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The weak methodology and accuracy of climate models is the subject of an entertaining Norman Rogers post. I want to share just a few passages along with a couple of qualifiers.

Rogers quotes Kevin Trenberth, former Head of Climate Analysis at the National Center for Atmospheric Research, with apparent approval. Oddly, Rogers does not explain that Trenberth is a strong proponent of the carbon-forcing models used by the UN’s Intergovernmental Panel on Climate Change (IPCC). He should have made that clear, but Trenberth actually did say the following:

‘[None of the] models correspond even remotely to the current observed climate [of the Earth].’“

I’ll explain the context of this comment below, but it constitutes a telling admission of the poor foundations on which climate alarmism rests. The various models used by the IPCCc are all a little different and they are calibrated differently. I’ve noted elsewhere that their projections are consistently biased toward severe over-predictions of temperature trends. Rogers goes on from there:

“The models can’t properly model the Earth’s climate, but we are supposed to believe that, if carbon dioxide has a certain effect on the imaginary Earths of the many models it will have the same effect on the real earth.

But how on earth can a modeler accept the poor track record of these models? It’s not as if the bias is difficult to detect! On this question, Rogers says:

The climate models are an exemplary representation of confirmation bias, the psychological tendency to suspend one’s critical facilities in favor of welcoming what one expects or desires. Climate scientists can manipulate numerous adjustable parameters in the models that can be changed to tune a model to give a ‘good’ result.

And why are calamitous projections desirable from the perspective of climate modelers? Follow the money and the status rewards of reinforcing the groupthink:

Once money and status started flowing into climate science because of the disaster its denizens were predicting, there was no going back. Imagine that a climate scientist discovers gigantic flaws in the models and the associated science. Do not imagine that his discovery would be treated respectfully and evaluated on its merits. That would open the door to reversing everything that has been so wonderful for climate scientists. Who would continue to throw billions of dollars a year at climate scientists if there were no disasters to be prevented?

Indeed, it has been a gravy train. Today, it is reinforced by green-preening politicians, the many billions of dollars committed by investors seeking a continuing flow of public subsidies for renewables, tempting opportunities for international redistribution (and graft), and a mainstream media addicted to peddling scare stories. The parties involved all rely on, and profit by, alarmist research findings.

Rogers’ use of the Trenberth quote above might suggest that Trenberth is a critic of the climate models used by the IPCC. However, the statement was in-line with Trenberth’s long-standing insistence that the IPCC models are exclusively for constructing “what-if” scenarios, not actual forecasting. Perhaps his meaning also reflected his admission that climate models are “low resolution” relative to weather forecasting models. Or maybe he was referencing longer-term outcomes that are scenario-dependent. Nevertheless, the quote is revealing to the extent that one would hope these models are well-calibrated to initial conditions. That is seldom the case, however.

As a modeler, I must comment on a point made by Rogers about the use of ensembles of models. That essentially means averaging the predictions of multiple models that differ in structure. Rogers denigrates the approach, and while it is agnostic with respect to theories of the underlying process generating the data, it certainly has its uses in forecasting. Averaging the predictions of two different models with statistically independent and unbiased predictions will generally produce more accurate forecasts than the individual models. Rogers may or may not be aware of this, but he has my sympathies in this case because the IPCC is averaging across a large number of models that are clearly biased in the same direction! Rogers adds this interesting tidbit on the IPCC’s use of model ensembles:

There is a political reason for using ensembles. In order to receive the benefits flowing from predicting a climate catastrophe, climate science must present a unified front. Dissenters have to be canceled and suppressed. If the IPCC were to select the best model, dozens of other modeling groups would be left out. They would, no doubt, form a dissenting group questioning the authority of those that gave the crown to one particular model.”

Rogers discusses one more aspect of the underpinnings of climate models, one that I’ve covered several times on this blog. That is the extent to which historical climate data is either completely lacking, plagued by discontinuities or coverage, or distorted by imperfections in measurement. The data used to calibrate climate models has been manipulated, adjusted, infilled, and estimated over lengthy periods by various parties to produce “official” and unofficial temperature series. While these efforts might seem valiant as exercises in understanding the past, they are fraught with uncertainty. Rogers provides a link to the realclimatescience blog, which details many of the data shortcomings as well as shenanigans perpetrated by researchers and agencies who have massaged, imputed, or outright created these historical data sets out of whole cloth. Rogers aptly notes:

The purported climate catastrophe ahead is 100% junk science. If the unlikely climate catastrophe actually happens, it will be coincidental that it was predicted by climate scientists. Most of the supporting evidence is fabricated.”