Kludgy, Inaccurate Climate Models Undergird Costly Net-Zero Agenda
Climate change prophecy hangs its hat on computer climate models. But the models have gigantic problems.
According to Kevin Trenberth, once in charge of modeling at the National Center for Atmospheric Research, “None of the models correspond even remotely to the current observed climate of the Earth.” [bold, links added]
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 Earth of the many models it will have the same effect on the real Earth. 1
The Wall Street Journal and Powerline report climate models’ projections of future temperatures have gotten worse over time.
As new generations of supposedly improved climate models are produced and refined, the accuracy of their temperature simulations decreases.
Here are some recent examples:
Using the same tree-ring dataset, 15 groups come up with 15 different reconstructions, reported in a 2021 study.
This was a double-blind experiment of 15 different groups that yielded 15 different Northern Hemisphere summer temperature recommendations.
Each group used the same network of regional tree-ring width datasets. 3
What’s fascinating is that all groups, despite using the same data network, came up with different results.
When it comes to deriving temperatures from tree rings, it has much to do with individual approach and interpretation. We can follow the science, but whose results?
The 15 groups who contributed independently to the experiment all had experience in developing tree-ring-based climate reconstructions. But as the study describes, each group employed a distinct reconstruction approach.
How could the groups come up with different results?
The paper abstract summarizes:
“Differing in their mean, variance, amplitude, sensitivity, and persistence, the ensemble members demonstrate the influence of subjectivity in the reconstruction process. We, therefore, recommend the routine use of ensemble reconstruction approaches to provide a more consensual picture of past climate variability.” 3
Perhaps this should not surprise since tree-ring width does not correlate to temperature. Botanists, horticulturists, foresters, and paleobotanists have been saying this for 30 years but ‘climate scientists’ refuse to listen.
Another recent study highlights the abysmal model performance manifested in the latest Intergovernmental Panel on Climate Change report (AR6).
The 38 CMIP6 circulation models fail to adequately simulate even the most recent (1980-2021) warming patterns over 60 to 81% of the Earth’s surface. 4
The author places particular emphasis on the poor performance of the highly uncertain estimates (somewhere between 1.83°C and 5.67°C) of equilibrium climate sensitivity (ECS) and their data-model agreement relative to 1980-2021 global warming patterns.
The worst performing ECS estimates are the ones projecting 3-4.5°C and 4.5-6°C warming in response to doubled CO2 concentrations (to 560 ppm) plus feedback, as the 1980-2021 temperature trends are nowhere close to aligning with these trajectories. 5
A study by John Christy demonstrates climate models consistently overstate the warming effect of increasing carbon dioxide concentrations on climate.6
Christy warns that the models are warming too fast. In the early 1990s, most climate modelers developed models projecting a 0.35 degree Celsius rise in temperature.
Using satellite readings available since 1979, Christy and colleague Dick McNider projected the amount of carbon dioxide being added to the atmosphere should cause the Earth to warm, on average, by about 0.09 degrees Celsius per decade.
That’s about one-quarter of the level projected by prevailing models used by the IPCC and government agencies such as NASA.
He concludes, “The warming trend we found suggests that we are having a relatively minor impact on global temperatures. 7
Legend Princeton physicist Freeman Dyson has harsh critical words for climate scientists and the models they rely on. He calls the science of climate modeling a ‘very dangerous game.’
He adds, “When you work with a computer model for years and years, always improving the model, in the end, you end up believing it. It’s very difficult to remain objective.”
On why we should not trust the models, Dyson says, ‘because they’re wrong, it’s very simple, they’re wrong.’
He adds that although the models are ‘very good tools for understanding climate,’ they are ‘very bad tools for predicting climate,’ and that these scientists ‘live by scaring the public.’ 8
Read more and footnotes at CFP
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