The Great OFCOM Swindle

By now you will all have read about the official OFCOM judgement on Durkin's Swindle. Rather than rehash all the details, I will point you to here and here on the blogosphere. This is probably the best news summary and Dave Rado's article is also worth a read. The full Rado et al complaint and commentary is here and OFCOM judgement is here. (although oddly that page does not cover the judgement of "unjust or unfair treament of individuals" which is highlighted here).

Although C4 did get criticised for the unfair way it had treated Sir David King, Prof Carl Wunsch and the IPCC (and will have to publish an apology), they got off remarkably lightly on the question of "materially misleading", due to the way that OFCOM wriggled their way out of making any meaningful judgement. Because it is a "factual" programme rather than merely "news", there is no requirement of "due accuracy" on the broadcaster. The appropriate test for a breach of the code is a rather higher one, that the program must actually mislead "so as to cause harm or offence". Since the science was already settled, no-one will have believed the Swindle, and no policy decisions will be made on it, therefore there is no chance of it materially causing harm. So in summary it seems that (1) OFCOM doesn't care about the factual accuracy precisely because the program is supposedly "factual", and (2) climate science is not "a matter of political or industrial controversy or matter relating to current public policy", thus OFCOM doesn't require the presentation of it to be impartial or balanced (the economics-focussed section of the program did breach this bit of the code, however). It sort of has a valid internal logic in a smugly complacent middle-class sort of way, but leaves me wondering what OFCOM is actually for.

OTOH, in OFCOM's favour, I've not seen any evidence that the Swindle actually did help to convince anyone of anything (other than Durkin's dishonesty).

"Watchdog finds documentary was unfair to scientists but did not mislead viewers"

The Grauniad is reporting that OFCOM is going to censure Channel 4 for Durkin's swindle, on the grounds that it "misrepresented some of the world's leading scientists". Even so, it "did not breach the regulator's broadcasting code". Score 0-1 against the regulator's broadcasting code, in that case.

Despite criticising Durkin for how the IPCC and Sir David King were treated, OFCOM seems to agree with my judgement that Wunsch was not actually badly misrepresented (although I can of course understand him being unhappy about how he was presented). And if Singer had had the sense to correctly attribute Lovelock's comments on "breeding pairs" etc (or report more accurately what David King had actually said) that would have taken the sting out of another of the major complaints, without changing the message substantially.

So it doesn't seem like the complaint has actually resulted in that definitive an outcome, although will have to wait to next week for the official version (and I suspect science correspondents may be harsher on Durkin than the Guardian's media correspondent was). I do hope that scientists who may in the future be tempted to appear in anything related to Martin Durkin and/or his company WAG TV will do a quick google search to find out what a piece of work he is, though.

More on that SST change

As expected, there have been increasing volumes of hot air expended on the blogosphere about this. RC's post seems pretty reasonable as ever and so is this comment they point to. There is probably little point in speculating in too great detail about the implications, but then again, if one is not going to speculate pointlessly on a blog, there seems little point in having one.

Steve McIntyre was quick to present a hypothetical new surface temperature record, based on slowly phasing out buckets over the 2nd half of the century.

This gives a greatly reduced warming trend over the last 50 and even 30 years, which got Roger Pielke very excited. However, even though Steve may be right about the buckets themselves, his analysis (which, to be fair, he did not present as anything authoritative) ignores the fact that SST observations have increasingly come from other sources such as satellites and buoys. (Furthermore, that graph above seems to show a change of 0.3C for the global mean temperature, which is hard to justify since the adjustment under discussion is only 0.3C for the SST measurements made by some ships, albeit most of them.) I happen to have used some satellite SST data in previous research, and on checking the details I see that the Pathfinder AVHRR were flying from late 1981 (there may even have been older missions for all I know, but I would guess not). This fleet of satellites has provided hi-res global coverage on a regular basis from 1985 (and probably something from the few years prior), so although I do not know the details of the global SST analysis it seems inconceivable that bucket measurements from ships played much of a part subsequent to that date. Turning to buoys, Wikipedia tells me that the US National Data Buoy Development Program started in 1967 and the National Data Buoy Center was formed in 1970, so it seems that at least some data was coming from this source back then too (and note that even if the volume of data was quite small, its relative accuracy may make it outweigh a lot of ship measurements).

So I don't know exactly what the charges will be, but I suspect that the graphic here attributed to CRU is a reasonable first guess.


As you should be able to see at a glance (although Roger apparently cannot), the maximum change in the smoothed record shown there is a little short of 0.2C globally, which is just as expected given a maximum change of no more than 0.3C for the ocean (70% of the earth's surface).

So how does this affect the IPCC's latest report? Well, in the Technical Summary, there is a nice figure (Figure TS.6) which gives 25, 50, 100 and 150 year trends. So let's give this a little update shall we?

Actually, I cannot reproduce either that graph or the Independent's one precisely, as I do not know exactly how they did the smoothing, or (in the case of the IPCC) which data set they used. But this seems acceptably close to both (click for larger version):


The original data are the crosses and the blue line (5 year boxcar smooth), with the new smoothed data forming the dotted blue line which trends down more slowly from 1945-1960. The adjustment I used was a linear term which falls from 70%*0.3C in 1946, to 0 in 1960. Obviously I don't claim this is authoritative but I do believe it is more plausible than a number of other graphs I have seen on the intertubes...

The solid straight lines are the trends plotted by the IPCC. The dotted ones are equivalent trends of the adjusted data. With the help of a bit of rounding, the 50 year trend (1956-2005) changes from 0.13 to 0.12C/decade. By cherry-picking the start date to be 1946 I can get a change as large as 20%, from 0.11C/decade to 0.09C/decade. Woohoo. Let the blogorrhea continue...

Update. It certainly looks like the Independent graphic attributed to CRU is smoothed over rather more than 5 years. Roger says it is a 21y binomial filter, and if that is correct then the adjustment presented in that graph there must be just a hand-drawn guess rather than the results of any realistic calculation, since a 21y smooth would smudge out any adjustment over a rather longer interval than indicated. It's even possible that the attribution to CRU is just for the original data, and the adjustment was drawn on by a journalist. So don't take any of this too seriously for now. I would guess that the data analysts may take this opportunity to have another look at the various assumptions underlying the splicing together of different data sources, and by the time they are done there may be a whole bunch of minor adjustments throughout the time series.

Oops

This seems pretty embarrassing for all concerned. Remember that mid-century cooling that people have been desperately fiddling their models to reproduce for years? It now turns out that it was just an artefact of dubious assumptions about measurement bias (at least, a large chunk of it - I haven't seen any official revised global surface temperature data).

It seems like it won't make much difference to climate predictions, although maybe one should expect it to reduce our estimates of both aerosol cooling and climate sensitivity marginally (I haven't read that linked commentary yet, so don't know how much detail they go into). It will also make it easier for the models to simulate the observed climate history. In fact one could almost portray this as another victory for modelling over observations, since the models have always struggled to reproduce this rather surprising dip in temperatures (eg SPM Fig 4). I've asked people about this problem myself in various seminars, and never got much of an answer. It's pretty shocking that such a problem could have been overlooked for so long.

It wasn't overlooked by everyone, actually. But I anticipate that plenty of people will try their best to avoid looking and linking in that particular direction...

Putting Roger out of his misery

OK, we've all had our fun, but perhaps it is time to put an end to it. There's obviously a simple conceptual misunderstanding underlying Roger's attempts at analysis, which some have spotted, but some others don't seem to have so I will try to make it as clear as possible.

The models provided a distribution of predictions about the real-world trend over the 8 years 2000-2007 inclusive. However, we have only one realisation of the real-world trend, even though there are various observational analyses of it. The spread of observational analyses is dependent on observational error and their distribution is (one hopes) roughly centred on the specific instance of the true temperature trend over that one interval, whereas the spread of forecasts depends on the (much larger) natural variability of the system and this distribution is centred on the models' estimate of the underlying forced response. Of course these distributions aren't the same, even in mean let alone width. There is no way they could possibly be expected to be the same (excepting some implausible coincidences). So of course when Roger asks Megan if these distributions differ, it is easy to see that they do. But what is that supposed to show?

People tend to get unreasonably hot under the collar in discussions about climate science, so let's change the scenario to a less charged situation. Roger, please riddle me this:

I have an apple sitting in front of me, mass unknown. I use some complex numerical models make a wild guess and estimate its mass at 100±50g (Gaussian, 2sd). I also have several weighing scales, all of which have independent Gaussian measuring errors of ±5g. I have two questions:

1. If I weight the apple once, what range of observed weights X are consistent with my estimate of 100±50g?

2. If I weigh the apple 100 times with 100 different sets of scales (each set of scales having independent errors of the same magnitude), what range of observed weight distributions are consistent with my estimate for the apple's mass of 100±50g. Hint: the distribution of observed weights can be approximated by the Gaussian form X±5g for some X. I am asking what values for X, the mean of the set of observations, would be consistent with (at the 95% level) my estimate for the true mass.

You can also ask Megan for help, if you like - but if so, please show her my exact words rather than trying to "interpret" them for her as you "interpreted" the question about climate models and observations. You can reassure her that I'm not looking for precise answers to N decimal places to a tricky mathematical problem so much as a understanding of the conceptual difference between the uncertainty in a prediction, and the uncertainty in the measurement of a single instance. It is not a trick question, merely a trivial one.

Or, dressing up the same issue in another format:

If the weather forecast for today says that the temperature should be 20±1C, and the thermometer in my garden says 19.4±0.1C, then I hope we would all agree that the observation is consistent with the forecast. Would that conclusion change if I had 10 thermometers, half of which said 19.4±0.1C and half 19.5±0.1C? Of course, in this case the distribution of observations is clearly seen to be markedly different from the distribution of the forecast. Nevertheless, the true temperature is just as predicted (within the forecast uncertainty). If there is anyone (not just Roger) who thinks that the mean observation of 19.45C is inconsistent with the forecast, please let me know what range of observed temperatures would be consistent.

Roger gets it right!

But only where he says "James is absolutely correct when he says that it would be incorrect to claim that the temperatures observed from 2000-2007 are inconsistent with the IPCC AR4 model predictions. In more direct language, any reasonable analysis would conclude that the observed and modeled temperature trends are consistent." (his bold)

Unfortunately, the bit where he tries cherry picking a shorter interval Jan 2001 - Mar 2008 and claims "there is a strong argument to be made that these distributions are inconsistent with one another" is just as wrong as the nonsense he came up with previously.

Really, I would have thought that if my previous post wasn't clear enough, he could have consulted a numerate undergraduate to explain it to him (or simply asked me about it) rather than just repeating the same stupid errors over and over and over and over again. This isn't politics where you can create your own reality, Roger.

So let's look at the interval Jan 2001-Mar 2008. I say (or rather, IDL's linfit procedure says) the trend for these monthly data from HadCRU is -0.1C/decade, which seems to agree with the value on Roger's graph.

The null distribution over this shorter interval of 7.25 years will be a little broader than the N(0.19,0.21) that I used previously, for exactly the same reason that the 20-year trend distribution is much tighter than the 8-year distribution (averaging out of short-term variability). I can't be bothered trying to calculate it from the data, but N(0.19,0.23) should be a reasonable estimate (based on an assumption of white noise spectrum, which isn't precisely correct but won't be horribly wrong). This adjustment doesn't actually matter for the overall conclusion, but it is important to be aware of it if Roger starts to cherry-pick even shorter intervals.

So, where does -0.1 lie in the null distribution? About 1.26 standard deviations from the mean, well within the 95% interval (which is numerically (-0.27,0.65) in this case). Even if the null hypothesis was true, there would be about a 21% probability of observing data this "extreme". There's nothing remotely unusual about it.

So no, Roger, you are wrong again.

The consistently wrong chronicles

...or, how to perform the most elementary null hypothesis significance tests.

Roger Pielke has been saying some truly bizarre and nonsensical things recently. The pick of the bunch IMO is this post. The underlying question is: Are the models consistent with the observations over the last 8 years?

So Roger takes the ensemble of model outputs (8 year trend as analysed in this RC post), and then plots some observational estimates (about which more later), which clearly lie well inside the 95% range of the model predictions, and apparently without any shame or embarrassment adds the obviously wrong statement:

"one would conclude that UKMET, RSS, and UAH are inconsistent with the models".

Um....no one would not:

Update: OK, there are a number of things wrong with this picture. First, these "Observed temperature trends" stated on the left, calculated by Lucia, are actually per century not per decade, although I think they have been plotted in the right place. When OLS is used on the 8-year trends (to be consistent with the model analysis), the various obs give results of around 0.13 - 0.26C/decade, with my HadCRU analysis actually being at the lower end of this range. Second, the pale blue lines purporting to show "95% spread across model realizations" are in the wrong place. Roger seems to have done a 90% spread (5-95% coverage) which is about 20% too narrow, in terms of the range it implies.

I challenged this obvious absurdity and repeatedly asked him to back it up with a calculation. After a lot of ducking and weaving, about the 30th comment under the post, he eventually admits "I honestly don't know what the proper test is". Isn't thinking about the proper test a prerequisite for confidently asserting that the models fail it? Anyway, I'll walk through it here very slowly for the hard of understanding. I'll use Wilks "Statistical methods in the atmospheric sciences" (I have the 1st edition), and in particular Chapter 5: "Hypothesis testing". It opens:

Formal testing of hypotheses, also know as significance testing, is generally covered extensively in introductory courses in statistics. Accordingly, this chapter will review only the basic concepts behind formal hypothesis tests...[cut]

and then continues with:

5.1.3 The elements of any hypothesis test

Any hypothesis test proceeds according to the following five steps:

1. Identify a test statistic that is appropriate to the data and question at hand.

This is a gimme. Obviously, the question that Roger has posed is about the 8-year trend of observed mean surface temperature. I'm going to use an ordinary least squares (OLS) fit because that is what is already available for the models, and it is also by far the most commonly used method for trend estimation and has well understood properties. For some unstated reason, Roger chose to use Cochrane-Orcutt estimates for the observed data that he plotted in his picture, but I do not know how well that method performs for such a short time series or how it compares to OLS. Anyone who wishes to repeat the analysis using C-O should find it easy enough in principle, they will need to get the raw model output (freely available) and analyse it in that manner. I would bet a large sum of money that this will not change the results qualitatively.

2. Define a null hypothesis.

Easy enough, the null hypothesis H0 here that I wish to test is that the models correctly predict the planetary temperature trend over 2000-2007. If anyone has any other suggestion for what null hypothesis makes sense in this situation, I'm all ears.

3. Define an alternative hypothesis.

"H0 is false". This all seems too easy so far....there must be something scary around the corner.

4. Obtain the null distribution, which is simply the sampling distribution of the test statistic given that the null hypothesis is true.

OK, now the real work - such as it is - starts. First, we have the distribution of trends predicted by the models. As RC have shown, this is well approximated by a Gaussian N(0.19,0.21). (I am going to stick with decadal trends throughout rather than using a mix of time scales to give me less chance of embarassingly dropping factors of 10 as Roger has done in several places in his post. He has also plotted his blue "95%" lines in the wrong place too, but I've got bigger fish to fry.) There are firm theoretical reasons why we should expect a Gaussian to provide a good fit (basically the Central Limit Theorem). This distribution isn't quite what we need, however. The model output (as analysed) uses perfect knowledge of the model temperature, whereas the observed estimate for the planet is calculated from limited observational coverage. In fact, CRU estimate their observational errors at about 0.025 for each year's mean (at one standard deviation). This introduces a small additional uncertainty of about 0.04 on the decadal trend. That is, if the true planetary trend is X, say, then the observational analysis will give us a number in the range [X-0.08,X+0.08] with 95% probability.

Putting that together with the model output, we get the result that if the null hypothesis is true and the models' prediction of N(0.19,0.21) for the true planetary trend is correct, then the sampling distribution for the observed trend should also be N(0.19,0.21). I calculated 0.21 for the standard deviation there by adding the two uncertainties of 0.21 and 0.04 in quadrature (ie squaring, adding, taking the square root). This is the correct formula under the assumption that the observational error is independent of the true planetary temperature, which seems natural enough.

So, as I had guessed in my comments to Roger's post, considering observational uncertainty here has a negligible effect (is rounded off completely), so we could have simply used the existing model spread as the null distribution. Using this approach generally makes such tests stiffer than they should be, but it is often a small effect.

5. Compare the observed test statistic to the null distribution. If the test statistic falls in a sufficiently improbable region of the null distribution, H0 is rejected as too unlikely to have been true given the observed evidence. If the test statistic falls within the range of "ordinary" values described by the null distribution, the test statistic is seen as consistent with H0 which is then not rejected. [my emphasis]

OK, let's have a look at the test statistic. For HADCRU, the least squares trend is....0.11C/decade. That is a simple least squares to the last 8 full year values of these data. (I generally use the variance-adjusted version, on the ground that if they think there is a reason to adjust the variance, I see no reason to presume that this harms their analysis. It doesn't affect the conclusions of course.)

So, where does 0.11 lie in the null distribution N(0.19,0.21)? Just about slap bang in the middle, that's where. OK, it is marginally lower than the mean (by a whole 0.38 standard deviations), but actually closer to the mean than one could generally hope for, even if the null is true. In fact the probability of a sample statistic from the null distribution being worse than the observed test statistic is a whopping 70% (this value being 1 minus the integral of a Gaussian from -0.38 to +0.38 standard deviations)!

So what do we conclude from this?

First, that the data are obviously not inconsistent with the models at the 5% level.

Second...well I leave readers to draw their own conclusions about Roger "I honestly don't know what the proper test is" Pielke.

Are you avin a laff?

Round and round the mulberry bush...

Roger Pielke, 30 April:

there is in fact nothing that can be observed in the climate system that would be inconsistent with climate model predictions. If global cooling over the next few decades is consistent with model predictions, then so too is pretty much anything and everything under the sun.

Me (in the comments):

over the 30 year time frame there will be strong warming

Roger:

I see that you neglected to address my central question

Me:

I explicitly wrote "over the 30 year time frame there will be strong warming" - and actually 20y would be a safe bet too.

Roger:

I see that you have once again avoided addressing this question.

Me here in more detail:

Warming over 30 years is assured, 20 years must be "very likely", 10 years I would certainly say "likely" but that is a bit of a rough estimate.

I could do a detailed calculation about the probability of different trends over the next 30 years, but that's already been done.

Roger:

James, when you write, "Warming over 30 years is assured, 20 years must be "very likely", 10 years I would certainly say "likely" but that is a bit of a rough estimate" you are much closer to what I am looking for. I am asking for somewhat less "roughness" in these estimates, and grounding them more quantitatively than this sort of hand-waving which is a common response.

Me:

you asked for more quantitative estimates, but did you read the link I provided, where such quantitative estimates were explicitly presented 6 years ago?

If, after reading that (and the two papers it refers to) you still have a question then feel free to follow up.

Roger:

If you think that I'm focused on 2020-2030 (the subject of the essay in Nature that you linked to) then you are not really paying attention.

Me:

Roger, you started off with "if global cooling over the next few decades..." (my emphasis) which remains on your blog even after several people have pointed out that it is a gross mischaracterisation of the Keenlyside paper. So I pointed you to explicit probabilistic predictions about the next few decades which are as clear as day about the probability of cooling over that time frame.

Now you say you are not focussed on the next few decades...

If you want shorter term, I'm sure you have already seen the Smith et al Science paper, within which 50% of years post 2009 are predicted to beat the 1998 record. But as you can see, this is still a rather young area of science, and Keenlyside disagree to some extent (although not as strongly as some have portrayed it - I think their 10y mean forecast could still validate even if we see some new records).

Roger again (not in response to me, but bringing up the topic again on his blog):

You can just clear all of this up by answering my original question:

What observations of the climate system to 2020 would be inconsistent (lets say at the 95% level of certainty) with the climate model projections of the IPCC AR4? It is a simple question. use global average surface temps from UKMET as the variable of interest if you'd like, since that is what we've been discussing, or use a different one.

Me, hopefully for the last time:

Stott and Kettleborough estimate that the global mean temperature in the decade 2020–30 will be 0.3–1.3 K greater than in 1990–2000 (5–95% likelihood range)

and

Knutti et al. find that the projected distribution of likely surface warming is independent of the choice of emission scenario for the next several decades; that the probable warming for 2020–30 relative to 1990–2000 is about 0.5–1.1 K (5–95% likelihood range)

(these being direct quotes from the paper I linked to earlier).

As I mentioned back then, I think these forecasts do have some limitations, but since I pointed them out to Roger 10 days ago it is more than a little tendentious of him to repeatedly insist that they do not exist, and furthermore to pretend that he's been met with nothing but dodging and evasion in response to his question about which observations over the next few decades would be inconsistent (at the 5% level) with the model forecasts. The reason why that paper specifically looked at decadal averages over a 30 year interval is because on this time frame the GW signal is clearly visible above natural variability, but its magnitude is not very sensitive to emissions scenarios (within reason). But it is a simple matter of reading off the graphs for anyone who wants a different forecast interval. However, it seems quite clear that Roger is more interested in pretending that the answer has not been provided, than in actually looking at it. He's avin a laff.

Also relevant: Eli Rabett and RC.

Jumping on the betting bandwagon

I have been waiting for the RC take on that Keenlyside et al paper. To be honest I had been wondering if they were going to duck the debate, having quickly decided that they couldn't find anything good to say about it. So I'm pleased to see that in fact they were doing some behind-the-scenes checking with the authors (to make sure that the media coverage was accurate) and have now issued a bold challenge offering to bet against the prediction of "slight cooling relative to 1994-2004 conditions".

No-one who has read my comments will be surprised to hear that I strongly favour the RC side. Indeed I just recently made another bet that is rather more confident of a more significant warming by 2011 (which I don't consider to be a sure thing, but do consider to be in my favour). I see that even William Connolley has been tempted to come back from retirement to get a piece of the action!

Keenlyside and his colleagues can hardly refuse the offer given their confirmation of the reported statements (at least it wold be a humiliating climb-down for them to do so). I hope they will learn a useful lesson - and that other scientists who are tempted to make extravagant claims (in order to get their papers into Nature?) may also think twice about the risk of having their bluff called so publicly. It's one thing making essentially unfalsifiable claims about 100 years of change (since we won't be around to see the results) but quite another to say something meaningful about the next few years!

o noes!

All I do is place a modest bet for some warm temperatures and a socking great big volcano goes and erupts. Well at least I didn't put much money on it.

Actually, it's not all doom and gloom. There are several factors that weigh against it really making too much difference to my probability of winning. First, it is not really that big yet, although it may get worse before it gets better. Second, it is at a fairly high latitude (42S) so the plume may not spread over the tropics where it would have most effect. Third, it is going to be winter down there for the next few months so there isn't much sun to reflect anyway. Fourth, these things usually don't have much effect past the first year, and I'd already basically written off 2008 due to the coolish start it's had. By 2009, let alone 2011, it may well be ancient history.

Probably someone is already running some predictions of the effect it is likely to have. I'd try it myself it I had the necessary tools. Of course it's having plenty of effects right now for the people who actually live there.

There are some impressive pictures here and here.

"What observations would be inconsistent with climate model predictions?"

Roger Pielke keeps on posting the same question, and keeps on ignoring the replies, so rather than just posting it again in his comments I'll write it out in full here.

First, I should make it clear that I don't accept the true/false dichotomy implicit in his question. Is the Newtonian view of gravity "falsified" by relativity? I suppose so, but in practical terms for everyday applications, it does just fine. Is relativity "falsified" by the Pioneer anomaly? Maybe, at some level. I wouldn't like to bet on that one. No-one is going to "falsify" the fact that CO2 absorbs LW radiation - that doesn't make this statement an act of "faith", it simply makes it true.

That said, some observations would strongly modify our views on the impact of this on the Earth's climate. Most obviously, sustained cooling on the multidecadal time scale would greatly change our estimates. (I'm ignoring the theoretical possibility of major external shocks such as meteors, volcanoes, or nuclear winter). Warming over 30 years is assured, 20 years must be "very likely", 10 years I would certainly say "likely" but that is a bit of a rough estimate. Note that despite the press coverage of the Keenlyside et al work, they don't actually predict any cooling in the future (although they do seem to think it cooled from 1990 to 1998)! Of course there are also upper limits to the expected warming trend (of roughly double the central model projections, at the same level of confidence as I've given the warming/cooling threshold). But I've seen presentations which explicitly draw attention to the possibility of ~5y cooling trends even with a strong background warming, so obviously on the very short time scale we can't expect global mean temperatures to tell us anything conclusive or even highly informative. After all, global temperatures decreased by a whopping 0.22C/year only 10 years ago (1998 to 1999) - that's a rate of 22C per century!! Scary ice age is going to kill us all!!! Not.

I'm sure Roger will find some way of not reading or understanding this. After all, I wrote it in the first comment to his post, and then posted it again in direct answer to his question, and he still ignored it (and according to a comment, Gavin said the same thing previously). I could do a detailed calculation about the probability of different trends over the next 30 years, but that's already been done. FWIW, I think there are some problems with the work described in that article, and intend to have a go myself shortly, but I don't expect to see any really large changes - the issues are similar to those in the climate sensitivity stuff I've talked about before, but I expect the impacts to be smaller in the transient case.

Interesting fact in passing: if the 2008 anomaly is merely +0.3C or greater, then the newest 10y trend 1999-2008 will actually get steeper compared to the current last 10y trend (which is already positive, despite starting in 1998). I predict that were this to occur, some people will start looking hard at 11 or 9 year trends :-) Currently 2008 is running a little colder than 0.3, as Jan and Feb were very cold (but still warmer than the 1961-1990 baseline). But the March anomaly is up above 0.4....

Another decadal prediction...

...is appearing in Nature tomorrow, accompanied by some rather odd press (and blog) coverage. The paper itself also seems a little odd to me (but not as odd as the coverage). The authors have nudged sea surface temperatures to observations, which is probably the simplest plausible first step in coupled model initialisation (and I think has been used in seasonal prediction for some time). Mostly, they are looking at regional results (and predictions), especially the North Atlantic, but they also include some global analysis. For this, they are predicting very little change in mean temperature for the next few years, after which the trend will revert strongly upwards. Roger Pielke somehow saw "the world may cool over the next 20 years" which seems comprehensively contradicted by what the paper actually shows in their Fig 4. I've posted a comment on his blog.

Curiously, the global temperature prediction is contained in a graph which also appears to show (confirmed in the supplementary info) that the free-running model integrations actually tracked historical temperatures better than the nudged ones. This does not look like a good sign to me! In fact they only seem to show that their system has some skill in representing the phase of natural oscillations in some areas, and (unless I've missed something) never actually claim that it has any skill at predicting mean global temperatures (hence their use of correlations rather than the more usual RMS errors). They also have a rather odd graph of the IPCC results, which seems to imply that these models predicted a ~0.3C mean rise over the current decade (and the lead author quotes that value in the Telegraph article). I have not read the paper carefully enough to work out how they managed that, since as I just showed yesterday, the IPCC models on average generate a very linear response (and it's just under 0.2C/decade currently). It may be something to do with how they splice the 20th century simulation on to the A1B scenario projection - eg there could be an abrupt change in forcings, since the scenarios originally started in 1990. But anyway, that doesn't seem like a very fair comparison.

I suppose I should interpret this paper as implying that I'm less likely to win my bet than I thought yesterday. It would be biased of me to cling to Smith et al. as support and simply choose to ignore this less convenient one. But I honestly think Smith et al did a better job at demonstrating the value of their method, especially for predicting global temperatures over the 5 year time scale which is most directly relevant to me. It does seem that there is (almost certainly) a strong contradiction between the results, so one of them has to be wrong!

More on the 4-year bet

So, the program went out on Monday (and can be listened to on-line for those who missed it) and IMO they covered the issue very well. In fact the whole program was interesting - I'm a bit embarrassed not to have discovered it earlier. The presenter seems to do a lot of interesting things - he also has his own webpage/blog.

David Whitehouse stated very clearly on the program that he would bet £100 against a new record by 2011, although I've not yet had a reply to the email I sent on Monday. If any reader knows him directly, I'm be grateful for some contact. In the comments to my earlier post, Chris Randles seemed a bit sceptical of my justification for why I think the bet is a good one (and why I think 30% per year is a reasonable estimate for the probability of a new record in 2009-2011), so here's a bit more background. Actually 30% was partly an inverse calculation, "what would the probability have to be to make the bet an attractive one", but I don't think it is overly optimistic, for the following reasons.

First, here is a bit of Fig 10.4 from the recent IPCC report. The left hand half consists of the last 20y of the models' historical 20th century simulations, and the right half is the first 20y of projections under various scenarios. The yellow/orange future is for fixed atmospheric constituents (at year 2000 values) so is not at all realistic, but the other scenarios all show a near-linear response on average.



I drew on the green line by hand, but it has the right slope for the historical trend. The point here is that for all models under all plausible scenarios, the climate response is very close to linear plus natural variability "noise" over this sort of time scale. In fact the models tend to show a modest increase in trend, although I personally would not be too surprised if this does not actually transpire. But over the next 5 years that is not an issue anyway.

This linear response is a well-known property of the system, basically due to thermal inertia and the steady ongoing increase in CO₂. The only real question is, what is the true underlying trend?

Now here's a modified version of the graph I showed last time.



Here, all the blue lines are the even-year trends from 8 to 40 years duration, extrapolated out to 2011 (I just chose even numbers to limit the clutter). Most of these exceed the 1998 record before 2011, some by quite a lot. I've also put dots on the 30y trend line (a rather arbitrary choice, but actually one of the lower trends) just to show that it crosses the 1998 record between 2010 and 2011. Some important details: the residuals have negligible autocorrelation, so it is reasonable to consider each year's anomaly (compared to the trend) as independent. Also, the RMS of the residuals is about 0.08, and the 1998 value is 2.5 standard deviations (a 1% event, if we assume Gaussian residuals, which I would not hang my hat on but it's a reasonable starting point). None of the cold anomalies are that extreme, not even those due to the Pinatubo and El Chichon eruptions. In fact the cold anomaly in 1996 is greater than either of those, with no volcano to explain it. The 2007 cold anomaly is also an entirely unremarkable 0.8 standard deviations, and all 5 years from 2001-2005 were above the trend line. So there is absolutely no evidence of any strange cooling in the recent record - it's just that 1998 was abnormally warm. Using a conservative "underlying" temperature anomaly of 0.5 (on that scale) over the interval 2009-2011, we only need a further 0.026 due to natural variability - about 0.3 standard deviations, a 40% event - to break the old record. So that makes my 30% guesstimate seem a touch pessimistic. Of course the historical trend may be somewhat "contaminated" by some natural variability or other forcings. But this may work either way, it arguably increases the uncertainty a bit but should not bias the results significantly (in fact an increase in uncertainty for the trend in future temperatures would make the odds closer to 50% for each year, which is better for me).

Finally, this is from Smith et al which I talked about earlier. I've added on a couple of lines as guides.


The green one is just the trend, extrapolated (again positioned by hand but the slope is right). This plot uses seasonal anomalies so the link to annual average is not perfect, but it should be good enough. Their own model forecast (white line with red shading) exceeds the old record from 2008 onwards, with high confidence. In fact their paper contains the explicit statement that "at least half of the years after 2009 are predicted to be warmer than 1998, the warmest year currently on record." Actually on re-reading it that phrase is slightly ambiguous, I suspect they mean that each year from 2009 will beat the old record with probability 50% or more (obviously if you run out far enough into the future then the vast majority of years will break the old record). So according to that statement, I've got a 1-0.5³ = 87.5% chance of winning.

Has global warming stopped?

This has been done to death all over the blogosphere (eg here, here and here), so I can hardly bring myself to post about it. However, I do have one minor contribution to make.

First, the basics. Most of you will have noticed that various sceptics have been crawling out from under stones with variations on "global warming stopped in 1998". Of course, the temperature in 1998 was exceptionally hot, due to the strongest El Nino on record. And according to HadCRUT, we haven't quite exceeded that temperature yet (although according to the NASA/GISS analysis, 2005 just pipped it).

Here is the HadCRUT surface temperature record, with 30 consecutive 10-year straight line fits overplotted in blue. Note how the last of these, 1998-2007, still has a positive trend despite starting right at that cherry-picked high point. However, there have been 3 different 10y intervals with lower trends even during this period, with the more recent one covering 1987-1996. That does include the 1992 Pinatubo eruption, but even correcting for that would still leave it no higher than the 1998-2007 trend. Anyway, global warming can hardly be be described as having stopped since 1998 when the trend starting in that year remains positive.

One of the sceptics who has waffled on about global warming having stopped is is a person called David Whitehouse, who I must admit I'd not heard of prior to that linked article. Mark Lynas has written a perfectly adequate rebuttal, so we don't need to dwell on the argument any longer. But thanks to "More or Less" (today at 16:30 on Radio 4, I just discovered) I may have a 100UKP bet with David that there will be a new record temperature by 2011 at the latest. As I said in the interview (whether or not it ends up on the cutting room floor), I don't think this is a sure win for me, but I do think that the odds are clearly in my favour. Even writing off 2008 (since it's started a bit cold), that leaves 3 more years, and if each one has only an independent 30% chance of beating the old record, then that gives me a 0.7³= 35% chance of losing and therefore 65% chance of winning. That's without any careful analysis of whether an El Nino is likely to turn up (surely the next decent-sized event will result in a new record), just from eyeballing the graph. The Smith et al Science paper puts the odds better than that, I think.

Weitzman's Dismal Theorem again

Via John Fleck, I see that Marty Weitzman's manuscript is getting more air-time. It has changed a lot since I previously wrote about it, but my fundamental criticism remains unchanged.

You have to read through about 15 pages of background and overview to get to it, but the crux of the argument is as follows. Marty describes the situation as if climate sensitivity S "has a pdf" of unknown width, and our process of learning about the width of its pdf is akin to drawing samples from "the pdf of S". In this case, our estimate for the next sample from the pdf will be a long-tailed pdf.

However, I think that S is best considered as an unknown constant, and we learn about S by making imprecise observations of it. In this case, our pdf for S (and our next observation) may or may not have long tails, depending on the nature of the observations and their errors.

This distinction is not a purely semantic one, but is fundamental to the whole process of estimation - ie, are we estimating the (finite but unknown) width of a pdf, or the location of a parameter? I think that basically all of the climate science literature follows the latter point of view (there is some oddball stuff that is sufficiently ambiguous that it's not clear what the authors intend). To be perfectly honest, I don't even know what it might mean to say that "S has a pdf" from which we draw samples. Drawing samples from a pdf is an inherently frequentist construct. In my worldview, we can treat observational error (including natural variability) as a pdf from which we sample, because we can in principle make more observations. But I don't see at all how we can sample from "the pdf of S". The fact that we will never know S precisely, and thus any estimate of S will always take the form of a pdf, is not the same thing at all. This latter pdf is "my pdf of S" and is fundamentally attached to me, not S. Any future observations that are taken will not be influenced by my beliefs about S - the thermometer can't tell who is reading it and change its output accordingly!

Some pedants may argue (correctly) that Bayesians should only really care about observations, and that the concept of a probabilistic estimate of a non-observable parameter doesn't really make much sense anyway. While that may be technically true, it's a dodge that does not materially alter things. Bernardo and Smith give this attitude short shrift in their famous tome:

However, as we noted on many occasions in Chapter 4, if we proceed purely formally, from an operationalist standpoint it is not at all clear, at first sight, how we should interpret "beliefs about parameters" as represented by p(theta) and p(theta|x), or even whether such "beliefs" have any intrinsic interest. We also answered these questions on many occasions in Chapter 4, by noting that, in all the forms of predictive model representations we considered, the parameters had interpretations as strong law limits of (appropriate functions of) observables.[...]
Inference about parameters is thus seen to be a limiting form of predictive inference about observables. [their emphasis]

As far as I can tell, nothing in Marty's basic argument is specific to climate science and climate sensitivity. If he is correct that S naturally has a long tail, then his argument appears to apply equally to all Bayesian estimates of all unknown parameters in all fields of science. I find this a priori unlikely.

I've had a frustrating time trying to debate this with Marty, and am still unclear at which point he parts company with my argument. He certainly seems to agree that the two viewpoints about the nature of S are fundamentally incompatible and that his argument rests on taking his particular approach. I've tried to get Andrew Gelman to read and comment on this manuscript, so far to no avail (mind you he seems to have gone off Bayesian statistics recently). I'd also be interested in hearing the views of any other people who really do know about Bayesian statistics.

Blair - which project?

Not content with being "Middle East Envoy" (isn't that the international equivalent of Minister for N. Ireland, the job that no-one wants?) and bible bashing somewhere in Redneckistan, Blair is now going to deal with global warming. He says:

"At the big G8 summit of last year everybody agreed that climate change is a serious problem, everybody agreed we need a new global deal once the Kyoto Protocol expires in 2012.

"And everybody agreed that everybody should be part of it - including America and China.

"What this means is that there is a consensus now right across the world that we need a new global deal and at the heart of it there has got to be a substantial cut in emissions."

With such profound wisdom and inspiring rhetoric, he surely cannot fail. He's supposed to be reducing hot air, not adding to it.

Another bet on global warming

I'm not sure what prompted it...but I'm all for people taking money off sceptics. Full details here.

Initially ridiculed by many scientists as new age nonsense, today that theory forms the basis of almost all climate science.

A small prize (OK, absolutely nothing except your e-immortality assured in a blog comment) for anyone who can identify the subject of that sentence. Small hint: you won't find it in the IPCC report (not that I've searched the text, actually).

Lentil-munching sandal-wearing Grauniad readers need not apply (even if they haven't read it yet, cos being lentil-munching sandal-wearing Garudina readers they will instinctively know the answer anyway :-) ).

Too crap to publish or too hot to handle?

No, don't answer that :-)

By now probably many of you will have seen the discussion regarding this manuscript. Roger Pielke Snr covers the story here and Fergus has added some commentary here and here. For those of you who are interested in how such an odd triple came to co-author the paper, I'll go into that at the bottom. But first to flesh in some of the details of the submission process:

We first sent it to EOS for their Forum section, which as Roger says, it seems well suited for. Note that this is not a formally peer-reviewed publication in the way that most academic journals are - it is a newspaper, not a research journal (their own choice of words). The manuscript sat on the editor's desk for an astonishing 4 months, and Fergus' occasional polite enquiries were fobbed off rather abruptly, until eventually we got a brief rejection email from Fred Spillhaus on the grounds that they wanted to focus only on science, not opinions (it took him 4 months to work out that it was an opinion poll?). He has not replied to any further requests for clarification as to how he squares this explanation with the stated policy:

Forum contains thought-provoking contributions expected to stimulate further discussion, within the newspaper or as part of Eos Online Discussions. Appropriate Forum topics include current or proposed science policy, discussion related to current research in our fields especially scientific controversies, the relationship of our science to society, or practices that affect our fields, science in general, or AGU as an organization. Commentary solely on the science reported in research journals is not appropriate. [my italics]

But with all emails to him simply vanishing into a black hole, it soon became clear there was no point in pursuing that route any further. Anyway, by this time the survey results had been spotted by some sharp-eyed journalists, and it was getting mentioned in various places (such as here and here). So Fergus then approached the Nature Climate Feedback blog, asking if they were interested. Olive Heffernan replied that they weren't open to guest bloggers, but that he should send it to Nature Precedings and after it had appeared there she could write about it herself.

Nature Precedings is basically a non peer-reviewed preprint service (maybe a rival to the Arxiv?) that merely screens for "relevance and quality". So it was rather a surprise to get a one-line rejection that they were "unable to post your document at this time". The email was anonymous and the author(s) did not explain whether it was because they considered the manuscript irrelevant, or rather than it was too poor quality, or both. Only a minuscule proportion of scientific papers get mentioned in the press, and as I've mentioned this has been picked up in a few places despite having no PR, so it is apparently relevant to some. Obviously I'm biased but the quality of the work and presentation seems well up there with the typical middle-of-the-road conference presentation/poster type of thing (remember we aren't talking high-impact peer-reviewed journals here, just a preprint server).

So it seems that no-one wants to publish it, and no-one wants to say why...with Fergus moving on to other things, it seems like we are at a dead end.

As for my participation in this:

The first I heard about it was an email from Fergus (who I know via his blogging, but not otherwise) asking for comments on his proposed poll. I was generally supportive of the idea and offered some suggestions on the questions and format. I also participated in the poll (FWIW I was a 5: although I can see some arguments leaning towards 4 and 6, they are IMO not strong enough to justify actually choosing one of these options, even as a half point). Later on, he sent me the manuscript again asking for comments, and I suggested some edits. It was around this point that the question of co-authorship was mentioned, and although my contribution had been rather minor the other two seemed keen to include me and I was happy to accept. I have certainly known co-authors do less work (though not on papers where I was first author)!

One can always quibble over details of the wording, but IMO the questions are clear enough, the set of scientists polled is very reasonable and carefully controlled (due entirely to Fergus' hard work) and the results are written up fairly and accurately. Indeed I think it stands in striking contrast with the previous survey of Bray and von Storch, where the questions were more ambiguous (how much do you agree with the sentence "Climate change is mostly the result of anthropogenic causes"?) and the survey was open to anyone who found out about it, including the entire readership of the "climate sceptics" mailing list. Of course the main weakness is in the response rate of ~10%: that leaves open the possibility that the 90% non-responders were either all firmly suportive of the IPCC and saw the poll as a bit of irresponsible trouble-making that didn't justify a response, or all so thoroughly alienated and marginalised by the IPCC that they don't have the energy to grumble about it. Personally, I think the first of these is much closer to the truth, but it seems we will never know for sure. Of course, all surveys suffer from this problem to some extent. I bet all the current polls on Clinton vs Obama have enough refusals to completely dominate the result, were they all to end up on one side of the fence. Yet you don't see reports saying "Clinton 22%, Obama 24%, and the other 54% slammed the phone down".

Just do it

This story has has surprisingly little coverage IMO, considering how significant it could be:

"The [Japanese] government will aim for 30 percent of all households to have solar panels installed by 2030"

That's 40 million people. Japan is already one of the world-leaders in this area, at about 1% household coverage. 30% is a lot. Japan is blessed with a lot of sun, but is otherwise short of energy resources. Their nuclear power industry is large but the climate for that isn't great, so the country is heavily reliant on imported oil and likely to remain so for some time. We are also right at the limit of generation capacity here, with official Govt advice (eg on air-con use) aimed at cutting peak demand in the summer. So obviously promoting solar power could brings substantial benefits both in energy security, and avoiding new power station construction. Of course the massive cash injection into research will also cement Japan's position as the world's leading producer. I'm not sure if I've written it before, but I've long thought that one of the best reasons for increased investment in renewable technology is to get at the forefront of the technological advances. It hardly takes a genius to see which way the wind is blowing on this in the medium term.

IMO spinning this policy as primarily a global-warming issue is probably as much political convenience as hard reality. The Japanese happily pay massively inflated food prices on the grounds of food security (probably that's got a lot to do with buying the support of the agricultural sector), so it is hard to see them objecting at support for energy security too, if it was presented in those terms. But doing something about emissions certainly makes you one of the "good guys" internationally.

Either way, I hope it's the sort of action that people at all positions in the spectrum can agree is a good thing. OK, maybe hard-line libertarians could argue that the Govt spending taxpayers' money is less efficient than the private sector doing it by themselves. But compared to (say) wasting trillions of dollars on an unwinnable war in the Middle East in the vain hope of securing a couple more decades of affordable oil, it's hard to argue that the Japanese approach to energy policy is worse!