The Tick

In the last post we looked at the recent temperature reconstruction for the holocene, in particular the last 11,300 years, from Marcott et al. We noted that the changes over most of this very long time span were no bigger, but a lot slower, than the changes over the last century or so. That means trouble.

We also mentioned that the “uptick” at the end of their “main” (the “Standard 5×5”) reconstruction was much larger than in their RegEM reconstruction, and that they had expressed doubt about its robustness. The large uptick at the end (in 1940) is larger than indicated by the instrumental data — another reason to doubt its reality. Let me tell you my opinion why this difference exists. I could be mistaken, but this is what I think.

Global Temperature Change — the Big Picture

There’s a new reconstruction of past temperature covering the last 11,300 years by Marcott et al. (2013, A Reconstruction of Regional and Global Temperature for the Past 11,300 Years, Science, Vol. 339 no. 6124 pp. 1198-1201, DOI:10.1126/science.1228026). Data for their reconstructions, and the proxy data on which they’re based, are part of the supplementary materials.

The Marcott reconstruction has been joined to the Shakun reconstruction prior to that, and the HadCRUT4 global temperature data since, and the projected temperature change under the A1B scenario for the future, by Jos Hagelaars, in order to show us some perspective on climate change past, present and future.

This graph has been dubbed the “wheelchair.” Compared to the past, what’s happening in the present is scary. The future is scary as hell.

Antarctic Sea Ice Gain

We’ve looked at Arctic sea ice data, noting not only its overall decrease but changes in the annual cycle as well. As one reader suggested, let’s take a similar look at sea ice in the southern hemisphere.

Arctic Sea Ice Loss, part 3

Having looked at extent, area, and volume of Arctic sea ice, then at its thickness, let’s examine some other derived variables.

Arctic Sea Ice Loss, part 2

In the last post we looked at the extent, area, and volume of Arctic sea ice. We also mentioned that we can derive other quantities from these, namely the average thickness as the volume divided by area, and what I called the “spread” which is the extent divided by the area. I’ve also been looking at the difference (rather than ratio) of sea ice extent and area, which I’ve dubbed the “split” (for lack of a better term). I’ll take up spread and split in another post, at the moment let’s see how thickness has changed over time.

Arctic Sea Ice Loss, part 1

Although it’s useful and sometimes interesting to refute silly ideas about Arctic sea ice loss (such as the claim that it is “stabilizing” or even in “recovery”), it’s far more interesting scientifically to consider what available data actually tell us about the changes of the ice pack in the frozen north.

Ice Cover is Not “Stabilizing”

NOTE: for a brief, non-technical summary of this post see the UPDATE at the end. To get there, go to the full post (not just the blog’s home page), then click here.

Real data are the combination of signal and noise. By noise I don’t just mean measurement error. I mean the stochastic part of the process. That includes naturally occuring noise in the system itself — those ubiquitous wiggles up and down and up and down and down and up, that never cease but never really get anywhere. They’re not part of the trend, they’re noise. If you want to know what the trend is then you have to account for the noise.

If you claim that “ice cover is stabilising,” then you better be talking about the trend. You damn well better not be basing that conclusion on the effect of those ubiquitous wiggles that never cease but never get anywhere.

Back to School

Much of what’s wrong with the online discussion of global warming is revealed by a recent reader comment on RealClimate.

Greg Goodman thinks that he’s taking climate scientists to school — he actually “lectures” the RealClimate readership about their supposed need to “dig a bit deeper” into the data on Arctic sea ice (both extent and area). He shows a graph based on some analysis which — unbeknownst to him — actually reveals that he doesn’t know what the hell he’s doing. He thinks he has established the presence of “cyclic variations” of which the climate science community is ignorant, and concludes that climate scientists are missing “important clues” about “internal fluctuations” which, of course, those inadequate computer models just can’t handle.

One would be hard pressed to find a more clear-cut example of hubris.

Climate scientists who study sea ice have been all over the data, every piece of it, but instead of making the mistakes Goodman makes they’ve been as careful and rigorous as their expertise and experience allow. They have certainly dug a whole helluva lot deeper than Greg Goodman has, or probably is capable of. It’s Goodman who needs to go back to school.

Cherry-Picking is Child’s Play

Anybody can do it.

Fake “skeptics” of global warming do it all the time. One of the latest and most extreme — this one is a real doozy — comes from John Coleman. Of course it’s regurgitated by Anthony Watts.

Theil-Sen

A reader recently inquired about using the Theil-Sen slope to estimate trends in temperature data, rather than the more usual least-squares regression. The Theil-Sen estimator is a non-parametric method to estimate a slope (perhaps more properly, a “distribution-free” method) which is robust, i.e., it is resistant to the presence of outliers (extremely variant data values) which can wreak havoc with least-squares regression. It also doesn’t rely on the noise following the normal distribution, it’s truly a distribution-free method. Even when the data are normally distributed and outliers are absent, it’s still competitive with least-squares regression.