‘lukewarming’ we have experienced, which is fairly mild, has benefits that are overlooked.
Carbon dioxide is a naturally occurring, colorless, odorless, nontoxic gas. It is a key element of photosynthesis and thus has agricultural benefits, and to consider it only as a pollutant that solely has deleterious effects is a mistake.
Dayaratna offered some advice for policymakers and the public at the conclusion of his Oct. 16 presentation.
“Models are highly sensitive to assumptions, and the Biden administration is using these same models,” he said. “We need to think seriously about the administration’s estimates, and the assumptions that went into producing them.”
If not, Dayaratna cautioned, predictions as inaccurate as those provided to Bush in 2004 could beguile the public into accepting costly regulatory policies that do not square with scientific observations.
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