Or behind the curtain, or wherever they’re telling you not to look because it’s messy or distracting. But Willis Eschenbach, a computer programmer with many decades of experience, just did anyway. He obtained the source code for “Model E”, NASA’s own super-intelligent whiz bang climate model and published a report for Net Zero Watch in which he discusses some of the weird kludges, fixes and ad hoc cheats that make it run. After describing some of the more glaring errors Eschenbach notes: “This is what the climate modellers mean when they say that their model is ‘physics-based’. They use the term in the same way Hollywood producers do when they say a movie is ‘based on a true story’”.
The first really weird thing is that the model is written in the ancient programming language Fortran. The reason is that it was first written many decades ago, and it has sprawled in size over the years as more and more pieces get added on instead of the modelers at some point going back and starting from scratch using cleaner assumptions and functions and a more modern coding system. But it’s a dangerous way to program, because as one bit gets added here, another bit over there no longer works right, and ever messier kluges are employed to fix short-run problems at the cost of making the underlying mechanics more and more obscure, ad hoc and opaque even to the programmers.
Eschenbach gives the example of polynyas, pools of meltwater that form on top of the sea ice in polar regions. These objects play an important role in determining how much of the sun’s energy gets reflected back to space rather than warming the surface. But in an earlier version of the model, polynyas could form and remain liquid regardless of how cold the air was. So instead of going back and undertaking a proper fix of the underlying physics, the modelers just added an ad hoc rule limiting how many days the melt pool could form. But in the latest version of the model the crude limit on melt days is gone, replaced by a crude limit on the overall reflectivity regardless of the number of melt days. Why? Well, not because it better fits the physics as we now understand it, that’s for sure.
As for temperature, which you hope these models can get right given their purpose, NASA’s Model E like many climate models sometimes wanders way out into left field and generates temperatures outside any reasonable range. Does that claim sound harsh? Actually it’s what some of the coders themselves wrote as comments right in the code, in the spot where they added a fix to stop the temperature from wandering around so much:
“This routine makes sure that the temperature remains within reasonable bounds during the initialization process. (Sometimes the computed temperature iterated out in left field someplace, *way* outside any reasonable range.) This routine keeps the temp between the maximum and minimum of the boundary temperatures.”
But when you fix a problem like this one by telling the program not to go there even if it wants to, it means you’re ignoring the fact that its representation of the world is obviously wrong in order to convince people its representation of the world is right. Which is cheating.
It also appears in the part that determines wind speed. Same problem, same fix, same warning in the code. It’s what some people mean by “settled science”.
Another problem in climate models is that one part of the model estimates how much energy comes in from the sun and other parts determine how much gets sent back out to space. They are all supposed to agree, but they don’t. Which would be OK except that they can come up with such different numbers that the virtual planet either fries up or turns into an ice ball. Rather than fix whatever the problem is in the underlying representation of climate physics, modelers just take the energy imbalance and spread it all over the globe like icing.
Eschenbach renders the following verdict:
“Bottom line? The current crop of computer climate models (which should really be referred to as ‘climate muddles’) is far from being fit to be used to decide public policy. To verify this, you only need to look at the endless string of bad, failed, crashed-and-burned predictions that they have produced. Pay them no attention. They are not ‘physics-based’ except in the Hollywood sense, and they are far from ready for prime time. Their main use is to add false legitimacy to the unrealistic fears of the programmers.”
Pay no attention to that Mann behind the curtain, or his pals at the computer keyboard, or the digital ravings of their GIGO machines.