A Call for Integrity in Climate Science
Notes on Steven Koonin’s Unsettled: What Climate Science Tells Us, What It Doesn’t, and Why It Matters
The following is my informal book review of Unsettled: What Climate Science Tells Us, What It Doesn’t, and Why It Matters, by Steven E. Koonin (Dallas: BenBella Books, 2021).
Steven Koonin is a former Undersecretary for Science under the Obama administration’s Department of Energy. He began his career as a theoretical physicist at Caltech, teaching and researching in the fields of physics, astrophysics, and scientific computation. After working as chief scientist at BP (focusing on renewable energy) he joined the Department of Energy, eager to make progress on reducing carbon dioxide emissions in order to “save the planet.” In 2013 Koonin was asked by the American Physical Society to coordinate an update to its public statement on climate. This led to his organizing a workshop in order to “stress test” the state of climate science:
Six leading climate experts and six leading physicists, myself included, spent a day scrutinizing exactly what we know about the climate system and how confidently we can project its future. To focus the conversation, we physicists had spent the prior two months preparing a framing document based on the UN assessment report that had just been released. We posed some specific and crucial questions along the lines of: Where is the data poor or the assumptions weakly supported—and does that matter? How reliable are the models that we use to describe the past and project the future?1
The findings of this workshop shocked Koonin and led to him becoming far more skeptical of many climate claims. They also caused him to question the scientific integrity of the process by which climate studies are summarized and then presented to the public. Koonin ultimately concluded that:
Humans exert a growing, but physically small, warming influence on the climate. The deficiencies of climate data challenge our ability to untangle the response to human influences from poorly understood natural changes.
The results from the multitude of climate models disagree with, or even contradict, each other and many kinds of observations. A vague “expert judgment” was sometimes applied to adjust model results and obfuscate shortcomings.
Government and UN press releases and summaries do not accurately reflect the reports themselves. There was a consensus at the meeting on some important issues, but not at all the strong consensus the media promulgates…
In short, the science is insufficient to make useful projections about how the climate will change over the coming decades, much less what effect our actions will have on it.2
Koonin wrote Unsettled in order to expand upon and explain these conclusions. The first three chapters present an introductory overview of the nature of global warming and human-caused greenhouse gases. These are followed by chapters on the nature of climate models and on the alleged climate emergencies continually trumpeted in the media, regarding issues such as heat increases, hurricanes, and sea level rise.
Two aspects of the book struck me as particularly interesting: the discussion of climate models and the ways in which assessment reports can misrepresent the science that they are meant to objectively summarize.
Problems with Climate Models
Kooning explains how, due to the sheer complexity of the earth’s climate, it is extremely difficult to create good climate models. Models are based on grids covering the earth’s surface, which divide the atmosphere into pizza-box-shaped volumes, each of which get assigned specific physical values such as temperature, pressure, etc. On the surface of the earth, these grid lines are typically about 60 miles apart. But many important phenomena occur at smaller scales, so modelers must make “subgrid” assumptions about climate activity within the grid boxes, involving phenomena such as the height and coverage of clouds. While based on fundamental physical laws and observations of weather phenomena, these assumptions also involve considerable individual judgment and are more of an art than a science, leading to widely different results between models. These subgrid phenomena can influence temperature values as much as human activity.
Given a set of subgrid assumptions, the model needs to be “tuned,” which involves the difficult task of setting specific parameter values for these phenomena. After discussing the judgment calls required to tune the parameters and the effects on the model results, Koonin concludes:
it is impossible—for both practical and fundamental reasons—to tune the dozens of parameters so that the model matches the far more numerous observed properties of the climate system. Not only does this cast doubt on whether the conclusions of the model can be trusted, it makes it clear that we don’t understand features of the climate to anywhere near the level of specificity required given the smallness of human influences.3
Koonin quotes from a paper by fifteen leading climate modelers:
Choices and compromises made during the tuning exercise may significantly affect model results . . . In theory, tuning should be taken into account in any evaluation, intercomparison, or interpretation of the model results . . . Why such a lack of transparency? This may be because tuning is often seen as an unavoidable but dirty part of climate modeling, more engineering than science, an act of tinkering that does not merit recording in the scientific literature. There may also be some concern that explaining that models are tuned may strengthen the arguments of those claiming to question the validity of climate change projections. Tuning may be seen indeed as an unspeakable way to compensate for model errors.4
Koonin then gives an example of the extent of this tuning:
A paper laying out the details of one of the most esteemed models, that of Germany’s Max Planck Institute, tells of tuning a subgrid parameter (related to convection in the atmosphere) by a factor of ten because the originally chosen value resulted in twice as much warming as had been observed. Changing a subgrid parameter by a factor of ten from what you thought it was—that’s really dialing the knob.5
Given that dozens of research teams around the globe create and maintain their own models, a centralized Coupled Model Intercomparison Project (CMIP) compiles “ensembles” of these models, releasing an updated ensemble (such as CMIP3) every few years. Assessment reports then refer to averages of these ensembles. This averaging implies that the models generally agree, but this is definitely not the case at the scales required to identify specific changes due to human influences. At these scales, the models differ quite a bit from each other and from observations.
One particularly concerning type of difference is absolute temperature:
the simulated global average surface temperature (not the anomaly) varies among models by about 3ºC (5.6ºF), three times greater than the observed value of the twentieth-century warming they’re purporting to describe and explain.6
The assessment reports cover up this type of discrepancy by focusing on the temperature changes within each model (the “temperature anomaly”), which are typically the values shown in the report graphs.
Another significant problem with the models is their inability to explain the degree of warming between 1910 and 1940, when greenhouse gas concentrations were very low. On average, their warming rate over this period is about half the observed rate. According to Koonin, this is a major problem, because “the observed early twentieth-century warming is comparable to the observed late twentieth-century warming, which the assessment reports attribute with “high confidence” to human influences.7
Non-Objective Assessment Reports
Thoughout the book, Koonin gives examples of how assessment reports and official statements misrepresent the relevant science, often by omitting crucial information. One example is a 2019 a statement issued by the presidents of the National Academies of Science, Engineering, and Medicine. This statement, affirming “the Scientific Evidence of Climate Change,” included only the following paragraph on the science itself:
Scientists have known for some time, from multiple lines of evidence, that humans are changing Earth’s climate, primarily through greenhouse gas emissions. The evidence on the impacts of climate change is also clear and growing. The atmosphere and the Earth’s oceans are warming, the magnitude and frequency of certain extreme events are increasing, and sea level is rising along our coasts.8
Koonin remarks:
Even given the need for brevity, this is a misleadingly incomplete and imprecise accounting of the state of climate science. It conflates human-caused warming with the changing climate in general, erroneously implying that human influences are solely responsible for these changes. It invokes “certain extreme events” while omitting the fact that most types (including those that pop most readily to mind when one reads the phrase “extreme events,” like hurricanes) show no significant trend at all. And it states that “sea level is rising” in a way that not only suggests that this, too, is solely attributable to human-caused warming, but elides the fact that the rise is nothing new.9
Given these problems with the way that climate science is summarized and communicated, what can be done about this? Koonin argues for the use of “Red Teams,” which are often used for double-checking high-consequence reports such as those on complex engineering projects such as aircraft or spacecraft. These could be easily applied to climate assessment reports:
a group of scientists (the “Red Team”) would be charged with rigorously questioning one of the assessment reports, trying to identify and evaluate its weak spots. In essence, a qualified adversarial group would be asked “What’s wrong with this argument?” And, of course, the “Blue Team” (presumably the report’s authors) would have the opportunity to rebut the Red Team’s findings.10
The usual response to this proposal is that assessment reports are already peer-reviewed. But Koonin points out that the rigorous type of peer review done on scientific journal articles is very different than the process applied to assessment reports.
an assessment report is not a research article—in fact, it’s a very different sort of document with a very different purpose. Journal papers are focused presentations written by experts for experts. In contrast, assessment authors must judge the validity and importance of many diverse research papers, and then synthesize them into a set of high-level statements meant to inform non-experts. So an assessment report’s “story” really matters, as does the language used to tell it—especially for something as important as climate.
The processes for drafting and reviewing the climate science assessment reports do not promote objectivity. Government officials from scientific and environmental agencies (who might themselves have a point of view) nominate or choose the authors, who are not subject to conflict of interest constraints. That is, an author might work for a fossil fuel company or for an NGO promoting “climate action.” This increases the chances of persuasion being favored over information.
A large group of volunteer expert reviewers… reviews the draft. But unlike the peer review of research papers, disagreements among reviewers and lead authors are not resolved by an independent referee; the lead author can choose to reject a criticism simply by saying “We disagree.”11
For non-specialists, it can seem impossible to objectively evaluate many climate claims, so Koonin also provides a helpful list of “red flags” which they can use to check if skepticism is warranted for a climate science report. These include such things as referring to a scientist as a “denier” or “alarmist,” appealing to the “97 percent consensus,” and quoting alarming quantities without context.
In the final three chapters Koonin describes various actions proposed to reduce the concentration of carbon dioxide in the atmosphere, or to otherwise deal with climate changes, manmade or natural. One chapter assumes for the sake of argument that the US must soon get to “zero greenhouse gas emissions,” and it becomes obvious how impossibly difficult this would be. Moreover, as Koonin points out, the US is the source of only about 13 percent of global greenhouse gases.
For an essential supplement to these final chapters, I recommend Alex Epstein’s book Fossil Future, which carefully examines the way we treat experts in general, the way we think about the benefits and negative side-effects of energy technologies, and the implications for government policy.12
As I read Unsettled, I often would have liked more annotations on the graphs. Unfortunately, some were too small and poorly labelled to be read clearly. But overall, Koonin has provided an excellent overview of a very controversial topic, and a well-written call for scientific integrity for a field in urgent need of it.
I invite you to tell me your favorite book on climate science in the comments — especially if you disagree with the theme of Koonin’s book.
Steven E. Koonin, Unsettled: What Climate Science Tells Us, What It Doesn’t, and Why It Matters (Dallas: BenBella Books, 2021), p. 3
Ibid., p. 4
Ibid., pp. 84-85
Ibid., pp. 85-86
Ibid., p. 86
Ibid., p. 87
Ibid., p. 89
Ibid., p. 190
Ibid., pp. 190-191
Ibid., pp. 197-198
Ibid., p. 199
Alex Epstein, Fossil Future: Why Global Human Flourishing Requires more Oil, Coal, and Natural Gas—Not Less (New York: Penguin, 2022)
Nice review: clear, well-written, and focused. I look forward to more on this subject.