UK leads the world

I’m happy to say that in one respect at least the UK leads the world: the proportion of the U15’s having sex. According to UNICEF we storm ahead with 38%, way ahead of our nearest rivals the repressed Swedes (figure 5.2d). We also do best at getting drunk, too (5.2b), though we only just beat the sober Finns.

Of course, as far as the report goes, these count as negatives not positives. But how do the children count it?

Figure 4 time (the data strikes back)

I thought I’d expand a bit more on why Svensmarks figure 4 is unacceptable (fig 4 of arXiv; fig 6 in Cosmoclimatology: a new theory emerges). Bear in mind that there is more wrong in the article than just this, though! The fig is:


I’m arguing about the lower line, which purports to be a 90-64S average. This is sourced to: (90-64S zonal mean) and thats a perfectly reputable source. However, not one to be used blindly, as S does. You have to wonder about the data quality. And even a cursory think would lead you to wonder how much early data there is in there.

One hint is that the early data is more variable. If you look closely you can see this in S’s fig. If you draw the raw data its more obvious; and if you take the standard deviation its 1 oC before 1957 and 0.4 after. Which is because there are a whole pile of extra stations available after 1957 which smooths things out. The table referenced says it also uses HadISST1 for SSTs in the early period, and it says its a land-ocean mean. But that isn’t consistent with the change in variability (there is an other table,, which only has the stations in. But the differences between that and the former, for 90-64S, is very small).

A good source of temperature data is the BAS READER project. A quick glance shows only Orcadas in the early years in the correct region (and even thats a bit wrong, since Orcadas is only 60 S; maybe GISS is taking 5 degree radius-of-influence to include it S of 64S?).

In fact, I can demonstrate that the early data *is* pure Orcadas by plotting it:


Black: GISS data. Blue: Orcadas station data. Note that GISS are anomalies so I’ve adjusted them vertically to fit (by 3.6 oC, if you care). The early fit is so good its clear that the GISS data *is* pure Orcadas. Which means the table description is odd? Anyway. I’ve also added 4th order polys a-la S. Amusingly, the poly fit is fine, so I would have no complaints if S just used the Orcadas data. But then the fit wouldn’t be so good after 1950; and he wouldn’t be able to call it “Antarctic” temperatures.

So: just to be clear: the early part of S’s data comes from Orcadas, an Island station at 60 S. it is *not* an average of 90-64S as he says: its data from a single station. Any competent Antarctic-type reviewer would have caught this glaring error. This is a teensy bit of a problem for him, as his “Antarctic theory” is most pronounced S of 75S; arguably, 60 S should actually be in rest-of-world as far as he is concerned. I’ve no doubt though that his theory will prove sufficiently pliable to account for this 🙂

[Update: the data sparsity is a bit more obvious via a map: e.g. for 1910 (thanks G) -W]

[A read writes: Could you please be more clear? Write what is on the axes in different colors, what it is used by Svensmark for, and why you think that it’s wrong as opposed to some vague cliches that the data are not enough. I thought I had been. OK, my pic (the lower one) shows in black the raw data used in the lower line in S’s plot. They are the same, except I haven’t put a 12y filter through the data. Overplotted in blue is the raw Orcadas station data. From 1905 to 1950 the data overly so exactly that its hard to see the blue line unless you look closely, except for a few excursions (1945 is the most obvious) that are presumably caused by more data becomming transiently available for that year. This demonstrates that the data S is using from GISS really is the Orcadas data. Therefore it isn’t a mean for 90-64S or anything like it (that is obvious from the data from 1960 on, which disagrees. If anything there is an antiphase relation, especially from 1980 on. I hope thats clear now -W]

President Václav Klaus speaks for the first time about the American radar base…

…but also about global warming. See here. And also Lubos’s blog. And what did he have to say?

President Klaus also expressed his opinion on the recent finding of the UN scientific panel on global warming. In his opinion, warming is a myth. Oh dear, not a very good start.

Václav Klaus: I don’t see any destruction of the planet and I’ve never seen any… I would like to demonstrate my non-militant mood by showing that I have brought a Europencil Ah, is that the evidence for lack of destruction? More seriously, I would draw a distinction between environmental damage and global warming. The M11 near my home and office is environmental damage on a local scale; but maybe the Prez would see it as economically useful. But back to the global warming…

Continue reading “President Václav Klaus speaks for the first time about the American radar base…”

Revenge of the killer cosmic rays from hell

Yes, clouds and cosmic rays are back, via the indefatiguable Svensmark, at arXiv. But excitingly there is an Antarctic twist, in that the clouds connection explains the “Antarctic climate anomaly, ie why Antarctic and rest-of-work are out of sync. Errrm, but are they? Its a common idea during glacial periods, but Svensmark wants it to be true on shorter timescales so that it can’t be ocean forcing. See his fig 1. So (ignoring the fact that it clearly doesn break down in the most recent past, which I don’t see him noting) there is a nice anti-correlation on longer scales. Which I was unaware of. But: if you plot d-o-18 (a temperature proxy instead) between NGRIP (greenland) and Epica Done C (antarctica) you get:


[Update: Axes are time in years (x) and delta-o-18 (y) in per mille – thanks to LL]

Which doesn’t show the same thing at all. Which may be why his paper is in arXiv rather than a journal?

Oh, and fig 4a, which claims to plot Antarctic temperatures over the last 100 years, is a great nonsense: there is not enough data available to do this. You can’t even pretend to do it before the IPY.

(NGRIP data from, EDC from; nb NGRIP offset by 45 per mille)

[Fairly similar stuff at . The dodgy Antarctic figure becomes fig 6]

AR4 SPM sea level proves more interesting than expected

Its probably a measure of how accepted the bulk of the AR4 SPM is, that the most interesting discussion about it seems to center around the sea level rise uncertainty ranges. There does indeed seem to be some confusion here… RP Jr explores this, and points out that it would have been nice had the IPCC made a comparison easier, with which I agree (and complains about the take on this from the most authoritative source, of course RC; though as far as I can see he is wrong to say that we assert that the range isn’t lower).

But (before venturing onto the minutiae) I’ll say that as far as I can tell the main message is For each scenario, the midpoint of the range in Table SPM-2 is within 10% of the TAR model average for 2090-2099. So whatever disagreement is small; and likely to be due to estimates of the range rather than the central value.

The other point to make is what we’re discussing here is *not* what the septics have been pushing, which is based on a simple misreading of the report (thus RPs Thus, I conclude that the top end estimate has indeed come down from the TAR to the AR4, and those making this observation are accurately representing the AR4 is a touch disingenuous, because there are two schools here: those correctly noting a lowing of the range and those incorrectly touting nonsense that the value is halved: the latter sadly including the WSJ).
Continue reading “AR4 SPM sea level proves more interesting than expected”