US Dept Of Energy Climate Report Eviscerates The Climate Changed Extreme Weather Narrative

The full report can be found here. It’s a long report, amounting to some 140 pages, about which much has already been written, but I want to focus on one section only: Extreme Event Attribution (pp.95-97). The authors write (my bold):

While the overall issue of detecting changes in extreme weather events and their attribution remains ambiguous, most of the activity in this area relates to the attribution of particular extreme weather events. The most prominent effort is World Weather Attribution (WWA; worldweatherattribution.org), an international research initiative for extreme event attribution that purports to analyze how climate change influences the likelihood and intensity of extreme weather events. Their approach is to use large ensembles of regional climate models to compare an event in today’s climate with one in a counterfactual pre-industrial climate without human influences.

WWA has a prominent public presence in linking extreme weather to climate change, with its press releases attracting considerable attention in public and policy discussions. However, WWA’s extensive promotion of non-peer-reviewed findings, its open admission to shaping analyses to serve litigation, and its methodological challenges have sparked controversies, with critics questioning the robustness and impartiality of their conclusions (Pielke Jr. 2024). Despite these issues, WWA’s work continues to influence climate science and media narratives. Technical criticisms of the approach include a lack of a formal detection process; an implicit assumption that 100 percent of the post-industrial warming is caused by greenhouse gases; and a failure to adequately account for internal climate variability.

Because EEA is relatively new, many basic methodological issues have yet to be settled in the expert literature. An important challenge is the lack of data. Extreme events are by definition rare. Many analyses of extreme event types (including the U.S. National Assessment Reports) only evaluate data since 1950 or 1970. However, as emphasized in Chapter 6, many of the worst extreme weather and climate events in U.S. history occurred in or before the first half of the 20th century, including in the early 19th century. And if paleoclimate reconstructions are considered, it becomes very difficult for an event to pass thresholds of what is expected from natural variability, particularly if a reasonably sized geographic region is considered.

Another challenge is defining the event under study. There is a longstanding literature in statistics and econometrics on the challenge of analyzing data with outliers. The issue arises because a data series establishes a probability distribution defining the expected range of observations. If an outlier is observed it might indicate that the underlying process giving rise to the data distribution has changed (which in the weather context would mean that a climate change has been detected) or that the underlying process has multiple regimes each with a different probability distribution, in which case observing an outlier simply means we were temporarily in a different regime, but the system itself was unchanged. If a time series contains only a single outlier event at the end of the series, it is not possible to determine which model is the correct one (Chen and Liu 1993). For instance, there might be an “ordinary” weather regime that yields a distribution of summer daytime highs in a particular coastal region, and a second “heatwave” regime that kicks in when an inland blocking event occurs, which yields a temperature distribution centered 15°C higher than the first one. A day with temperatures 13°C above normal would either be an extreme heat anomaly under the first regime or a somewhat cool event under the second, and we have no way in this case of knowing on statistical grounds which view is correct.

Visser and Petersen (2012) and Sardeshmukh et al. (2015) both point out that different distributions might fit observed data equally well but yield very different implications about the likelihood of a specific weather event. Visser and Petersen argue that, in view of the deep uncertainties of extreme weather analysis, drawing a connection between individual events and global climate change should be avoided. Furthermore, the existence of an outlier at the end of a data series poses the problem that estimates of the event probabilities will be biased whether the outlier is included or excluded (Barlow et al., 2020). Methods to eliminate the bias have not yet been established, leading some experts (e.g. Miralles and Davison 2023) to argue that in settings in which a data series contains a single extreme event at the end, estimation of a return period for the extreme event will be so biased and uncertain that it should be avoided altogether.

I have been criticising extreme weather attribution, and in particular the antics of WWA, for 9 years now, so none of this commentary is new to me and indeed those sections I have highlighted echo almost word for word many of my own criticisms over the years. In August 2016, for instance, I wrote:

Extreme weather attribution is an obscure ‘science’, reliant upon a rather cliquey peer-reviewed scientific literature pioneered by Peter Stott of the Met Office, consisting essentially of endless climate model runs, with and without anthropogenic forcings, looking at regional weather forecasts, global and regional climate change projections, and past meteorological data, then putting it all together in a giant melting pot to arrive at what is called a Fraction of Attributable Risk (FAR) for any one particular extreme event – basically, the increased probability of such and such happening if one assumes ‘known’ anthropogenic GHG forcings. You can call it science or you can call it hocus pocus.

This is the standard, rather long-winded process; the slow-cook method – which isn’t much use if you want to foil the evil machinations of the merchants of climate doubt who, because they are rank amateurs, can quickly and easily come up with AOR to misinform the public with. Enter our crack team of First Responder Climate Change Attributors, complete with flashing blue lights atop a fully equipped alarmist ambulance, on the scene in a jiffy in order to pronounce gravely that the patient is suffering from a serious case of the global warminks. They can do this because, I quote:

Rather than running models after an event, researchers like Dr. van Oldenborgh and Dr. Otto shorten the process by using models that have already been run.

“The only way we can do this rapid attribution is by precooking everything that we can,” Dr. van Oldenborgh said.

There you have it; pre-cooked, ready to go model runs that they can just throw into the wok, sizzle and serve up almost immediately for public consumption. Hubble, bubble, toil and no trouble!

At least, that is what they hope to achieve eventually; trouble-free, ‘routine’ attribution analyses of extreme weather events that will not even require the submission of peer reviewed papers:

Although the hope is that such studies will eventually become so routine that there is no need to publish the findings in a scientific journal, for now, at least, a research paper has to be written and submitted for peer review. So for the flooding analysis, that was another week’s work for Dr. van Oldenborgh.

Friederike Otto and van Oldenborough founded World Weather Attribution in 2014. They achieved their ambition of churning out ‘rapid’ extreme weather attribution analyses (minus peer review) and I wrote about one of their early fairly rapid attribution studies here in 2018:

Rapid extreme weather attribution, aka climate ambulance chasing, has come of age and the attributors are in high demand:

For Friederike Otto, a climate modeller at the University of Oxford, UK, the past week has been a frenzy, as journalists clamoured for her views on climate change’s role in the summer heat. “It’s been mad,” she says. The usual scientific response is that severe heatwaves will become more frequent because of global warming. But Otto and her colleagues wanted to answer a more particular question: how had climate change influenced this specific heatwave? After three days’ work with computer models, they announced on 27 July that their preliminary analysis for northern Europe suggests that climate change made the heatwave more than twice as likely to occur in many places.

Soon, journalists might be able to get this kind of quick-fire analysis routinely from weather agencies, rather than on an ad hoc basis from academics. With Otto’s help, Germany’s national weather agency is preparing to be the first in the world to offer rapid assessments of global warming’s connection to particular meteorological events. By 2019 or 2020, the agency hopes to post its findings on social media almost instantly, with full public reports following one or two weeks after an event. “We want to quantify the influence of climate change on any atmospheric conditions that might bring extreme weather to Germany or central Europe,” says Paul Becker, vice-president of the weather agency, which is based in Offenbach. “The science is ripe to start doing it”.

So it will be just like getting the weather report, albeit just a few days or even just hours after the event, but in this case, you’ll get to know whether storm, heatwave, drought, deluge or freezing spell is simply ‘weather’, or whether it is all the fault of those nasty anthropogenic CO2 molecules which keep popping up in our atmosphere courtesy of our exhaust pipes and modish technological lifestyles. Presumably, if found guilty, we can then all engage in a universal display of repentance, lashing ourselves with the electrical flex ripped from the back of the new dishwasher or cinematic 60 inch flat screen TV with 3D surround sound, slash the tyres on the 4×4, and say ‘it’s a fair cop’ when the insurance company rejects our claim for damage to the roof because it was ‘not a natural disaster’. Oh yes, ’twill be fun.

But before we get too carried away, and start thinking about smashing up the old C-rated washing machine in an anguished fit of remorse, let’s take a look at the supposed damning scientific evidence that we did in fact cause ourselves to cook this summer in what will probably turn out to be the hottest, longest and driest heatwave in parts of northern Europe since way back when it was last this hot and dry.

The clear intention of rapid and super rapid extreme weather attribution was, whilst individual weather events were still fresh in the public mind, to get headlines out in the media claiming that ‘science experts’ had linked that particular event with man-made climate change. It was pure optics; 1% science, 99% climate propaganda, right from the start. And the ‘science’ was not difficult to pick holes in, even for a non expert like me. I was pointing out back then the fallacy of merely assuming that all post industrial warming was man-made, which even the IPCC reports did not support:

Key Assumptions About AGW And Natural Variability

For transient simulations of the changing climate, we again calculate how the probability of the event is changing over time in the model data, by fitting the temperature values to a distribution that shifts proportional to the smoothed global mean temperature. This method assumes that global warming is the main factor affecting local temperatures since about 1900, and that virtually all global warming is attributable to anthropogenic factors. In Europe, with very little decadal variability, the first condition is met. The second assumption is the conclusion of the IPCC, but disregards the uncertainty surrounding it (IPCC WG1 AR5 Chapter 10).

My bold. The authors assume that all global warming since 1900 is anthropogenic and that this is the main factor affecting temperature at the specified locations. They justify these assumptions by reference to IPCC WG1 AR5 Ch. 10. They also state, bare-faced, that northern European climate is subject to very little decadal variability . . . .

Let’s deal with the second assumption first, that most or all global warming since 1900 is anthropogenic. Let us go to AR5 WG1 Ch. 10 and see what it says about the attribution of warming post 1900. When we do, we find it has an awful lot to say about attribution post 1950, stating it is extremely likely that most or all of the warming 1951-2010 is due to GHGs. 1900 to 2010, not so much.

I was also pointing out the scandalous failure to account properly for natural variability:

The IPCC statements also blow a hole in the first assumption of the report’s authors, i.e. that the station locations they’re analysing are subject to little decadal variability. The IPCC clearly mention the importance of the AMO which affects precisely this region. Northern European climate is subject to a lot of multi-decadal internal variability, principally by the AMO which has a cycle length of approximately 70 years, which is more than sufficient to have affected temperatures at the specified locations from 1900 to the present! For the avoidance of doubt in this respect:

The Atlantic multidecadal oscillation (AMO) explains over 90% of the pronounced decadal temperature and summer precipitation variation. Understanding the impact of these ocean variations when interpreting long climate records, particularly in the context of a changing climate, is crucial.

[https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/wea.2543]

That rather buggers up the supposedly eminently suitable data from Phoenix Park, Dublin, with regards to demonstrating the probability of extreme weather supposedly unaffected by the presence of natural climate variability, subject only to anthropogenic influences!

Well I must say, it’s good to see that the United States government now recognises that extreme weather attribution (and WWA) are as dodgy as I’ve been saying for several years now!