For decades, some members of the fossil fuel industry tried to convince the public that a causative link between fossil fuel use and climate warming could not be made because the models used to project warming were too uncertain. Supran et al. show that one of those fossil fuel companies, ExxonMobil, had their own internal models that projected warming trajectories consistent with those forecast by the independent academic and government models. What they understood about climate models thus contradicted what they led the public to believe. —HJS
In 2015, investigative journalists discovered internal company memos indicating that Exxon oil company has known since the late 1970s that its fossil fuel products could lead to global warming with “dramatic environmental effects before the year 2050.” Additional documents then emerged showing that the US oil and gas industry’s largest trade association had likewise known since at least the 1950s, as had the coal industry since at least the 1960s, and electric utilities, Total oil company, and GM and Ford motor companies since at least the 1970s. Scholars and journalists have analyzed the texts contained in these documents, providing qualitative accounts of fossil fuel interests’ knowledge of climate science and its implications. In 2017, for instance, we demonstrated that Exxon’s internal documents, as well as peer-reviewed studies published by Exxon and ExxonMobil Corp scientists, overwhelmingly acknowledged that climate change is real and human-caused. By contrast, the majority of Mobil and ExxonMobil Corp’s public communications promoted doubt on the matter.
Many of the uncovered fossil fuel industry documents include explicit projections of the amount of warming expected to occur over time in response to rising atmospheric greenhouse gas concentrations. Yet, these numerical and graphical data have received little attention. Indeed, no one has systematically reviewed climate modeling projections by any fossil fuel interest. What exactly did oil and gas companies know, and how accurate did their knowledge prove to be? Here, we address these questions by reporting and analyzing all known global warming projections documented by—and in many cases modeled by—Exxon and ExxonMobil Corp scientists between 1977 and 2003.
Our results show that in private and academic circles since the late 1970s and early 1980s, ExxonMobil predicted global warming correctly and skillfully. Using established statistical techniques, we find that 63 to 83% of the climate projections reported by ExxonMobil scientists were accurate in predicting subsequent global warming. ExxonMobil’s average projected warming was 0.20° ± 0.04°C per decade, which is, within uncertainty, the same as that of independent academic and government projections published between 1970 and 2007. The average “skill score” and level of uncertainty of ExxonMobil’s climate models (67 to 75% and ±21%, respectively) were also similar to those of the independent models.
Moreover, we show that ExxonMobil scientists correctly dismissed the possibility of a coming ice age in favor of a “carbon dioxide induced ‘super-interglacial’”; accurately predicted that human-caused global warming would first be detectable in the year 2000 ± 5; and reasonably estimated how much CO2 would lead to dangerous warming.
Today, dozens of cities, counties, and states are suing oil and gas companies for their “longstanding internal scientific knowledge of the causes and consequences of climate change and public deception campaigns.” The European Parliament and the US Congress have held hearings, US President Joe Biden has committed to holding fossil fuel companies accountable, and a grassroots social movement has arisen under the moniker #ExxonKnew. Our findings demonstrate that ExxonMobil didn’t just know “something” about global warming decades ago—they knew as much as academic and government scientists knew. But whereas those scientists worked to communicate what they knew, ExxonMobil worked to deny it—including overemphasizing uncertainties, denigrating climate models, mythologizing global cooling, feigning ignorance about the discernibility of human-caused warming, and staying silent about the possibility of stranded fossil fuel assets in a carbon-constrained world.
Climate projections by the fossil fuel industry have never been assessed. On the basis of company records, we quantitatively evaluated all available global warming projections documented by—and in many cases modeled by—Exxon and ExxonMobil Corp scientists between 1977 and 2003. We find that most of their projections accurately forecast warming that is consistent with subsequent observations. Their projections were also consistent with, and at least as skillful as, those of independent academic and government models. Exxon and ExxonMobil Corp also correctly rejected the prospect of a coming ice age, accurately predicted when human-caused global warming would first be detected, and reasonably estimated the “carbon budget” for holding warming below 2°C. On each of these points, however, the company’s public statements about climate science contradicted its own scientific data.
In this Review, we report and analyze all known projections of global mean surface temperature (hereafter “temperature”) change reported by company scientists working for Exxon and/or for ExxonMobil Corp after Exxon’s merger with Mobil Oil Corp in 1999. (Hereafter, we collectively refer to Exxon and ExxonMobil Corp as “ExxonMobil” or the “company.”) Some projections resulted from models built or run in-house by ExxonMobil scientists, sometimes in collaboration with independent researchers. Others were produced by third parties and then discussed by ExxonMobil scientists in internal reports. Where relevant, we distinguish these provenances, but otherwise we collectively refer to these projections as “reported” by ExxonMobil scientists.
Materials and methods
Using manual content analysis, we identify all documents that reported climate model outputs of (i) a time series of projected future temperature, and (ii) future external radiative forcings [including at least atmospheric carbon dioxide (CO2) concentration] (see SM section S1.1 for coding details). For models driven by more than one forcing time series (i.e., for high- and low-CO2 scenarios as well as a central, “nominal” one), each resulting temperature time series is treated as a separate and individual projection. Our figures and tables therefore distinguish between “nominal,” “high,” and “low” model projections. By contrast, for a given CO2 scenario, temperature time series accompanied by uncertainty bars (corresponding, for example, to different model climate sensitivities) are treated as single projections with uncertainty bounds given by those uncertainty bars. This yields 12 documents published between 1977 and 2003, which contain 16 distinct temperature projections presented in the form of 12 unique graphs and one table (summarized in SM section S2.2). The 12 documents comprise seven internal memos (1977 to 1985) and five peer-reviewed papers (1985 to 2003). Twelve of the 16 temperature projections came from models built or run in-house by ExxonMobil scientists, typically in collaboration with independent researchers. Once identified, all original temperature and forcing projections are converted for analysis by digitizing graphs and extracting tables.
where is the initial CO2 concentration (in parts per million) at the start of the projection period and is the CO2 concentration during each subsequent year through 2019 (16). In the real world, of course, global temperature changes are driven by multiple natural and anthropogenic factors, including but not limited to CO2. Nevertheless, even when model projections are driven by CO2-only anthropogenic forcing scenarios, retrospectively comparing projections to observations offers a robust, independent, and established test of model skill. This is because (i) global warming has been almost entirely human-caused since the late 19th century (32, 33) and (ii) total anthropogenic forcing over the past 150 years has been, to first order, similar to the forcing of CO2 alone, because the warming effects of other greenhouse gases and the cooling effects of other sources cancel one another out (34). For further discussion of the implications and limitations of model-versus-observation comparisons, see SM section S1.2.7. Observed values, meanwhile, were based on a 1000-member ensemble of observationally informed forcing estimates reported by Dessler and Forster (2018) (35).
Evaluated in terms of each of the above metrics, we deem model projections and historical observations to be consistent if and only if the 95% confidence intervals of the differences between the two include zero. As detailed in SM sections S1.2.2 and S1.2.3, these confidence intervals were calculated to reflect two sources of uncertainty: (i) statistical uncertainty in regression coefficients and (ii) structural uncertainty due to different model climate sensitivities, as and when indicated by error bars in projections reported by ExxonMobil scientists.
As an additional measure of performance, we calculate the “skill score” of each model by comparing the root-mean-squared errors of a model projection with those of a zero temperature change null hypothesis (20). For each projection, we calculate skill scores with respect to (i) each of the five observational temperature records for the temperature-versus-time metric and (ii) the 5000 estimates of for the iTCR metric. (See SM section 1.2 for details on graphical overlays and on calculation of consistency and skill scores and their accompanying uncertainties.)
Accurate and skillful climate modeling
Overall, ExxonMobil’s global warming projections closely track subsequent observed temperature increases.
|Projection||Reference||Time frame||Skill (%)||Skill (%)|
|1977 Black (vugraph 10); 1979 Mastracchio | nominal||(54, 88)||1977–2019||22 (–55 to –4)||–49 (–102 to 0)|
|1980 Shaw; 1982 Glaser (fig. 9) | nominal||(36, 89)||1980–2019||73 (53 to 84)||49 (16 to 78)|
|1982* Glaser (fig. 3/table 4); 1984 Shaw | nominal||(36, 37)||1982–2019||82 (61 to 92)||37 (1 to 68)|
|1982 Weinberg et al.; 1984 Callegari | nominal||(41, 42)||1982–2019||70 (64 to 82)||90 (73 to 99)|
|1985* Flannery (page 23) | nominal||(39)||1985–2019||70 (63 to 83)||76 (61 to 92)|
|1985* Flannery (page 24) | high||(39)||1985–2019||87 (66 to 97)||69 (55 to 84)|
|1985* Flannery (page 24) | low||(39)||1985–2019||46 (42 to 55)||90 (73 to 99)|
|1985* Flannery (page 24) | nominal||(39)||1985–2019||71 (64 to 84)||77 (62 to 94)|
|1985* Hoffert and Flannery (fig. 5.16) | high||(38)||1985–2019||28 (–5 to 44)||92 (71 to 99)|
|1985* Hoffert and Flannery (fig. 5.16) | low||(38)||1985–2019||64 (58 to 76)||77 (49 to 97)|
|1985* Hoffert and Flannery (fig. 5.16) | nominal||(38)||1985–2019||99 (80 to 99)||89 (65 to 99)|
|1994* Jain et al. | nominal||(40)||1994–2019||97 (71 to 99)||89 (54 to 99)|
|1997* Kheshgi et al. | nominal||(92)||1997–2010||93 (49 to 98)||34 (–43 to 80)|
|2001 Albritton et al. | nominal||(90)||2001–2019||84 (60 to 98)||81 (18 to 98)|
|2003* Kheshgi and Jain (fig. 7c) | nominal||(91)||2003–2019||56 (41 to 85)||85 (55 to 98)|
|2003* Kheshgi and Jain (fig. 8c) | nominal||(91)||2003–2019||72 (51 to 95)||88 (37 to 99)|
|Average of all projections||67 (60 to 74)||67 (58 to 76)|
|Average of ExxonMobil models||72 (66 to 78)||75 (70 to 81)|
Table 1. Skill scores of global warming projections reported by ExxonMobil scientists in internal documents and peer-reviewed publications.
Scores are shown for () temperature change versus time; and () temperature change versus change in radiative forcing (“implied TCR”). Average skill scores are summarized for (i) all projections and (ii) projections modeled by ExxonMobil scientists themselves (indicated by asterisks). A skill score of 100% indicates perfect agreement with observations; a score less than zero indicates worse performance than a zero temperature change null hypothesis. For each projection, median scores and 5th and 95th percentile confidence intervals are shown, all as percentages. For each average skill score, the mean and the 1σ standard error of the mean are shown. Confidence intervals for projections over short periods—such as Kheshgi et al. (1997), Albritton et al. (2001), and Kheshgi and Jain (2003)—are large, primarily owing to the substantial impact of interannual and subdecadal variability on short-term temperature trends.
What ExxonMobil knew versus what they said
Our findings about the company’s early understanding of climate science contradict many of the claims that the company and its allies have made in public.
Denigrating climate models
Quantifying ExxonMobil’s broader climate knowledge
We gain additional insights into how ExxonMobil misled the public and other stakeholders by further evaluating the company’s climate projections and comparing them to its public communications.
Mythologizing global cooling
Claiming ignorance about discernibility
Staying silent on stranded assets
Quantifying climate knowledge
The authors thank Z. Hausfather (University of California, Berkeley) for technical guidance; P. Achakulwisut (Stockholm Environment Institute) for helpful discussions; and two anonymous peer reviewers.
Funding: The authors are supported by a Rockefeller Family Fund grant (G.S.) and Harvard University Faculty Development Funds (N.O.).
Author contributions: Conceptualization: G.S., S.R. Methodology: G.S., S.R. Investigation: G.S. Writing – original draft: G.S. Writing – review & editing: G.S., S.R., N.O. Visualization: G.S. Supervision: G.S., N.O. Funding acquisition: G.S., N.O.
Competing interests: The three authors have received speaking and writing fees, and S.R. and N.O. have received book royalties for communicating their research, which sometimes includes but is not limited to the topics addressed in this paper. G.S. and N.O. have offered their expertise pro bono to groups and organizations combating climate change, including briefing attorneys and coauthoring amicus briefs in climate lawsuits. N.O. has in the past served as a paid consultant to Sher Edling law firm, which has filed complaints against ExxonMobil Corp and other fossil fuel companies. However, Sher Edling played no role in this or any other study by the authors (including but not limited to study conceptualization, execution, writing, or funding).
This PDF file includes:
Materials and Methods
Tables S1 to S4
References and Notes
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