Proof is for mathematical theorems and alcoholic beverages. It’s not for science.
The WUWT post links to an article on the Heartland Institute website called Michael Mann redefines science which is critical of what Michael Mann has said. As already pointed out elsewhere (Open Mind – Michael Mann understands science) Michael Mann is essentially correct.
Science doesn’t really work the way that some think. Scientists don’t simply propose theories or hypotheses that can be tested. Typically, scientists are using well-tested theories to understand the world around us. Given that this has been discussed elsewhere, I thought I would discuss something related that I’ve been thinking about recently. This is the issue of falsifiability, an idea attributed to Karl Popper. The basic argument is that something is only scientific if it can be falsified. This, however, is not how scientists think and isn’t really how science works today. Let me try and illustrate this using what Tamino used in his post. Before I start, however, let me make it clear that I’m not an expert at the philosophy of science and I’m sure there are many who could come here and out-philosophize me. These are my thoughts as an active scientists.
So, Newton proposed what is now called Newton’s Law of Universal Gravitation. He surmised that the force, F, between two bodies of mass M1 and M2, a distance R apart was F = G M1 M2 / R2, where G is the gravitational constant. So, how did we test this? Well, as far as I’m aware people did experiments that actually measured the force between two masses. You could suggest that they framed this as an expectation that no force would be measured, but once they’d shown the force existed, experiments were carried out to determine the value of the gravitational constant.
However, there are at least two problems with Newton’s Law of Universal Gravitation. One is that it assumes the force is transmitted instantly (or, rather, it doesn’t address how the force is transmitted). Einstein’s theory of Special Relativity tells us that nothing can travel faster than the speed of light. Furthermore, observations tell us that Mercury precesses faster in its orbit around the Sun that it should if only Newton’s Law of Gravity applied. Both of these problems were solved by Einstein’s Theory of General Relativity which suggests that gravity is actually a manifestation of the curvature of spacetime (which is curved in the presence of mass), rather than some kind of invisible, instantaneous force.
So, there you go. Newton’s Law of Universal Gravitation has been falsified. We should stop using it; right? No, it works extremely well in most circumstances where we want to consider the influence of gravity. There are some circumstances where it doesn’t work, but as long as we understand where and when, we can add suitable corrections or use the full theory of General Relativity. So, we have a theory that’s been falsified that we still use. Let me take this analogy one step further though.
Imagine we want to try and understand the formation and evolution of the planets in our own Solar System. Once the Sun has finished forming, it should be surrounded by a disc of asteroid-like bodies that collide and grow to form the planets (there’s some gas involved in the formation of the outer planets, but let’s ignore that for now). One can set up a simulation that puts a large number of asteroid-like bodies in orbit around the young sun, and run this forward in time. The evolution will be determined, largely by gravity. However, the chances that you’ll end up with a final system that matches our own is vanishingly small. What does this mean? Do we claim that something’s been falsified? If so, what? It can’t be Newton’s Laws because the model was built on these laws, so the model might depend on the laws, but the laws don’t depend on the model. Has the model been falsified? Well, its results might not match our reality, but that’s not the same as the model having been falsified.
So, what might we conclude from such a situation? There are a large number of possibilities. Maybe the initial conditions weren’t suitable. Maybe some physics has been left out. Understanding why the model results differ from reality provides evidence about the system, so even if the model is “wrong” doesn’t mean that it has no value. Also, maybe the system is inherently chaotic? If so, then the model isn’t actually wrong. It has simply produced a different reality to the reality that we observe. Understanding such a system would then require a large number of simulations to determine if our Solar System is a possible outcome and to determine the likelihood of such an outcome. So the basic point I’m trying to make is that applying falsifiability to a model doesn’t really make sense. It is neither a theory nor a hypothesis. Also, just because a model result doesn’t match our observed reality doesn’t necessarily make it wrong or valueless.
So, how does this apply to climate science. Well global climate models are simply models that are based on fundamental, well-tested, well-founded science. Just because the climate models do not produce results that match our observed reality doesn’t mean that something’s been falsified. You could argue that even if this is true, the model is still wrong. Well, if your goal was to exactly match our observed reality then that may be true, but such a goal – given the complexity of the system – is probably completely unrealistic. It could be that the model is ignoring something important and so, in some sense, is wrong. It could, however, be that it’s not possible to include some aspects accurately (some natural variability, for example) or it could be – as it almost certainly is – that the models are inherently chaotic.
Hence using climate models to understand the future evolution of our climate requires a large number of simulations so that we can use them to determine the most likely outcome and the range of possible outcomes. That some short-term variations are very difficult to model also means that such ensembles will tend to smooth out short-term variations and enhance any long-term trends (which is what we’re essentially interested in). So, that the model results don’t precisely match our observed reality doesn’t mean the models have been falsified, nor does it mean that they are simply wrong. The results still provide information about the future evolution of our climate. So, I’m suggesting that applying falsifiability to global climate models doesn’t really make sense. Additionally, just because the model results don’t precisely match our observed reality doesn’t mean that they’re wrong. You need to understand something about how these models work and also how likely it is that such models could precisely match our observed reality. Judging them simply on how well they match our observed reality is not really enough.
Really, the people who should be judging the evidence provided by these models should be the climate scientists themselves. They understand the models and their limitations. They know what’s included and what isn’t and the likely influence of what might have been left out. I know that it’s going to take a lot for some to trust what climate scientists say, but I really can’t see an alternative. Trusting those who think we should use the philosophy of science to determine the merits of global climate models, rather than trusting those who actually understand the models, just seems like the wrong thing to do.