A new paper just published in Science Bulletin by Mark Richardson, Zeke Hausfather, Dana Nuccitelli, Ken Rice, and John Abraham shows that mainstream climate models simulate global temperature observations much better than the “irreducibly simple climate model” of Christopher Monckton, Willie Soon, David Legates, and William Briggs.

When the Monckton paper was published in the Chinese journal Science Bulletin this January, it was covered by conservative media outlets like the Daily Mail, Breitbart and World Net Daily, which used it to manufacture doubt about the dangers associated with human-caused global warming. The ideologically-appealing but scientifically incorrect message from the paper was essentially, ‘climate models are running hot, the climate is insensitive to the increasing greenhouse effect, and thus future global warming will be minimal and nothing to worry about.’

However, our team identified numerous glaring fundamental errors in the Monckton paper. The first was in the very premise of the paper itself, claiming that global climate models are “running hot.” In reality, as I show in my book Climatology versus Pseudoscience, mainstream climate models have done a good job at projecting the observed changes in the global surface temperature.

While temperature measurements have been toward the lower of the range of model projections in recent years, there’s been a tremendous body of scientific research investigating the various contributors to the slowdown in global surface warming. This research, which was entirely ignored by Monckton and his colleagues, is summarized by Kevin Cowtan in week 5 of the Denial101x course.

Kevin Cowtan’s Denial101x lecture 5.8.1.2.

In fact, ignoring a vast body of important relevant research was a recurring theme throughout the Monckton paper. After they manufactured a problem by exaggerating the discrepancy between mainstream climate model simulations and temperature observations, and ignored the relevant scientific research on that issue, Monckton and colleagues created their own “irreducibly simple climate model” with built-in assumptions based on circuit design rather than the physics of the Earth’s climate system.

Here they made two fundamental mistakes. First, they assumed that the Earth’s climate is very stable, and built that assumption into their model. This assumption was based ignoring most of the body of paleoclimate (historical climate change) research showing big past climate change swings influenced by amplifying feedbacks, and by assuming that the Earth’s climate will behave the same as a human-designed electrical circuit with minimal gain and feedbacks.

Second, based on that first assumption of a stable climate, their paper claimed “warming is already at equilibrium” and the Earth’s response to an energy imbalance is instantaneous. However, this is obviously wrong because satellites measure a large ongoing global energy imbalance, with a tremendous amount of heat building up in the oceans. As John Abraham explains,

The model of Monckton and his colleagues is fatally flawed in that it assumes the Earth responds instantly to changes in heat. We know this isn’t true. The Earth has what’s called thermal inertia. Just like it takes a while for a pot of water to boil, or a Thanksgiving turkey to heat up, the Earth takes a while to absorb heat. If you ignore that, you will be way off in your results.

Circular logic was another fundamental flaw in the Monckton et al. paper – they used their simple model, which assumed that the Earth’s climate is stable and hence insensitive to the increasing greenhouse effect, to demonstrate that the climate is insensitive to the increasing greenhouse effect.

As you might expect from a simple model based on flawed assumptions, as we show in our paper, it does a poor job in reproducing observed temperature changes. In the figure below, the blue area represents temperature changes simulated by climate models used in the last IPCC report; the red area represents temperature simulations from the Monckton et al. simple model; and the red, blue and black lines show the observed global surface temperature changes. As you can see, the mainstream climate models do a much better job simulating the observational data than the flawed, simple model.

Comparison between modelled and observed temperature change (°C) from 1850. Solid lines show observational series HadCRUT4, Berkeley Earth (BEST) and Cowtan and Way. The 5%–95% CMIP5 range and Monckton et al. range are shown as shaded areas. N = 45 CMIP5 models transitioning to RCP6.0 after 2005, M15 model forced with the Otto et al. radiative forcing time series and all temperature series anomalies calculated relative to the 1850–1900 mean. Source: Science Bulletin; Richardson et al. (2015).

Ultimately our paper concludes as follows,

The M15 [Monckton et al. (2015)] model performs poorly against observations because its parameters were selected using a logically flawed narrative, rather than physical and mathematical analysis. Observational evidence from palaeoclimate and of ocean heat content measurements directly contradict the values adopted by M15, but are not acknowledged. Partial use and misinterpretation of the relevant literature may explain many of the differences between statements in M15 and the results of other studies. The authors of M15 cite some studies supporting their estimate of lower climate response, but miss much of the larger body of research that contradicts the claims in M15 … Their low estimates of future warming are due to assumptions developed using a logically flawed justification narrative rather than physical analysis. The key conclusions are directly contradicted by observations and cannot be considered credible.

The paper by Monckton and colleagues was badly flawed and should not have been published, but at least Science Bulletin also published our critique just a few months later. This incident shows that while the peer-review process is necessary, it’s insufficient by itself to filter out all erroneous research. Sometimes bad papers still get published, and when the results of those papers align with the ideological biases of certain media outlets, their faulty conclusions can misinform a large audience.

In short, be skeptical of new research, especially if it purports to overturn a large body of scientific evidence, and wait to see if the study withstands subsequent scientific scrutiny. In the case of this paper published by Monckton and colleagues, it did not.