This does not mean computer models are not real science. In fact, many phenomena in, for example, biology, chemistry, weather and yes climate are simply too complex to be comprehended by the reductionist approach that works so well for physics: reducing the problem to relatively simple equations or systems of equations. In the future, more “understanding” in science will be the result of computer models, not human understandable equations. As an example of this sort of model, consider that an important factor in determining your credit worthiness (in the credit card market) is the output of a neural network. Nobody has any idea how it makes its recommendations – it just does. The network understands credit risk in a way people do not.

Climate models are weak because, well, they are weather models, and weather models are weak. Basically, they cannot model every “billiard ball” in the game – there are too many molecules around. So they rely on equations that are generalizations. But the equations are coupled in complex, nonlinear fashions. On top of that, many of the coefficients are guestimates – which in the climate world are pretty hard to calibrate.

As one who uses weather models for forecasting, I find it fascinating that the highest resolution models can be very, very wrong just a few hours into the future. For example, the question of whether an isolated thunderstorm will form is often impossible to answer.

These same models (or ones like them) are used to evaluate climate sensitivity to CO2(or other factors). But many important phenomena in weather/climate take a lot longer than a couple of hours to operate – certainly longer than the competent forecasting time of the models. For example, the coupling of the Madden-Julian oscillation to western US precipitation is one that takes many days. Oops… we’ll just have to parameterize that one. The sad thing is that almost everything in the problem is like that.

Also, I consider evolution to be an awfully good hypothesis, but experimentation, in the way some people mean it, has not been possible. Science is not about experimentation, it is about hypothesis formation and refutation. Sometimes an “experiment” provides evidence about the hypothesis. Other times the hypothesis may predict what will be determined about the past. This is certainly true in evolutionary biology (less so in the last decade or two). If your theory says that certain kinds of things happened in the past, and later evidence is found for that, you have the equivalent of experimental evidence.

“It is impossible to speak in such a way that you cannot be misunderstood.” — Karl Popper

LT

I was in the hallway where two senior engineers were being introduced to a new geologist on the staff. After the cordialities were exchanged, the more blunt of the two senior guys said, “I only hire one armed geologists.”

He left it hang for a while, then he continued, “Every time I ask a geologist for an answer, he tells me one thing, and before I can reply, he says, but on the other hand.”

LT: Objection to computer modeling as expressed by climate skeptics is not a red herring.

Anon: Well, then F=ma must be a computer model, because it’s used a gajillion times a day on computers all over the world. What about Navier-Stokes? Is that a “computer model”? Computers are used simply when there are too many numbers to use a calculator. That’s usually because you are trying to apply the fundamental equations, like F=ma, over a non-trivial spatio-temporal domain. etc. etc.

[You left out Reynolds Number, Pitot, Galileo, Torricelli, Mariotte, Pascal, Bernoulli, Euler, et al. You must have been in a hurry. I understand. You're a busy fellow, as you've pointed out.]

LT: The rest of your post is bullshit.

Which it is. You never come back around to telling us why you think the computer modeling is a red herring. All you do is tell us how important computer modelling is, has been, and will probably always be, which is a nonissue. No responsible skeptic that I’ve read in the last four or five years has ever come close to saying what you’re implying [they say], i.e., that the models themselves are the problem. What they are challenging is both the non-critical acceptance of the models by AGW proponents both in the sciences and in the political/entertainment sphere, and the stonewalling, obfuscation and name calling by the “climate scientists” when their methodology and conclusions are criticized.

Read carefully what I first said. I have, and I’ll acknowledge that it could have been fleshed out just a bit so as to it read:

Objection to the uncritical acceptance of the AGW proponents’ computer modeling as expressed by climate skeptics is not a red herring.

Appears to me neither of our statements were adequately clear.

Another guy named Dan seems to have captured the essence where I failed, at least in your case.

Anon – It’s not the use of computer models per se, but how they are used that is the problem.

Thank you, Dan.

And thank you, anon, for sharing with us your impressive c.v. I’ll rest easier tonight knowing science is in such well credentialed hands.

LT

Second, peer-review requires that the author makes a reasonable case for their conclusions. It doesn’t mean that they are “right.”

Third, a reasonable case in math will probably stand forever; in physics, it can get knocked down by replication; in climate modeling (or other modeling), it will be subject to the calibration errors (data and parameters) — some of which are subjective/biased; in humanities, it’s all just opinion.

That said, publication is useful as a means of extending the debate (and getting paid) and providing something for others to work with. Publication is NOT the end of the debate.

If a particle physicist builds a model that states that a particle with certain properties will behave under certain conditions in a manner inconsistent with observation, he either changes the model or discards it all together.

In the “soft sciences” along with climate research, there is a tendency to “re-interpret” observations to bring them into the range that the model would predict. Thus the historical average temperature series for the US gets changed on an anual basis etc.

I have FIRED ALOT of GEOLOGISTS due to EXPENSIVE DRY HOLES!!!!!!

CAN’T FIRED AL GLORE ( WARMING WIZARD!)

GO FIGURE!!!!

Also, here is a link to the DOE SciDAC (Scientific Discovery through Advanced Computing) program. You’ll see climate along with other “hard” sciences, but no social sciences.

Both of these funding programs have “computer modeling” as the basis for most, if not all, of the awards.