Ocean and Climate Dynamics @UCI

Principal Investigator: Henri F. Drake, Department of Earth System Science

News

Researchers reveal ExxonMobil’s hypocrisy on climate and use our previously published method to quantify it

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An article published in Science today demonstrates that ExxonMobil scientists have been accurately predicting global warming since the 1980s, even as the company publicly downplayed the link between carbon dioxide emissions and global warming. To quantitatively evaluate the climate projections published in internal company memos, the team of researchers led by Dr. Geoffrey Supran used the implied Transient Climate Response (iTCR) method we first published in Geophysical Research Letters in 2020 (and which features prominently in the Intergovernmental Panel on Climate Change (IPCC)’s Sixth Assessment Report).

We can compare these metrics with [Hausfather, Drake, Abbott, and Schmidt] (2020), who calculated the average skill scores of 18 academic and government climate model projections published between 1970 and 2007. They obtained a value of 69% for both temperature-versus-time and iTCR metrics (16). On average, therefore, global warming projections reported by ExxonMobil scientists were as skillful as those of independent scientists of their day, and their own models were especially skillful.

Supran et al. (2023), Science [link]

Fig. 3. Comparison of (red) historical temperature observations and (gray or black) global warming projections reported by ExxonMobil scientists in internal documents and peer-reviewed publications, as illustrated in Figs. 1 and 2.
Observed and projected trends are compared in terms of (A) temperature change versus time and (B) temperature change versus change in radiative forcing (“implied TCR”). iTCR is defined as the change in temperature versus change in radiative forcing (see materials and methods and SM section S1.2.3 for details). The left-to-right order of panels corresponds to the numbering of projections (“1” to “12”) in Figs. 1 and 2. Trends are computed over model projection periods indicated in the blue boxes above each panel. Asterisks indicate global warming projections modeled by ExxonMobil scientists themselves. The yellow-labeled box in (A) displays averages and bootstrapped standard errors of (black) the 16 projections reported by ExxonMobil scientists spanning 1977 to 2003 and (cyan) 18 academic and government climate model projections spanning 1970 to 2007 reported by Hausfather et al. (2020) (16). [Reproduced from Supran et al. (2023), Science]

These new results are likely to be cited in ongoing lawsuits by cities, counties, and states “accusing ExxonMobil Corp and others of deceptive marketing, misleading shareholders, and culpability for climate changes”.

While this new research is quite far from the focus of our research group, it is a perfect illustration of how even the most basic of climate science research (including ours!) can advance the global movement for climate justice (see also the recent essay Geoffrey Henderson and I published in Climatic Change).

Two companion papers on deep ocean mixing, eddies, and tracer transport published in Journal of Physical Oceanography

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Part 1: Dynamics of eddying abyssal mixing layers over sloping rough topography

This paper uses a hierarchy of idealized models, from approximate analytical solutions in terms of elementary functions to non-linear simulations requiring high performance computers, to understand how small-scale turbulence mixing can drive strong flows along gently sloping ocean topography such as Mid-Atlantic Ridges.

By adding in the complexity of the real ocean one step at a time, we can understand how several individual processes combine to produce the complicated patterns we observe in reality.

(b),(c) Height above bottom-averaged stratification profiles at t = 5000 days, as a function of model complexity (lines) and domain subregion. (a) 1D solutions with the same parameters as the BBTRE simulations (solid); without a mean-slope (dashed), without rotation (f = 0; dotted); and with an enhanced along-slope turbulent Prandtl number (dash-dotted), a crude proxy for restratification by submesoscale baroclinic eddies (dash–dotted) [also shown in gray lines in (b) and (c)]. Colored lines show a hierarchy of 3D simulations with increasingly complex topographies (see figure above). Arrows show how the stratification profiles evolve when processes are added: 1) adding a mean slope, 2) allowing 3D eddies, 3) introducing a cross-slope canyon, 4) blocking the canyon with a sill, and 5) adding realistic hills (i.e., the BBTRE topography).

Part 2: Diapycnal displacement, diffusion, and dispersion of tracers in the ocean

This paper presents a new theoretical framework for exactly comparing in-situ estimates of ocean mixing rates with bulk rates inferred from the spreading of an injected tracer, which improves upon previous approximate methods that assume a direct relationship between diffusion and dispersion.

We use high-resolution quasi-realistic simulations to generate synthetic observations that demonstrate, at least as a proof-of-concept, that the new method provides less ambiguous estimates of ocean mixing.