Besides the overwhelming fact that it is fundamentally and mathematically impossible for climate models to predict climate, there are more good reasons to doubt climate models can predict climate.
You Can’t Talk Around Chaos
When most climate scientists, who have little understanding of chaos, are even willing to mention chaos they talk about the climate being on an “attractor”, which is the shape in phase space (climate variables being the coordinates of this many-dimensional space) of where the climate can be.
They then say that while they may not be able to predict exactly where on the attractor the climate is, which is actually the weather, the attractor will give the bounds of this weather, which is the climate. Thus they say that while the weather is unpredictable more than ten days into the future, the climate is not.
This explanation conveniently ignores the fact that there is no way to ever know if a climate model’s attractor is the same as nature’s. When I was at NASA GISS I pointed this out to Dr. Gavin Schmidt, current head of NASA GISS (anointed by former head Dr. James Hansen, the father of global warming) and leading climate change spokesperson.
His response was, “We just have to hope they are on the same attractor”, literally using the word “hope.” They are almost certainly not so a climate model can’t predict nature’s climate.
Moreover, there is no way to ever know what either attractor looks like. Some climate modelers, as a sop to chaos, pretend to know what an attractor looks like, at least a climate model’s, by running “ensembles” — groups of runs of the same climate simulation starting from different initial conditions.
Each run is expensive and time-consuming so there aren’t usually enough to be even statistically significant. They often just average these runs and that is their climate prediction. But this average may not even be possible in the climate system.
Which Is It, “Abrupt Climate Change: Inevitable Surprises” Or Can Climate Be Predicted?
Obviously, it can’t be both. If you are surprised it means you didn’t predict it would happen. And then to call the surprise “inevitable” means the only thing you are certain of is that you can’t predict climate.
I was a contributor to the National Academies book Abrupt Climate Change: Inevitable Surprises. So was Dr. Gavin Schmidt. Unlike Schmidt, I questioned the whole premise but was just a graduate student at the time so I didn’t speak up.
Abrupt climate change involves “tipping points.” The climate is relatively and slowly changing until it reaches a point where it rapidly changes, to an opposite extreme to that where it was originally headed.
For example, it has been theorized by climate scientists that global warming will cause the ice caps to melt and the resulting freshwater will turn off the thermohaline circulation causing an ice age (which the Earth’s current orbital parameters already favor). This was the basis for the movie “The Day After Tomorrow.” (We may need as much greenhouse gas as we can generate.)
For tipping points think of a dice on its edge and which way it rolls. This is even classically unpredictable — an infinitesimal, unknowable difference in conditions could determine which way it tips, which is again just chaos.
Physicists who work with quantum mechanics have already admitted this fundamental unpredictability — it is time for climate modelers to do the same. (Einstein: “God does not play dice with the universe.” Bohr: “Stop telling God what to do.”)
Similarly, some climate modelers study whether climate systems have multiple equilibria — different possible steady-states. If there are multiple equilibria then you can’t predict which equilibrium will occur and thus you can’t predict climate.
Climate Models Were Never Meant For Prediction
When I first started in climate modeling as a graduate student in the early 1990s it was understood that if you ever claimed that climate models could actually predict climate it would be the end of your career — the same as if you proposed perpetual motion or cold fusion.
Climate models were for studying the various processes of climate. You would research a climate process (insolation in my case then), parameterize (approximate) it in program code in a climate model and study its effect on the resulting climate output from the model.
Unfortunately, some scientists who cared more about publicity than climate science, particularly those who had no graduate work in climate science (or chaos) and could never be famous in their own fields, ignored this warning.
This was followed by non-scientists, often failing entertainers, taking over as climate spokespeople. See my article Who Is Qualified To Be A Climate Spokesperson?
If A Climate Model Could Predict Climate Why Would You Need More Than One?
There are numerous climate models and each is extremely expensive. That there are numerous models, that they originally (before comparison) gave significantly different results, and that they are compared, with none hailed as definitive, shows that climate modelers know no model can predict climate, they just want to have their own, for publication and funding advantage.
Climate modelers then say that because most of these models now show global warming that proves global warming. However, this ignores that scientists are all-too-human and don’t want to be outliers — after comparison, they literally tune their climate models (this is easily done) to give results more like the rest of the herd.
Plus they even started with an assumed result (warming), which is well-known in science to skew results toward that assumption.
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