We were discussing whether there was internal variability in the climate on a decadal timescale. In order to deduce that any change on such a timescale is due to changes in external forcing, you have to assume or have evidence that internal forcing is negligible on that timescale – you have to have a particular form of null hypothesis. I’ve discussed various reasons for why that’s unlikely to be true, and stated that the only ‘evidence’ I’ve seen presented for it has been graphs that show model results with and without added CO2, for which the ones without were flat. (The models did include natural forcings like volcanoes and solar changes, but according to the model the differences were insignificant.)

This is a crucial plank on which your argument rests. If there may be unquantified spurious trends on a decadal timescale due to internal variation, then performing regression on a 30-year base is no better supported than doing one on 10 years, 60 years, 1 year, or 8,000 years.

Rather than come up with an answer to that, you said that you didn’t think anyone had made the claim that I had attacked, and on which your whole argument relies. Or so I understood. Were you merely objecting that the only forcing I had mentioned in one particular sentence was CO2? If so, I’ll concede the point that I said CO2 as a stand in for the whole collection without making that clear, if you’ll agree that your comment hasn’t in any way answered the essential point of my argument.

And before you jump to the conclusion that I’ve intentionally tried to distort what you said, you should please bear in mind that in a conversation where people are struggling to understand what the other means, and coming from opposite ends of a polarised and somewhat rancorous political spectrum, that genuine misunderstandings are common.

For example, I said “the only evidence I’ve seen presented is that the models come out flat if you don’t add CO2, which is a bit too virtual for my taste.” and you responded with “that is a very long way from being the only evidence that CO2 affects climate.” I was talking about the evidence that it was flat, and you twisted it to mean the evidence it was affected by CO2. You then went on to explain, in what might be seen as a very patronising manner, that the CO2 greenhouse effect was a matter of basic physics, as if I wouldn’t know that. It looks like a strawman argument put up to avoid the issue of the evidence for flatness, and at the same time to portray me as a fool for not being aware of the most basic physical argument that appears in every single presentation of AGW, even those to the youngest of schoolchildren. That, at least, is how somebody could interpret it, if they weren’t feeling generous.

Now I’m not complaining, and I did assume that it was simple misunderstanding. I only put up this explanation in the hopes that you can see how genuinely unintended misunderstanding can easily look like dishonest debating techniques.

I’ve found our exchange interesting, although not particularly fruitful. And it’s been better than a lot of such exchanges I’ve had with AGW believers. But I have noticed that you still have a tendency to treat your opponents as if they were ignorant fools for believing as they do. That sort of rhetorical tactic can work in an environment where most people believe as you do, and you are to some degree playing to the gallery. But here you are on what might be called ‘enemy turf’, and if your purpose is either to persuade, or merely to have a reasonable debate, you should be aware that the psychology of such situations is that belittling people’s views and intellects leads people to fight you rather than listen. It is best that even if criticised yourself, that you contain your answer to the bare facts, without editorial. It works better in the long run. Maybe you’re not bothered by that, or of what people here have come to think of you, and I’ve no personal objection to you using such tactics since it makes our position look far more persuasive in comparison, but perhaps it’s something you’d want to think about.

You say “On a timescale of decades, most of the variation is due to changes in solar activity, CO2 concentrations and aerosol concentrations.” which I took to imply that you thought internal variation was negligible on a decadal timescale. I cited examples of internal variation like the Pacific decadal oscillation that do occur on a decadal timescale in answer to that, and pointed out that with autocorrelated sequences even the noise can occur on arbitrarily large timescales.

Now you say “But I don’t think anyone has said climate variations would be zero without CO2 – far from it.” So which is it? Are internal variations effectively zero on a decadal timescale or not?

“In the absence of all forcing, of course the climate variation would be essentially flat – that’s just Newton’s first law, really.” So now you are claiming it’s flat?

On what basis? What’s the evidence for the claim that, absent changes in forcing, climate would be flat on a decadal timescale? If you think you can argue that from Newton’s first law, I’d like to see it.

BTW, when I say ‘mysterious’ I mean that there are still many mysteries about them. We don’t understand the quantitative (and sometimes qualitative) details. And of course there are feedbacks in the system, but there are negative feedbacks too. What do they all add up to? Nobody knows. For all we know, the total might even be negative, and doubling CO2 could give less than a degree.

You also obviously don’t understand feedback. You must be either ignorant of or in denial of all the evidence that shows that feedbacks exist in our climate system.

No, the latest observations do not show a levelling off. To think that they do, you have to have no understanding of trends and statistics.

Stevo – sorry I misunderstood what you were saying. But I don’t think anyone has said climate variations would be zero without CO2 – far from it. Everyone knows that solar activity changes, that volcanoes erupt, and things like that. Look up papers by Solanki et al for work on how solar variation has been an important driver in the past. In the absence of all forcing, of course the climate variation would be essentially flat – that’s just Newton’s first law, really.

I don’t know why you think feedback effects are mysterious. They’re fairly common sense really – if you melt the polar caps a bit, the Earth’s albedo drops, so more radiation is absorbed. What’s mysterious about that? And as oceans get warmer, they can hold less CO2. No mystery there, surely?

Here‘s a paper about autocorrelation and climate change that you might be interested in.

markm – there is no such thing as ‘recovery from the little ice age’. The climate doesn’t have an equilibrium state that it must return to. It won’t change without being pushed. And climate change over the 20th century is well explained by a combination of rising CO2, variable aerosols and solar activity, and the occasional large volcanic eruption.

Congratulations!

You’re reasonable exchange with Stevo is the first positive contribution that you’ve made to this blog. I actually paid attention to what you said!

When I said “the only evidence I’ve seen presented” I meant the only evidence for the climate being flat. The evidence for claiming that on a timescale of decades, most of the variation is forced and not due to internal variability. I wasn’t talking about evidence that CO2 affects climate, but the claim that nothing else does.

Yes. I already know the very basic physics. Doubling CO2 would, all other things being equal, increase the temperature by about 1.1 C. And the increase from 280 to 380 we saw over the 20th century would increase it by about half that, so we can expect the temperature in 2100 to be about 0.5 C above what it is today as a result of CO2. But all other things are not equal. The modellers posit all sorts of other mysterious effects causing positive feedback that increases this 1.1 C to a variety of numbers ranging from 3 C to 10 C and beyond. And which would incidentally imply that we should have had between 1.5 C and 5 C rise over the 20th century, which they then have to invent more mysterious effects to cancel. Water vapour and aerosols and ocean heat capacity and all that jazz. But we don’t even know from observation the sign of the feedback, let alone that it has the huge values the modellers claim.

But what I’m talking about is a different feature of the models, that if you don’t put in external forcers like AGW or massive solar changes, they come out nearly flat on a decadal timescale. This, it is claimed, is evidence that the climate is naturally flat, and therefore any lumps and bumps in it must be unnatural. But I don’t accept computer models as evidence of flatness in the real world. History begs to differ.

I suspect some of the flatness is due to the way the modellers deal with divergence. Here is some of the output of that climate model the BBC got everyone to run at home. http://www.climateprediction.net/science/thirdresults.php http://www.climateprediction.net/science/secondresults.php What they do is to trim out the obviously crazy stuff and quietly bin it, and then take the spread of the remainder as representative of the uncertainty while they draw a line through the middle of it. And of course if you do that, any variations on a decadal timescale that you might be modelling get cancelled out. It is like taking all those cumulative coin toss graphs, averaging them, and finding the line goes flat. Correct, in a sense, but it isn’t how an actual climate behaves.

Take a monthly temperature series and plot the anomaly for each month against the anomaly of the next month. That is, if you have temperatures a, b, c, d, e, f, … then plot the points (a,b), (b,c), (c,d), (de,e),… You will see that the resulting patch is not circular but elongated along the diagonal. The temperatures are autocorrelated. There are an infinite number of possible mechanisms for autocorrelated random processes (look up ARIMA and ARFIMA processes sometime) and the coin toss experiment is only one of them. (ARIMA(1,1,0) to be precise.) It’s just an easy way to get an intuitive understanding of what utter havoc autocorrelation can play on statistical tests that assume stuff is “independent identically distributed”. It’s not often taught outside postgrad stats and econometrics courses, I only came across it myself later on in my professional life, but it is vitally important for every scientist to know about.