Why wasn’t this astonishing, large error of basic astrophysical calculations caught billions of dollars ago, and how much has this error affected the results of all modeling studies in the past?
The paper adds to hundreds of others demonstrating major errors of basic physics inherent in the so-called ‘state of the art’ climate models, including violations of the second law of thermodynamics. In addition, even if the “parameterizations” (a fancy word for fudge factors) in the models were correct (and they are not), the grid size resolution of the models would have to be 1mm or less to properly simulate turbulent interactions and climate (the IPCC uses grid sizes of 50-100 kilometers, 6 orders of magnitude larger). As Dr. Chris Essex points out, a supercomputer would require longer than the age of the universe to run a single 10 year climate simulation at the required 1mm grid scale necessary to properly model the physics of climate.
But let’s get a carbon tax, right now!
This statement is true but misleading “the grid size resolution of the models would have to be 1mm or less to properly simulate turbulent interactions and climate”
Yes, we’ve dealt with this for many years with turbulence models, is he suggesting that no computational fluid dynamic models be created with grids that don’t resolve the Kolmogorov scale? Plenty of rockets and airplanes fly just as the CFD predicts with doing that.
But to the general point, no we shouldn’t make big changes to our economy based on these models. It wasn’t until maybe 20 years ago that it was possible to make an accurate estimate of heat transfer to a flat plate using CFD, now I’m supposed to believe that CFD can resolve heat transfer globally?
On the other hand the simple radiation calculation easily convinces almost everyone that adding CO2 to the atmosphere must cause a temperature rise. 10 degrees or a nano degree, that’s the question.
“Plenty of rockets and airplanes fly just as the CFD predicts with[out] [resolving the Kolmogorov scale].”
With a grid size of 100 km, climate models can’t resolve a turbulence scale smaller than a hurricane…and a big one, at that. The CFD models used in aircraft and missile aerodynamics use very fine grids in the boundary layer region, and all of them still have to use an artificial turbulence model. Generally, the model is “anchored” with wind tunnel and flight test; the turbulence parameters are fiddled with until the flow matches what is seen in test, and, yes, the airplanes fly just as the CFD says they should. The models produce these stellar predictions after the fact, however. It’s an expensive exercise in curve-fitting, IMHO.
Climate modelers seem to need to impress people with their “rigor,” and so use the Navier-Stokes equations for their fluid dynamics. I can’t think of any legitimate reason to do this, given that at the grid size they are talking about, there is no point in including viscous effects. In fact, it’s counterproductive in that discrete N-S solutions of unsteady flows (even with very well defined geometries and tight grids) are unstable at large Reynolds numbers, and are useless after a few thousand time steps. For a 100 km grid, the Reynolds number would be on the order of 100E6 for a gentle breeze. It’s no surprise that no two model outputs are even close to the same.
This incident radiation error is symptomatic of the larger problem climate modelers have: they don’t know what they’re doing.
“Why wasn’t this astonishing, large error of basic astrophysical calculations caught billions of dollars ago”
Who would dare speak up? Even if you enthusiastically believed in global warming, raising questions like this could get you labeled a denier.
So models are models and don’t have the details of the real thing!
Amazing.
Models that far off are useless.
As I read it, the problem the authors see in that, like the spatial resolution, the temporal resolution is, um, lumpy, but as long as that lumpiness isn’t causing a spurious trend, the model output should still be useful.
I’m not going to argue whether or not that’s the case, I don’t know enough to judge.
I get the impressing that climate modelers routinely don’t bother to validate against the real world.
Sort of the climate model equivalent of looking at the newspaper forecast for the current conditions instead of looking out the window.
That’s a mind boggling error.
Meanwhile, Judith Curry pointed to what may be the most profound paper yet. Link
I was partway through the abstract and was gobsmacked:
Joint analyses of surface solar flux data that are a complicated mix of measurements and model calculations with top-of-atmosphere (TOA) flux measurements from current orbiting satellites yield a number of surprising results including (i) the Northern and Southern Hemispheres (NH, SH) reflect the same amount of sunlight within ~ 0.2Wm2. This symmetry is achieved by increased reflection from SH clouds offsetting precisely the greater reflection from the NH land masses. (ii) The albedo of Earth appears to be highly buffered on hemispheric and global scales as highlighted by both the hemispheric symmetry and a remarkably small interannual variability of reflected solar flux (~0.2% of the annual mean flux). We show how clouds provide the necessary degrees of freedom to modulate the Earth’s albedo setting the hemispheric symmetry. We also show that current climate models lack this same degree of hemispheric symmetry and regulation by clouds.
The Earth’s albedo is tightly regulated by feedback mechanisms.