“The question is, whether you can make words mean so many different things?” — Alice in Wonderland
Over at The Climate Brink, Andrew Dessler and Zeke Hausfather have taken on the role of self-appointed sheriffs of climate science, at times in highly partisan and personal terms. Recently, Dessler, along with another scientist, Robert Kopp, and dozens of others, prepared a lengthy response to the Department of Energy’s Climate Working Group (DOE CWG) report.
The focus of Dessler’s post is his claim that the DOE CWG authors fail to appreciate the distinction between the concepts detection and attribution and time of emergence — and this represents “the central flaw” in the DOE CWG report.
In fact, as I show undeniably below, Dessler’s post reveals that he actually does not understand IPCC terminology or its application. Irony abounds. Someone should be embarrassed, and it’s not the DOE CWG authors.
Let’s dive into the details.
Dessler presents a definition of the time of emergence of a climate signal that is completely at odds with the definition used by the Intergovernmental Panel on Climate Change (IPCC). Dessler then uses his bespoke definition to argue that the DOE CWG authors made an “embarrassing error” by not employing his bespoke definition, rather than instead relying on the IPCC.
Here is Dessler’s bespoke definition (emphases in original):
Emergence is all about the size of the influence. It means that the climate has shifted so much that the average value of some parameter is larger than the largest value in a pre-industrial climate. In other words, you’ve emerged into a new climate.
The IPCC, in stark contrast, has a very different definition of the time of emergence (emphases in original):
Time when a specific anthropogenic signal related to climate change is statistically detected to emerge from the background noise of natural climate variability in a reference period, for a specific region (Hawkins and Sutton, 2012).
The signal of anthropogenic climate change is emerging against the background of natural climate variability. Only when the signal of change is of sufficient magnitude relative to this background variability can we be confident that a significant change has been detected. Such detection is a necessary step in the process of attributing a particular change to a specific cause, such as the observed rise in greenhouse gas concentrations [Hegerl et al., 2007].
Hawkins and Sutton (2012) explain that the time of emergence is a forward looking concept, in contrast to detection, which is backwards looking (emphasis added):
A headline conclusion from the IPCC AR4 was that “most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations”. Of greater importance for adaptation to climate change are changes on the regional and local scales that affect people, economies and ecosystems. However, on these smaller scales natural variability is larger, making detection more difficult. Some detection and attribution studies that have addressed these scales have obtained positive results [Hegerl et al., 2007; Stott et al., 2010], but for many regions and variables the signal of anthropogenic change has yet to clearly emerge from the ‘noise’ of natural climate variability.
So when will the signal emerge? And where and how?
Under the definitions of the IPCC, when looking at the past climate, detection of change (at a particular statistical level of confidence) and emergence of a signal of change (employing various possible methods) are conceptually identical, even if specific methodologies and results may vary.
The concept of time of emergence is also applicable to projections of future climate because it allows researchers to explore when we might expect changes in specific variables to emerge from the background of natural variability — for instance, based on alternative climate scenarios. models, and projections.
To be charitable to Dessler, it is conceivable that he has simply confused a single example provided by the IPCC in its framing chapter with the IPCC’s more general approach to the concept of time of emergence.
Specifically, IPCC AR6 Chapter 1 provides an “example” of one approach to calculating a time of emergence (emphasis added):
An example of observed emergence in surface air temperatures is shown in Figure 1.14 . . . [Figure 1.14 shown above]
The Figure 1.14 is based on Hawkins et al. 2020, who explain their unique methodological approach:
Here, we revisit the question of where and how the climate change signal is emerging from the background noise of internal variability. . . Our aim is to produce estimates of signal-to-noise (S/N) for changes in observed climate variables without utilizing data from any climate model simulations.
The IPCC acknowledges the validity of a signal-to-noise methodology such as of Hawkins et al. 2020, but the IPCC does not adopt that methodology as its definition of time of emergence or the only acceptable methodological approach to quantify a time of emergence.
The IPCC explains this clearly using the word “often” and not “always” (emphasis added):
This concept [emergence] is often expressed as a ‘signal-to-noise’ ratio and emergence occurs at a defined threshold of this ratio (e.g., S/N > 1 or 2).
For instance, in 2011 Ryan Crompton, John McAneny, and I published a very early paper on time of emergence using a different, but equally vaild statistical approach:
The larger issue here — the elephant in the room — is not the DOE CWG report, but rather the IPCC itself, which published the rather inconvenient but scientifically accurate summary table below in Chapter 12 of the AR6.
Table 12.12 explains that for most measures of extreme events (and a few others in the table) the signal of climate change has not emerged and is not expected to emerge by 2050 or 2100, even under the implausibly extreme RCP8.5 scenario. I’d guess that Dessler’s target here is the IPCC, but no climate scientist will want to be seen taking on the IPCC directly.
The IPCC clearly explains of Table 12.12:
The emergence of a climate change signal occurs when that signal exceeds some critical threshold (usually taken to be a measure of natural variability; see for example, Hawkins and Sutton, 2012) or when the probability distribution of an indicator becomes significantly different to that over a reference period (e.g., Chadwick et al., 2019; see also Chapter 10 and Section 1.4.2), in which case external anthropogenic forcings can be detected as causal factors. The ‘time of emergence’ (ToE) or ‘temperature of emergence’ is the time or global warming level thresholds associated with this exceedance. Emergence is particularly relevant to impacts, risk assessment and adaptation because human and natural systems are largely adapted to natural variability but may be vulnerable if exposed to changes that go beyond this variability range; this is not to say that changes within natural variability have no impact, as occurrence of damaging extremes proves. Emergence also informs the timing of adaptation measures.
Dessler’s bespoke definition of time of emergence is nowhere to be seen.
Based on his critique, Dessler takes issue with a claim of the DOE CWG report:
[I]t is not currently possible to attribute changes in most extreme weather types to human influences.
Dessler is incorrect — But I would make a few edits to the DOE CWG sentence to improve precision and recognize the confidence qualifiers of the IPCC:
[I]t is not currently possible to detect or attribute with high confidence changes to date in most extreme weather types to human influences.
IPCC Chapters 11 (detection and attribution) and 12 (time of emergence) are perfectly consistent with each other. Below is a summary table of IPCC conclusions for the detection and attribution of trends in various types of extreme weather, at the IPCC’s stated level of confidence for achieving detection and attribution.
For details and direct statements from the IPCC, see this THB post.
The DOE CWG is a convenient foil to use to have a go at the IPCC itself. Its Table 12.12 is scientifically accurate, but problematic for those wanting to claim that every extreme event reflects human caused changes in climate.
This episode reinforces why we need scientific assessments that include experts who understand the literature, are willing to call things straight, and lets the chips fall where they may regardless whose political advocacy might be affected. Red team and blue team science is fun team sport, but it is not good for reaching robust understandings.
So far the IPCC WG1 has played things straight with respect to extreme events. Let’s hope that it continues.
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"average value of some parameter is larger than the largest value in a pre-industrial climate" Average on what spatial and temporal scale? How could we possibly know the largest value of anything when we had so few observation of so few parameters in so few places pre-industrially? To me that sentence doesn't make sense on its own surface, let alone the lack of consistency with IPCC. I'd say "you can't just make up your own definitions" but I guess some people can.
Roger, you are always thoughtful and a gentleman. I may not understand all of your climate information forays, but I do appreciate classy when I read it.
I don't mean to be too picky.. but
"average value of some parameter is larger than the largest value in a pre-industrial climate" Average on what spatial and temporal scale? How could we possibly know the largest value of anything when we had so few observation of so few parameters in so few places pre-industrially? To me that sentence doesn't make sense on its own surface, let alone the lack of consistency with IPCC. I'd say "you can't just make up your own definitions" but I guess some people can.
Roger, you are always thoughtful and a gentleman. I may not understand all of your climate information forays, but I do appreciate classy when I read it.