Rather than relying on models of climate change that could be the basis for extensive and costly regulations, policymakers should instead question these models, focusing on the legitimacy of their underlying assumptions.
That’s what the Heritage Foundation’s chief statistician said at a recent climate change conference in Las Vegas leading up to the international summit in Glasgow, Scotland, which ends today.
As the Biden administration continues to pursue regulatory policies based on a concept known as the âsocial cost of carbon,â increasing carbon dioxide emissions have led to a âgreening of the planet,â Kevin Dayaratna , senior statistician and data scientist for The Heritage Foundation, said in his presentation to the 14th Heartland Institutee International Conference on Climate Change.
The Illinois-based nonprofit free market think tank attracted dozens of scientists, economists and academics from around the world to the conference, which took place Oct. 15-17.
The Heartland Institute also hosted a Climate Reality Forum in Glasgow on November 2-3 during the two-week United Nations Climate Change Conference.
The Heartland Institute is a co-sponsor of the International Non-Governmental Panel on Climate Change, which has brought together scientists, researchers and academics from around the world who challenge the UN findings indicating catastrophic climate change. Dayaratna is among the researchers who have advised policymakers to refrain from adopting anti-carbon measures in the name of preventing climate change.
âRegardless of predictions of the extent of human influence on climate change, solutions commonly offered by lawmakers here, such as carbon taxes and ‘cap and trade’, will have no impact anyway. significant impact on climate change, as we have demonstrated in previous Heritage Foundation research, âDayaratna told The Daily Signal, the outlet for the Heritage Foundation.
Questionable assumptions on the social cost of Carbon
The social cost of carbon is broadly defined as “the economic damage per metric ton of carbon dioxide emissions,” according to Dayaratna’s slide presentation at the Heartland Conference.
The Obama administration used three statistical models to measure the long-term economic impact of carbon dioxide emissions over a particular time horizon, Dayaratna explained. These are the DICE model, the FUND model and the PAGE model.
The Biden administration recently revived 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 in current modeling practices, Dayaratna said. That’s because the assumptions built into climate models overestimate recent warming trends while failing to account for the positive attributes of carbon dioxide, the data analyst told his audience.
âThe benefits of CO2 can outweigh the damage,â Dayaratna said.
âIn fact, when more realistic assumptions about the climate’s sensitivity to carbon dioxide emissions are incorporated into climate models, a lot of damage disappears from the forecast,â he added.
âIs 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 “Greening the Earth” which occurred from 1982 to 2009. The Heritage Foundation statistician also cited a newspaper article in The Guardian from 2004 which described how Pentagon officials told then-President George W. Bush that climate change over the next 20 years could “bring the planet to the brink of anarchy” and that “nuclear conflicts, mega-droughts, famine and widespread riots will break out across the world â.
The fact that these disaster predictions did not materialize demonstrates that there is still a lot to learn about climate change and that climate models such as those used to calculate the social cost of carbon are “very sensitive to assumptions” that may not be accurate, Dayaratna warned. .
âEstablished science is an oxymoron,â he said. “Science is never settled.”
Underestimating the benefits of carbon dioxide
Dayaratna is the co-author of a peer-reviewed research article that explores âthe implications of recent empirical findings on CO2 fertilization and climate sensitivity on the social cost of carbon in the FUND modelâ.
He and his colleagues chose the FUND model because, unlike other models, the FUND model takes into account the possibility of agricultural advantages.
Nonetheless, they conclude that even the FUND model underestimates the benefits of carbon dioxide.
There is “overwhelming evidence that increases in CO2 have a beneficial effect on plant growth, so models that ignore these benefits overestimate the [social cost of carbon]Says the research article. “Recent literature on global greening and the response of agricultural crops to increased CO2 availability suggests that the increase in productivity is probably greater than that set in FUND.”
After making âreasonableâ adjustments to âagricultural productivity specificationsâ in combination with âmoderate warmingâ forecasts that can be plugged into climate models, Dayaratna finds that there are âsocial benefitsâ to this. he describes it as the âwarmingâ that the planet has experienced. .
“There has indeed been man-made global warming, but the extent to which humans have contributed to it over the past century has been vastly overestimated,” Dayaratna told the Daily Signal in an interview.
To use a term coined by Pat Michaels of the Competitive Enterprise Institute, I like to call it âlukewarmâ. Climate models also dramatically overestimate the amount of warming likely to occur in the future. Human CO2 emissions are indeed responsible for some warming, but they are largely the result of natural influences and this “warming” that we have experienced, which is fairly mild, has benefits that are overlooked.
Carbon dioxide is a natural, colorless, odorless and non-toxic gas. It is a key part of photosynthesis and therefore has agricultural advantages, and to consider it only as a pollutant with only deleterious effects is a mistake.
Dayaratna offered some advice to policymakers and the public at the end of his October 16 presentation.
âThe models are very sensitive to assumptions, and the Biden administration uses those same models,â he said. “We need to think seriously about the administration’s estimates and the assumptions that led to their production.”
Otherwise, Dayaratna warned, predictions as inaccurate as those provided to Bush in 2004 could lead the public to accept expensive regulatory policies that do not match scientific observations.
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