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https://blogs.scientificamerican.com/observations/scientists-have-been-underestimating-the-pace-of-climate-change/
Scientists Have Been Underestimating the Pace of Climate Change

A book entitled *Discerning Experts* explains why—and what can be done
about it
By Naomi Oreskes <https://www.scientificamerican.com/author/naomi-oreskes/>,
Michael Oppenheimer
<https://www.scientificamerican.com/author/michael-oppenheimer/>, Dale
Jamieson <https://www.scientificamerican.com/author/dale-jamieson/> on
August 19, 2019
[image: Scientists Have Been Underestimating the Pace of Climate Change]
Credit: Getty Images
<https://www.gettyimages.com/detail/news-photo/lans-ice-stands-atop-a-ridge-as-seen-from-nasas-operation-news-photo/870892796?adppopup=true>

Recently, the U.K. Met Office announced a revision to the Hadley Center
historical analysis of sea surface temperatures (SST), suggesting that the
oceans have warmed about 0.1 degree Celsius more than previously thought.
The need for revision arises from the long-recognized problem that in the
past sea surface temperatures were measured using a variety of error-prone
methods such as using open buckets, lamb’s wool–wrapped thermometers, and
canvas bags. It was not until the 1990s that oceanographers developed a
network of consistent and reliable measurement buoys.

Then, to develop a consistent picture of long-term trends, techniques had
to be developed to compensate for the errors in the older measurements and
reconcile them with the newer ones. The Hadley Centre has led this effort,
and the new data set—dubbed HadSST4—is a welcome advance in our
understanding of global climate change
<https://www.metoffice.gov.uk/hadobs/hadsst4/>.

But that’s where the good news ends. Because the oceans cover three fifths
of the globe, this correction implies that previous estimates of overall
global warming have been too low. Moreover it was reported recently that in
the one place where it was carefully measured, the underwater melting that
is driving disintegration of ice sheets and glaciers is occurring far
faster than predicted by theory—as much as two orders of magnitude
faster—throwing current model projections of sea level rise further in
doubt.

These recent updates, suggesting that climate change and its impacts are
emerging faster than scientists previously thought, are consistent with
observations that we and other colleagues have made identifying a pattern
in assessments of climate research of underestimation of certain key
climate indicators, and therefore underestimation of the threat of climate
disruption. When new observations of the climate system have provided more
or better data, or permitted us to reevaluate old ones, the findings for
ice extent, sea level rise and ocean temperature have generally been worse
than earlier prevailing views.

Consistent underestimation is a form of bias—in the literal meaning of a
systematic tendency to lean in one direction or another—which raises the
question: what is causing this bias in scientific analyses of the climate
system?

The question is significant for two reasons. First, climate skeptics and
deniers have often accused scientists of exaggerating the threat of climate
change, but the evidence shows that not only have they not exaggerated,
they have underestimated. This is important for the interpretation of the
scientific evidence, for the defense of the integrity of climate science,
and for public comprehension of the urgency of the climate issue. Second,
objectivity is an essential ideal in scientific work, so if we have
evidence that findings are biased in any direction—towards alarmism or
complacency—this should concern us We should seek to identify the sources
of that bias and correct them if we can.

In our new book, *Discerning Experts*
<https://www.press.uchicago.edu/ucp/books/book/chicago/D/bo33765378.html>,
we explored the workings of scientific assessments for policy, with
particular attention to their internal dynamics, as we attempted to
illuminate how the scientists working in assessments make the judgments
they do. Among other things, we wanted to know how scientists respond to
the pressures—sometimes subtle, sometimes overt—that arise when they know
that their conclusions will be disseminated beyond the research
community—in short, when they know that the world is watching. The view
that scientific evidence should guide public policy presumes that the
evidence is of high quality, and that scientists’ interpretations of it are
broadly correct. But, until now, those assumptions have rarely been closely
examined.

We found little reason to doubt the results of scientific assessments,
overall. We found no evidence of fraud, malfeasance or deliberate deception
or manipulation. Nor did we find any reason to doubt that scientific
assessments accurately reflect the views of their expert communities. But
we did find that scientists tend to underestimate the severity of threats
and the rapidity with which they might unfold.

Among the factors that appear to contribute to underestimation is the
perceived need for consensus, or what we label *univocality*: the felt need
to speak in a single voice. Many scientists worry that if disagreement is
publicly aired, government officials will conflate differences of opinion
with ignorance and use this as justification for inaction. Others worry
that even if policy makers want to act, they will find it difficult to do
so if scientists fail to send an unambiguous message. Therefore, they will
actively seek to find their common ground and focus on areas of agreement;
in some cases, they will only put forward conclusions on which they can all
agree.

How does this lead to underestimation? Consider a case in which most
scientists think that the correct answer to a question is in the range
1–10, but some believe that it could be as high as 100. In such a case,
everyone will agree that it is at least 1–10, but not everyone will agree
that it could be as high as 100. Therefore, the area of agreement is 1–10,
and this is reported as the consensus view. Wherever there is a range of
possible outcomes that includes a long, high-end tail of probability, the
area of overlap will necessarily lie at or near the low end. Error bars can
be (and generally are) used to express the range of possible outcomes, but
it may be difficult to achieve consensus on the high end of the error
estimate.

The push toward agreement may also be driven by a mental model that sees
facts as matters about which all reasonable people should be able to agree
versus differences of opinion or judgment that are potentially
irresolvable. If the conclusions of an assessment report are not univocal,
then (it may be thought that) they will be viewed as opinions rather than
facts and dismissed not only by hostile critics but even by friendly
forces. The drive toward consensus may therefore be an attempt to present
the findings of the assessment as matters of fact rather than judgment.
<https://www.scientificamerican.com/page/newsletter-sign-up/?origincode=2018_sciam_ArticlePromo_NewsletterSignUp>

The impulse toward univocality arose strongly in a debate over how to
characterize the risk of disintegration of the West Antarctic Ice Sheet
(WAIS) in the Fourth Assessment Report of the IPCC (AR4). Nearly all
experts agreed there was such a risk as climate warmed, but some thought it
was only very far in the future while others thought it might be more
imminent. An additional complication was that some scientists felt that the
available data were simply not sufficient to draw any defensible conclusion
about the short-term risk, and so they made no estimate at all.

However, everyone concurred that, if WAIS did not disintegrate soon, it
would likely disintegrate in the long run. Therefore, the area of agreement
lay in the domain of the long run—the conclusion of a non-imminent risk—and
so that is what was reported. The result was a minimalist conclusion, and
we know now that the estimates that were offered were almost certainly too
low.

This offers a significant point of contrast with academic science, where
there is no particular pressure to achieve agreement by any particular
deadline (except perhaps within a lab group, in order to be able to publish
findings or meet a grant proposal deadline). Moreover, in academic life
scientists garner attention and sometimes prestige by disagreeing with
their colleagues, particularly if the latter are prominent. The reward
structure of academic life leans toward criticism and dissent; the demands
of assessment push toward agreement.

A second reason for underestimation involves an asymmetry in how scientists
think about error and its effects on their reputations. Many scientists
worry that if they over-estimate a threat, they will lose credibility,
whereas if they under-estimate it, it will have little (if any)
reputational impact. In climate science, this anxiety is reinforced by the
drumbeat of climate denial, in which scientists are accused of being
“alarmists” who “exaggerate the threat.” In this context, scientists may go
the extra mile to disprove the stereotype by down-playing known risks and
denying critics the opportunity to label them as alarmists.

Many scientists consider underestimates to be “conservative,” because they
are conservative with respect to the question of when to sound an alarm or
how loudly to sound it. The logic of this can be questioned, because
underestimation is not conservative when viewed in terms of giving people
adequate time to prepare. (Consider for example, an underestimate of an
imminent hurricane, tornado, or earthquake.) In the AR4 WAIS debate,
scientists underestimated the threat of rapid ice sheet disintegration
because many of the scientists who participated were more comfortable with
an estimate that they viewed as "conservative" than with one that was not.

The combination of these three factors—the push for univocality, the belief
that conservatism is socially and politically protective, and the
reluctance to make estimates at all when the available data are
contradictory—can lead to “least common denominator'' results—minimalist
conclusions that are weak or incomplete.

Moreover, if consensus is viewed as a requirement, scientists may avoid
discussing tricky issues that engender controversy (but might still be
important), or exclude certain experts whose opinions are known to be
“controversial” (but may nevertheless have pertinent expertise). They may
also consciously or unconsciously pull back from reporting on extreme
outcomes. (Elsewhere we have labeled this tendency "erring on the side of
least drama.”) In short, the push for agreement and caution may undermine
other important goals, including inclusivity, accuracy and comprehension.

We are not suggesting that every example of underestimation is necessarily
caused by the factors we observed in our work, nor that the demand for
consensus always leads to conservatism. Without looking closely at any
given case, we cannot be sure whether the effects we observed are operating
or not. But we found that the pattern of underestimation that we observed
in the WAIS debate also occurred in assessments of acid rain and the ozone
hole.

We found that the institutional aspects of assessment, including who the
authors are and how they are chosen, how the substance is divided into
chapters, and guidance emphasizing consensus, also mitigate in favor of
scientific conservatism. Thus, so far as our evidence goes, it appears that
scientists working in assessments are more likely to underestimate than to
overestimate threats.

In our book, we make some concrete recommendations. While scientists in
assessments generally aim for consensus, we suggest that they should not
view consensus as a goal of the assessment. Depending on the state of
scientific knowledge, consensus may or may not emerge from an assessment,
but it should not be viewed as something that needs to be achieved and
certainly not as something to be enforced. Where there are substantive
differences of opinion, they should be acknowledged and the reasons for
them explained (to the extent that they can be explained). Scientific
communities should also be open to experimenting with alternative models
for making and expressing group judgments, and to learning more about how
policy makers actually interpret the findings that result.

The views expressed are those of the author(s) and are not necessarily
those of Scientific American.
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ABOUT THE AUTHOR(S)
Naomi Oreskes

Naomi Oreskes is a professor of the history of science and an affiliated
professor of earth and planetary sciences at Harvard University. She is
co-author, with Erik M. Conway, of *Merchants of Doubt: How a Handful of
Scientists Obscured the Truth on Issues from Tobacco to Global Warming*
(Bloomsbury Press, 2010). She also wrote the introduction to the Melville
House Press 2015 edition of the papal *Encyclical on Climate Change and
Inequality*.

Credit: Nick Higgins
Michael Oppenheimer

Michael Oppenheimer is the Albert G. Milbank Professor of Geosciences and
International Affairs and the Director, Center for Policy Research on
Energy and the Environment at Princeton University.
Dale Jamieson

Dale Jamieson is Professor of Environmental Studies and Philosophy,
Affiliated Professor of Law, and Director of the Center for Environmental
and Animal Protection at New York University.