Which is it, “Abrupt Climate Change: Inevitable Surprises” or can climate be predicted?
Written by Duane Thresher PhD, Climate Expert
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 (Duane Thresher) was a contributor to the National Academy book “Abrupt Climate Change: Inevitable Surprises”. So was Dr. Gavin Schmidt, leading global warming spokesperson and current head of NASA GISS (anointed by former head Dr. James Hansen, father of global warming). Unlike Schmidt, I questioned the whole premise but was just a graduate student at the time so didn’t speak up.
Abrupt climate change involves “tipping points”. The climate is relatively 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”.
For tipping points think of a die 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 steady-state results based on different initial conditions (even though chaos theory already proves this will be the case, as do simulations). If there are multiple equilibria based on unknowable initial conditions, then you can’t predict which equilibrium will occur and thus you can’t predict climate.
Chaos trumps statistics.
Some climate modelers try to pretend their way around chaos’s fundamental implications by running “ensembles” — groups of runs of the same climate simulation starting from different initial conditions. The results of each run are invariably different so the modelers just average the results of these runs and pretend that is their one prediction. But this average may not even be possible in the climate system and which of the runs will actually be the case, if any? They also do other statistics on these runs but each run is expensive and time-consuming so there are usually only a handful of runs whereas n = 30 is the rule of thumb for statistical significance. Most importantly, they have no real-world statistics to use because there is only one Earth.
Climate models were never meant to be used for prediction.
When I first started in climate modeling as a graduate student in the early 1990’s 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 gave significantly different results (as chaos theory proves they should), 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 — they literally tuned 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.
Read more at columbia-phd.org
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