The Corner

Re: The Real Epistemic Closure

Kathryn / Andy / Mr. Levin,

I accept that it is fair to characterize my tone in the “Epistemic Closure” post as scathing. I apologize (sincerely) if this was offensive to you. All I can say about it is that I was calling a spade a spade as I saw it.

Mr. Levin,

Thank you for the reply. I’m happy to give you the last word, and simply invite readers to review both posts and draw whatever conclusions they feel are appropriate.


I read the Richard Lindzen Wall Street Journal op-ed that you reference. While I might not have chosen the same words as Professor Lindzen in places, there is very little of scientific substance in that piece with which I disagree. In fact, I’ve made some version of most of the relevant points, often in almost identical language, and often right here at NR and NRO.

I’ll start by repeating my characterization of Lindzen’s views on anthropogenic global warming (AGW) from the post, and compare this to what Lindzen said in a prior WSJ op-ed.

In my post I said:

Richard Lindzen, a very serious climate scientist who disputes the estimated magnitude of the greenhouse effect, but not its existence…

In the Wall Street Journal, in 2006, Lindzen wrote:

[T]here has been no question whatever that carbon dioxide is an infrared absorber (i.e., a greenhouse gas — albeit a minor one), and its increase should theoretically contribute to warming. Indeed, if all else were kept equal, the increase in carbon dioxide should have led to somewhat more warming than has been observed, assuming that the small observed increase was in fact due to increasing carbon dioxide rather than a natural fluctuation in the climate system.

Lindzen has argued for some time that the expected impact of CO2 on temperature – this is a rough definition of “climate sensitivity” – is lower than do most climate scientists, and that therefore we should not be alarmed, but he clearly acknowledges that CO2 is a greenhouse gas. This is important to keep in mind as we proceed through the current op-ed and discussion. Let me take it one piece at a time.

The first several paragraphs of his current op-ed make the point that the so-called science underlying much of the historical temperature record, and the use of historical data to establish a causal relationship between CO2 and temperature, is unreliable, and should not be the basis for establishing policy. 

Or, as I put it in 2009:


I argued over two years ago that: 1) Long-term climate reconstruction was one of the two key trouble spots in climate science; 2) mathematically sophisticated critics had debunked the methodology used to reconstruct long-term climate evidence that is the basis for the famous “hockey stick” increase in global temperatures; and 3) excellent evidence had been presented to the U.S. Senate that, in climate reconstruction, academic peer review meant, in effect, agreement among a tiny, self-selected group of experts. The root problem here is not the eternal perfidy of human nature, but the fact that we can’t run experiments on history to adjudicate disputes, which makes this less like chemistry or physics than like economics or political science.

Today’s Lindzen op-ed proceeds to consider the science around projections of warming impacts. I’ll compare the key points in it to what I’ve written.

First, Lindzen:

The IPCC’s position in its Summary for Policymakers from their Fourth Assessment (2007) is weaker, and is essentially simply that most warming of the past 50 years or so is due to man’s emissions. It is sometimes claimed that the IPCC is 90% confident of this claim, but there is no known statistical basis for this claim; it is purely subjective.

Compare, Manzi (2007):

The current summary indicates that the IPCC is “90% confident” that we have caused global warming. The summary further implies that if we double the concentration of carbon dioxide (CO2) in the atmosphere, the IPCC is 90 percent confident that we will cause further warming of 3° C +/- 1.5° C.

But what do these statements of confidence really mean? They are not derived mathematically from the type of normal probability distributions that are used when, for example, determining the margin of error in a political poll (say,+ /- 5%). IPCC estimates of “confidence” are really what we would mean by this word in everyday conversation—a subjective statement of opinion. This is a very big deal, since bounding the uncertainty in climate predictions is central to deciding what, if anything, we should do about them.

Second, Lindzen:

There are, however, some things left unmentioned about the IPCC claims. For example, the observations are consistent with models only if emissions include arbitrary amounts of reflecting aerosols particles (arising, for example, from industrial sulfates) which are used to cancel much of the warming predicted by the models. The observations themselves, without such adjustments, are consistent with there being sufficiently little warming as to not constitute a problem worth worrying very much about.…


But Messrs. Cicerone and Rees … throw in a very peculiar statement (referring to warming), almost in passing: “Uncertainties in the future rate of this rise, stemming largely from the ‘feedback’ effects on water vapour and clouds, are topics of current research.”


Who would guess from this statement, that the feedback effects are the crucial question? Without these positive feedbacks assumed by computer modelers, there would be no significant problem, and the various catastrophes that depend on numerous factors would no longer be related to anthropogenic global warming. That is to say, the issue relevant to policy is far from settled.


Compare, Manzi (2007):

The most important scientific debate is really about these feedback effects. Feedbacks are not merely details to be cleaned up in a picture that is fairly clear. The base impact of a doubling of CO2 in the atmosphere with no feedback effects is on the order of 1°C, while the United Nations Intergovernmental Panel on Climate Change (IPCC) consensus estimate of the impact of doubling CO2 is about 3°C. The feedback effects dominate the prediction. As we’ve seen, however, feedback effects run in both directions. Feedback could easily dampen the net impact so it ends up being less than 1°C. In fact, the raw relationship between temperature increases and CO2 over the past century supports that idea.


Over the past several decades, teams in multiple countries have launched ongoing projects to develop large computer models that simulate the behavior of the global climate in order to account for feedback effects. While these models are complex, they are still extremely simplistic as compared with the actual phenomenon of global climate. Models have successfully replicated historical climates, but no model has ever demonstrated that it can accurately predict the climate impact of CO2 emissions over a period of many years or decades.

Climate models generate useful projections for us to consider, but the reality is that nobody knows with meaningful precision how much warming we will experience under any emissions scenario. Global warming is a real risk, but its impact over the next century could plausibly range from negligible to severe.

Third, Lindzen:

[T]he proposed policies are likely to cause severe problems for the world economy.

Compare, Manzi (2007):

In summary, then, the best available models indicate that 1) global warming is a problem that will have only a marginal impact on the world economy, and 2) it is economically rational only to reduce slightly this marginal impact through global carbon taxes. Further, practical knowledge of the world indicates that 1) such a global carbon-tax regime would be very unlikely ever to be implemented, and 2) even if it were implemented, the theoretical benefits it might create would probably be more than offset by the economic drag it would produce.

Why, if I am in such close agreement, am I not just going along with the “don’t worry about AGW” line? Because of uncertainty. The problem of the lack of confidence highlighted in the first Lindzen quote from the current op-ed (restated in concept as lack of model certainty in the second quote) is crucial. It is the basis of the sophisticated argument for emissions mitigation.

Lindzen is one expert scientist who forecasts very small net warming as a result of emissions. Most relevant scientists predict quantitatively larger effects. Put yourself in the position of a senior government leader tasked with making real decisions that affect the lives of millions. What would you do if faced with a matter of technical disagreement on such a quantitative-prediction question among experts? The sensible thing to do is to gather together a group of the leading subject-matter experts to produce a review of known science, and subject it to review by a standing body of leading scientists who are not directly in the field in order to minimize both groupthink and opportunities for self-dealing. In America, this in effect describes the U.S. National Research Council (NRC). 

In 1979, prior to any accusations of politicization of which I am aware, the NRC convened exactly such a process, and estimated that climate sensitivity is about 3C. This estimate has been consistently affirmed by each of the U.N. IPCC Assessment Reports over the past 20 years. It turns out (as I explore in detail in a Corner post from last week rebutting Paul Krugman) that the amount of warming that would be implied by this climate sensitivity doesn’t justify the costs of cap-and-trade, carbon taxes, or other emissions-mitigation schemes.

However, it is also the case – for the basic reasons that both Lindzen and I reference – that there is substantial uncertainty about this and other related estimates. Thus, the legitimate risk from climate change is that our current best forecast is wrong; more specifically that climate change will be worse than current forecasts. In a post from earlier this week at the Corner, I go into excruciating detail about why the argument from uncertainty, however, is unpersuasive in supporting aggressive mitigation programs.

Jim Manzi is CEO of Applied Predictive Technologies (APT), an applied artificial intelligence software company.


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