Willis Eschenbach takes a nostalgic trip down memory lane that sounds like a hike through Satan’s domain to most of us. Either because it’s about computer programming or because it’s about computer programming putting punch cards into something with ring-shaped wired magnets bulging out the back. So he dropped out of college and became… a programmer. With a TSR-80. Who later fixed Apples in Fiji. Point being, he’s written thousands of programs, has vast experience with computers and their strengths and weaknesses and is exactly the kind of informed outsider who provides a useful check on the buddy system known as “the science”. Especially its hypnotic fixation on computer models whose actual performance is highly suspicious.
For instance “A computer model is nothing more than a physical realization of the beliefs, understandings, wrong ideas, and misunderstandings of whoever wrote the model. Therefore, the results it produces are going to support, bear out, and instantiate the programmer’s beliefs, understandings, wrong ideas, and misunderstandings. All that the computer does is make those under- and misunder-standings look official and reasonable. Oh, and make mistakes really, really fast. Been there, done that.”
Scary, huh? Well, yes. Especially because it’s bolstered by a side-splitting anecdote involving Enrico Fermi, Freeman Dyson and pseudoscalar meson theory. But it has a serious point: To illustrate the crucial point that once computer models have a significant number of tweakable “parameters” they become a giant mass of bailing wire compared to which Eschenbach’s old CDC 3300 looks like something out of Star Trek. Having given an eager young Dyson a bit of a smackdown on his graphs, Fermi asked how many parameters they used and was told four. “He said, ‘I remember my friend Johnny von Neumann used to say, with four parameters I can fit an elephant, and with five I can make him wiggle his trunk.’” Tweaking models isn’t improving the science. It’s jiggery-pokery.
As for the uncredentialled alarmists sneering at uncredentialled skeptics, yes, Eschenbach has exactly one college credit in computer programming. Which will lead a lot of people who wouldn’t know what to do if a C:> prompt appeared to say he’s not a climate scientist. But he does know that the illusion of knowledge is more dangerous than pure ignorance. And the illusion is what we have with all those fancy models.
In his words, “The climate is arguably the most complex system that humans have tried to model. It has no less than six major subsystems—the ocean, atmosphere, lithosphere, cryosphere, biosphere, and electrosphere. None of these subsystems is well understood on its own, and we have only spotty, gap-filled rough measurements of each of them. Each of them has its own internal cycles, mechanisms, phenomena, resonances, and feedbacks. Each one of the subsystems interacts with every one of the others. There are important phenomena occurring at all time scales from nanoseconds to millions of years, and at all spatial scales from nanometers to planet-wide. Finally, there are both internal and external forcings of unknown extent and effect. For example, how does the solar wind affect the biosphere? Not only that, but we’ve only been at the project for a few decades. Our models are … well … to be generous I’d call them Tinkertoy representations of real-world complexity.”
Eschenbach ... The voice of experience.
"... the illusion of knowledge is more dangerous than pure ignorance...", i.e. a little knowledge can be a dangerous thing. The "parameters" that provide all those wonderful extra degrees of freedom in the modeling of a system we (in the engineering world) often affectionately call "fudge factors". Fudge factors are your "friend" until the boss finds out. Each additional fudge factor increases the system complexity geometrically and it becomes a Monte Carlo nightmare, dramatically compounded by the existence of a multitude of nonlinear feedback process loops within loops across loops... etc. It would give Mandelbrot convulsions. FF's are more frequently the preferred tool of government yes-men statisticians but seem to find a home in any industry dealing with fuzzy or gooey, somewhat or highly unpredictable numbers being the result of the inevitably imperfect/incomplete information borne of stochastic processes. Madame with the crystal ball could do just as well as the climate models being used today. Calling them tinker toys is, in my view, perhaps a little too generous. It is appalling that people in positions of power and authority could be so easily led astray... but I guess they see what they want to see... and their refusal to acknowledge the serious flaws is a reflection on their own conceit.