Dr. Richard Lindzen and Dr. William Happer cover the sound reasons for climate science skepticism, the politicization of research funding, and the limitations of current climate models. //

Happer and Lindzen discuss how government funding mechanisms and political narratives shape climate research priorities. They argue that scientists who challenge mainstream views risk career marginalization and loss of funding. Rogan’s audience was treated to a robust review on how ideology and media framing have amplified what Happer calls a “CO₂ cult,” and how vital it is to question the reliability of predictive climate models. //

rhhardin | October 24, 2025 at 7:22 am
It was clear that science had nothing to say about global warming right from the hockey stick curve long ago, for two reasons that intersected with what was known about other things:

1. You can’t solve the Navier Stokes equations, which govern fluid flow. In 2D, flows go to larger and larger scales, and there’s no problem with numerical calculations. In 3D, flows go to shorter and shorter scales, and no numerical calculation can do the physics because the grid size is always too coarse no matter how fine it is. (The mechanism is that in 3D, vortices can kink and break up, which they cannot do in 2D. Those fine scale flows resulting feed back on larger scale flows by way of constituting a change in viscosity – transport of x momentum in the y direction etc. – on the large scale flows. Actually a tensor, not a scalar)
   So every calculation includes a term “effective viscosity” which does not appear in the Navier Stokes equation, and at that point stops doing physics. So no calculation is possible.

Weather forecasts are good for two or three days, which is how long it takes large scale vortices to kink. After that they’re no good.

2. You can’t say any historical change in temperature isn’t part of a long cycle and not a trend. A long cycle can’t be man-caused, a trend might be. The mathematical mechanism is that the linear system you have to solve to distinguish long cycles from trends develops eigenvectors of about 10 to the 30th power, which instantly multiplies any noise in the measurements and swamps the effort to distinguish. You need data that’s not shorter than they cycles that you want to eliminate, called the uncertainty principle in math (and quantum mechanics which has the same math but not other relation).

So there are no models and no data in support of man-caused global warming, in principle. //

DaveGinOly in reply to rhhardin. | October 24, 2025 at 11:58 am
The models themselves can’t provide any predictive authority. Even the UN cautions that the results spit out by models aren’t predictions. The trouble with models is that they are built by modelers who have preconceptions of how the climate works and changes over time. If a researcher thinks CO2 has an effect (there are good arguments that it doesn’t, for instance the geologic record shows the CO2 rises in response to warming, and not the other way around, there is also some – I think – very convincing science that CO2 causes warming up to a certain concentration, after which adding more CO2 has no effect), then he builds a model in which the virtual climate reacts to its virtual CO2 levels. If you had a theory that said the climate responds to the number of houses that are painted yellow, you’d build a model that had such a feedback mechanism in it. And, sure enough, if you increase the number of virtual yellow houses in the model, the virtual climate would respond. But that wouldn’t mean it isn’t utter nonsense.

Models can only show how a natural system might work. They represent theories and therefore prove nothing. Real-world observations are necessary to validate the theory. Even if the climate models are accurate, nobody has demonstrated, with real-world observations, that the actual climate behaves like their models.

Also note that there are literally dozens of climate models. Nearly every research group creates their own. This should inform us that no climate researchers have any faith in the climate models of any other researcher. What does that say about the reliability of the models?

“Science…requires only one investigator who happens to be right, which means that he or she has results that are verifiable by reference to the real world. In science, consensus is irrelevant. What are relevant are reproducible results.”
Dr. Michael Crichton
Speaking at the California Institute of Technology, 2023. //

Ironclaw in reply to rhhardin. | October 24, 2025 at 12:32 pm
I understood that political science is the only science involved with climate when they started going back and “correcting” measurements made nearly a century ago.