I have been intrigued by the frequent postings over at Real Climate in defense of the predictive ability of climate models. The subtext of course is political – specifically that criticisms of climate models are an unwarranted basis for criticizing climate policies that are justified or defended in terms of the results of climate models. But this defensive stance risks turning climate modeling from a scientific endeavor to a pseudo-scientific exercise in the politics of climate change.


In a post now up, Real Climate explains that cooling of Antarctica is consistent with the predictions of climate models:

A cold Antarctica and Southern Ocean do not contradict our models of global warming.

And we have learned from Real Climate that all possible temperature trends of 8 years in length are consistent with climate models, so too are just about any possible observed temperature trends in the tropics, so too is a broad range of behavior of mid-latitude storms, as is the behavior of tropical sea surface temperatures, so too is a wide range of behaviors of the tropical climate, including ENSO events, and the list goes on.

In fact, there are an infinite number of things that are not inconsistent with the predictions of climate models (or if you prefer, conditional projections). This is one reason why a central element of the scientific method focuses on the falsifiability of hypotheses. According to Wikipedia (emphasis added):

Falsifiability (or refutability or testability) is the logical possibility that an assertion can be shown false by an observation or a physical experiment. That something is “falsifiable” does not mean it is false; rather, it means that it is capable of being criticized by observational reports. Falsifiability is an important concept in science and the philosophy of science. Some philosophers and scientists, most notably Karl Popper, have asserted that a hypothesis, proposition or theory is scientific only if it is falsifiable.

Are climate models falsifiable?

I am not sure. Over at Real Climate I asked the following question on its current thread:

There are a vast number of behaviors of the climate system that are consistent with climate model predictions, along the lines of your conclusion:

“A cold Antarctica and Southern Ocean do not contradict our models of global warming.”

I have asked many times and never received an answer here: What behavior of the climate system would contradict models of global warming? Specifically what behavior of what variables over what time scales? This should be a simple question to answer.

Thanks!

As often is the case, Real Climate lets their commenters provide the easy answers to difficult questions. Here are a few choice responses that Real Climate viewed as contributing to the scientific discussion:

If Pielke wants to contribute constructively to this area of science, he should become a climate modeler himself and discuss such questions in the scientific literature. Otherwise, unless he can present some strong reason for doubting the competence or objectivity of people who do such work, he should listen to people who do work in the area.

. . .
Roger, your question is rather broad and vague. What aspect of the science are you seeking to falsify? See, that is precisely the problem when you have a theory that draws support from such a broad range of phenomena and studies as does the current theory of climate. It is rather like saying, “How would we falsify the theory of evolution?” When a theory has made many predictions and explained many diverse phenomena, it is quite difficult to falsify as a whole. You may be able to look at pieces of it and add to the understanding. Climate science is quite a mature field; future revolutions are quite unlikely. Changes will come but will likely be incremental. It is very hard to envision a development that would significantly alter our understanding of greenhouse forcing unless our whole understanding of climate is radically wrong, and that seems unlikely.

The good news is that there are a range of serious scholars working on the predictive skill of climate models. And there are some folks, myself included, who think that climate models are largely of exploratory or heuristic value, rather than predictive (or consolidative). (And perhaps a post on why this distinction is of crucial importantce may be a good idea here.) But you won’t hear about them at Real Climate.

Once you start playing the “consistent with” or “not inconsistent with” game, you have firmly placed yourself into a Popperian view of models as hypotheses to be falsified. And out of fear that legitimate efforts at falsifiability will be used as ammunition by skeptics (and make no mistake, they will) in the politics of climate change, issues of falsification are simply ignored or avoided. A defensive posture is adopted instead. And as Naomi Oreskes and colleagues have observed, this is a good way to mislead with models.

One of the risks of playing the politics game through science is that you risk turning your science – or at least impressions of it – into pseudo-science. If policy makers and the public begin to believe that climate models are truth machines — i.e., nothing that has been, will be, or could be observed could possibly contradict what they say — then a loss of credibility is sure to follow at some point when experience shows them not to be (and they are not). This doesn’t mean that humans don’t affect the climate or that we shouldn’t be taking aggressive action, only that accurate prediction of the future is really difficult. (For the new reader I am an advocate for strong action on both adaptation and mitigation, despite what you might read in the comments at RC.)

So beware the “consistent with” game being played with climate models by activist scientists, it is every bit as misleading as the worst arguments offered by climate skeptics and a distraction from the challenge of effective policy making on climate change.

For Further Reading:

Pielke, Jr., R.A., 2003: The role of models in prediction for decision, Chapter 7, pp. 113-137 in C. Canham and W. Lauenroth (eds.), Understanding Ecosystems: The Role of Quantitative Models in Observations, Synthesis, and Prediction, Princeton University Press, Princeton, N.J. (PDF)

Sarewitz, D., R.A. Pielke, Jr., and R. Byerly, Jr., (eds.) 2000: Prediction: Science, decision making and the future of nature, Island Press, Washington, DC.