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Old 06-03-2013, 06:01 AM
Elroch Elroch is offline
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Default Re: Data snooping and science

Originally Posted by Michael Reach View Post
Elroch, I was pretty resolved to stay out of discussing the actual science, since, as I said, I don't know much about it. But I am having trouble following what you're saying.
First, I'm not sure what you mean by the "complete certainty" of the physics. Probably you mean that one aspect of the physics, the amount of heating that CO2 would cause other things being equal, is simple physics. But I don't know why you think that should help Dr. Muller's statement, since other things are not equal. The tough part of the job is going to be to figure out what role all the other factors play. In the end, as you mentioned, the size of the feedbacks is a critical issue, with estimated values ranging (near as I can tell) over a factor of six or so, or maybe a factor of two from more recent work. And without the feedbacks, the basic sensitivity to CO2 would be much less concerning.
In any case, I don't think that was what Muller was saying. Obviously, if all he needs is to estimate a single parameter, that he can estimate it with one parameter isn't going to impress most skeptics very much! My impression from the video (and from some comments by his co-worker Steve Mosher elsewhere) is that they found that the best fit to the data was given by fitting the CO2 and dropping all other variables. Even volcanoes, which have an obvious immediate impact, dropped out if you look over a few years span, and he was left with no explanatory variables that helped except CO2.
Anyhow, if that's what he was saying, that's what I was asking: to what extent is he allowed to do that, and to what extent do we say that he's using a lot of hypothesis choices made by others?

"One thing that annoys me is when denialists argue against global warming on the basis of short term data." That's interesting: From a Bayesian point of view, the last decade of data shouldn't "argue against global warming", but it certainly must bring down the estimate of the climate sensitivity to CO2: that's pretty much automatic from Question 20 on the final! How much is going to be an important question. I believe there's a lot of discussion right now about a couple of papers currently submitted by Nic Lewis and some others, where he sharply lowers the sensitivity ranges based on the last decade of data - and others dispute his claims. He also has been complaining about the use of uniform priors in earlier IPCC estimates, so that part of the lecture is really very relevant!
Firstly, it's all physics, and all the physics is known to an unnecessarily high precision. But there are three issues with applying this physics

Firstly, the data we have about the state of the world's climate at any particular time is not perfectly detailed. But it has more detail than is needed for relatively simple outputs.

Secondly, the modelling of physical processes has to be approximate, out of necessity. But this modelling is, as far as I know, entirely physical, in the same way as weather forecasting models (which are vastly more detailed) are entirely physical. For an overview, see

Thirdly, there is the uncertainty in the detail: you can't predict the weather in 6 months, however much computing power you have. But I don't think anyone claims that random fluctuations in the actual weather are going to affect the sorts of quantities (mostly averages) that climate change is about.

So considerations of Bayesians are irrelevant: there is no scope for curve-fitting in physical models, there is only the scope for trying to model physical systems as accurately as your computer and data and physical models will permit. The only room for modification over time is to model the physics more accurately. The nearest to an exception might be the issue of flux correction, but this is a technique that stopped being necessary as supercomputers became more powerful.

[EDIT: I should clarify that this is not a field I have worked in (although I have done a lot of physical modelling and simulation). I can name drop by pointing out that one of the other 9 mathematicians in my year in my college at Cambridge is one of the most senior climate scientists in the UK, Vicky Pope. (A few of her articles for the Guardian are listed at the end) ]
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