Note: Steve McIntyre is also quite baffled by the Marcott et al paper, finding it currently unreproducible given the current information available. I’ve added some comments from him at the bottom of this post – Anthony
Guest Post by Willis Eschenbach
I don’t know what it is about proxies that makes normal scientists lose their senses. The recent paper in Science (paywalled of course) entitled A Reconstruction of Regional and Global Temperature for the Past 11,300 Years” (hereinafter M2012) is a good example. It has been touted as the latest hockeystick paper. It is similar to the previous ones … but as far as I can see it’s only similar in how bizarre the proxies are.
Nowhere in the paper do they show you the raw data, although it’s available in their Supplement. I hate it when people don’t show me their starting point. So let me start by remedying that oversight:
Figure 1. All of the proxies from M2012. The colors are only to distinguish individual records, they have no meaning otherwise.
I do love the fact that from that collection of temperature records they draw the conclusion that:
Current global temperatures of the past decade have not yet exceeded peak interglacial values but are warmer than during ~75% of the Holocene temperature history.
Really? Current global temperature is about 14°C … and from those proxies they can say what the past and present global average temperatures are? Well, let’s let that claim go for a moment and take a look at the individual records.
Here’s the first 25 of them:
Figure 2. M2012 proxies 1 to 25. Colors as in Figure 1. Note that each panel has its own vertical axis. Numbers to the left of each title are row/column.
Well … I’d start by saying that it seems doubtful that all of those are measuring the same thing. Panel 3/1 (row 3, column 1) shows the temperature decreasing for the last ten thousand years. Panels 4/4 and 4/5 show the opposite, warming for the last ten thousand years. Panel 4/3 shows four thousand years of warming and the remainder cooling.
Let’s move on to the next 25 contestants:
Figure 3. M2012 proxies 26 to 50. Colors as in Figure 1. Note that each panel has its own vertical axis. Numbers to the left of each title are row/column.
Here we see the same thing. Panels 1/1 and 4/1 show five thousand years of warming followed by five thousand years of cooling. Panel 1/5 shows the exact opposite, five thousand cooling years followed by five thousand of warming. Panel 4/5 show steady warming, panel 5/2 shows steady cooling, and panel 2/2 has something badly wrong near the start. Panel 2/4 also contains visible bad data.
Onwards, we near the finish line …
Figure 4. M2012 proxies 51 to 73. Colors as in Figure 1. Note that each panel has its own vertical axis. Numbers to the left of each title are row/column.
Panel 2/1 shows steadily rising temperatures for ten thousand years, as does panel 3/4. Panels 4/1 and 5/1, on the other hand, show steadily decreasing temperatures. Panel 4/2 has a hump in the middle. but panel 1/2 shows a valley in the middle.
Finally, here’s all the proxies, with each one shown as anomalies about the average of its last 2,000 years of data:
Figure 5. All Marcott proxies, expressed as anomalies about their most recent 2,000 years of record. Black line shows 401-point Gaussian average. N=9,288.
A fine example of their choice of proxies can be seen in the fact that they’ve included a proxy which claims a cooling about nine degrees in the last 10,000 years … although to be fair, they’ve also included some proxies that show seven degrees of warming over the same period …
I’m sorry, guys, but I’m simply not buying the claim that we can tell anything at all about the global temperatures from these proxies. We’re deep into the GIGO range here. When one proxy shows rising temperatures for ten thousand years and another shows dropping temperatures for ten thousand years, what does any kind of average of those two tell us? That the temperature was rising seven degrees while it was falling nine degrees?
And finally, their claim of turning that dogs breakfast shown in Figure 1 into an absolute global temperature and comparing it to the current 14°C average temperature estimate?
Don’t make me laugh.
I say the reviewers of this paper didn’t use their Mark I eyeball. The first thing to do when dealing with a multi-proxy study is to establish ex-ante criteria for the selection of the proxies (“ex-ante” meaning choose your criteria before looking at the proxies). Here are their claimed criteria …
This study is based on the following data selection criteria:
• Sampling resolution is typically better than ~300 yr.
• At least four age-control points span or closely bracket the full measured interval.
• Chronological control is derived from the site itself and not primarily based on tuning to other sites. Layer counting is permitted if annual resolution is plausibly confirmed (e.g., ice-core chronologies). Core tops are assumed to be 1950 AD unless otherwise indicated in original publication.
• Each time series spans greater than 6500 years in duration and spans the entire 4500 – 5500 yr B.P. reference period.
• Established, quantitative temperature proxies
• Data are publicly available (PANGAEA, NOAA-Paleoclimate) or were provided directly by the original authors in non-proprietary form.
• All datasets included the original sampling depth and proxy measurement for complete error analysis and for consistent calibration of age models (Calib 6.0.1 using INTCAL09 (1)).
Now, that sounds all very reasonable … except that unfortunately, more than ten percent of the proxies don’t meet the very first criterion, they don’t have sampling resolution that is better than one sample per 300 years. Nice try, but eight of the proxies fail their own test.
I must say … when a study puts up its ex-ante proxy criteria and 10% of their own proxies fail the very first test … well, I must say, I don’t know what to say.
In any case, then you need to LOOK AT EACH AND EVERY PROXY. Only then can you begin to see if the choices make any sense at all. And in this case … not so much. Some of them are obviously bogus. Others, well, you’d have to check them one by one.
Final summary?
Bad proxies, bad scientists, no cookies for anyone.
Regards,
w.
==============================================================
Steve McIntyre writes in a post at CA today:
Marcott et al 2013 has received lots of publicity, mainly because of its supposed vindication of the Stick. A number of commenters have observed that they are unable to figure out how Marcott got the Stick portion of his graph from his data set. Add me to that group.
The uptick occurs in the final plot-point of his graphic (1940) and is a singleton. I wrote to Marcott asking him for further details of how he actually obtained the uptick, noting that the enormous 1920-to-1940 uptick is not characteristic of the underlying data. Marcott’s response was unhelpful: instead of explaining how he got the result, Marcott stated that they had “clearly” stated that the 1890-on portion of their reconstruction was “not robust”. I agree that the 20th century portion of their reconstruction is “not robust”, but do not feel that merely describing the recent portion as “not robust” does full justice to the issues. Nor does it provide an explanation.
Read Steve’s preliminary analysis here:
[UPDATE] In the comments, Steve McIntyre suggested dividing the proxies by latitude bands. Here are those results:
Note that there may be some interesting things buried in there … just not what Marcott says.
Also, regarding the reliability of his recent data, he describes it as “not robust”. It is also scarce. Only 0.6% of the data points are post 1900, for example. This raises the question of how he compared modern temperatures to the proxies, since there is so little overlap.
Finally, about a fifth of the proxies (14 of 73) have the most recent date as exactly 1950 … they said:
Core tops are assumed to be 1950 AD unless otherwise indicated in original publication.
Seems like an assumption that is almost assuredly wrong. I don’t know if that’s a difference that makes a difference, depends on how wrong it is. If we take the error as half the distance to the next data point for each affected proxy, it averages about ninety years … pushing 1950 back to 1860 … yeah, I’ll go with “not robust” for that.
[UPDATE 2] Yes, I am shoveling gravel, one ton down, six to go … and I do get to take breaks. Here’s the result of my break, the Marcott proxies by type:
And here’s a picture of yr. unbending author playing what we used to call the “Swedish Banjo”.
Best to all,
w.
Thanks for a valuable article, Wills!
Such widely disparate proxy records sure do raise questions about what they are really measuring and how wide the confidence intervals may be. Also, with such a varied assortment the selection of the 73 proxies included seems immensely important. As with all of these multi proxy studies the screening to get a group of proxies may leave out proxies that could/should change the results significantly.
Ahhh, it’s because you clearly don’t understand statistics! [insert ad-hom attack of your choosing]. You need to imagine a Hockey stick shape and select the data sets which look more like it, and reject those which do not. You can think of a rationale later on, don’t worry about that right now. Oh, and don’t forget to divide by sqrt(n-1) to avoid any unfair bias and to prove to your colleagues that you thoroughly understand statistics. Go ahead and get your chums to fast track a nature paper through the old’ peer review process for you. Pick up a Nobel Peace prize as you pass go and for goodness sake, please try not to let anybody read your emails!
Even a kindergarten kid would get an F for that graph as a finger painting exercise but what would I know? I am sure that it truly does reveal the history of the planets climate to the 0.01 C accuracy that warmists claim….
We discuss the temperature of the planet and obtain a value of around 14C and debate it with people as if it really has some meaning. It is a strange game. It is almost like you have started a debate with your child about some pretend invisible pink elephant and what started off as a bit of childish indulgence has become a bit more serious. Your kid has decided that the pretend elephant is sick and you are being hit with real life vet bills! Now you are having to debate the health of the pretend elephant rather than just point out that there is no such thing as a pink invisible elephant because you know that there would be a major tantrum if you did.
So in the real world does the ‘temperature of the planet’ have any meaning? To me it is about as meaningful as the sum of the surface temperatures of ten randomly selected stars, the sum of the lengths of fify assorted rodents, the sum of the weights of everyone in Las Vegas with an ‘R’ in their name….
There is no hockey stick in their own published data: only one of the 73 proxies even remotely resembles one.
How they got to where they say they did is a fundamental mystery …
That is amazing. Truly amazing. How the heck do they expect to get away with this nonsense? How many times will these watermelon “scientists” get shown up before the masses turn nasty? Seriously nasty. The more they fake this stuff, the more obvious it is their intention to deceive. One might get it “wrong” or be “misguided”, but so many of them? Over and over and over? They get blown out of the water time and again for faulty science, and they are straight back at it like they are desperate, which of course they are (that’s quite telling, too).
Well done, Willis, for exposing more carp from Those Who Should Be De-funded. Treason still merits capital punishment, doesn’t it? I sure hope these *snips* and *snip-ettes* give some thought to their future. Perhaps they should backtrack while there is still time.
Should not be hard to produce more proxies of this quality with a random number generator. Add an instrumental temperature record at the end and there will always be a hockey stick
Count me as mystified.
If the “core tops are assumed to 1950 AD” I’m wondering how much proxy data they have since 1950 to create the hockey stick ending? How many of these graphs are in or out?
A while ago Steve McIntyre moaned about being tired of wading through ‘Dreck’ from Mann and others. Going through this paper must be an extraordinary unpleasant and painful endeavour.
I work in mineral exploration and have learnt to have little to no time for ‘averages’. Too many examples to explain, but Steve’s Macintyre’s experience with minerals would probably be similar.
I’ve worked with some within the industry, usually the computer modellers, who tend to love using ‘averages’, and these are very the same guys who usually never find anything. They think if you leave out the ‘weak’ areas, and the ‘weak’ data, as well as the ‘edges’ of supposedly ‘prospective’ ground (i.e. using a form of ‘spatial averaging’), then you can then concentrate on the good stuff; i.e. they average out very incomplete spatial information and think that is how you determine mineral prospectivity and deal with the uncertainties. Sometimes yes, but many times no, especially if the level of uncertainty is high, which is very common in mineral exploration. And in the last 3 cases I have seen, ore bodies were found over ‘weak’ data, in ‘weak’ areas, and at the ‘edge’ of or even outside of the supposedly ‘prospective’ ground. It just doesnt work, averaging spatial data when the level of uncertainty and inconsistency between various datasets is high.
A bit different to the above, but in the same ball park if you get my drift, ‘averaging’ can be a shoddy and a dangerous business if you don’t know what the various uncertainties are in the first place. Modellers tend to understand this much less than people in the field.
NSF funded this disaster and one of their program directors hyped it for the media. If there is congressional oversight over NSF, the overseers should come down hard right now.
Thanks Willis.
It might help if one knew all the “proxies” – what was measured, when, how accurate, how that relates to temperature, and so on. But it all seems such a muddle and the peer review – self correcting “science” fails time and again. For example if I were reviewer of this paper in draft form, I would write something like this:
In the first batch of 25, the bottom 2 in the middle column have these tags: “IOW225517” and “IOW225514” — so maybe they are related. One goes up sharply, then drops. The shorter one drops, but leaves open what the first 5,000 years might look like. How do those proxies support warming? Some proxies seem to bounce around wildly and some have extreme spikes that do not match anything else. Why does this happen if these proxies are supposed to relate to the same thing? Individually, some of these (maybe all of them) may provide useful information about past happenings – but Earth’s atmospheric temperature doesn’t seem to be one of them. Why does the author (s) think they do? I would have to tell the editor to which this was submitted that I think putting this in print would ruin the integrity of the publication. Well, I might not be so polite.
Like the “98% consensus”, this “study” indicates more desperation than science.
“I say the reviewers of this paper didn’t use their Mark I eyeball.”
Nor their white sticks or seeing-eye dogs … LOL !
Weak Willis:
“A fine example of their choice of proxies can be seen in the fact that they’ve included a proxy which claims a cooling about nine degrees in the last 10,000 years … although to be fair, they’ve also included some proxies that show seven degrees of warming over the same period …”
Yes there are regions in the planet that have experienced large amplitudes of warming/cooling in the last 10,000 years. This is the particularly plausible at high latitudes. Good Job Willis #thingsIdon’tmean
how do you do that, Willis? Do you teach a class
Wow! I saw the plots before but you make it so well presented.
R, how do you know? And how do you know that Marcott et al. obtained a statistically sound sampling of all the earth’s surface?
R says:
March 13, 2013 at 11:43 pm
Thanks, R. I’ve looked at a lot of individual temperature records over the years. And I’ve looked at a lot of proxies over the years. Yes, some areas warm and some areas cool … but that’s fractions of a degree. The overwhelming majority of proxies are more like the ones in Fig. 5 that are not far from the average.
The idea that one part of the world cooled by nine degrees, while another part of the world warmed by seven degrees, beggars belief. Heck, even among this group of proxies you can see how unusual those are.
Regards,
w.
dalyplanet says:
March 13, 2013 at 11:53 pm
No, I work building houses … today and yesterday I spent shoveling about 12 tonnes of gravel. And writing that post …
w.
Yamal again?
Reblogged this on The GOLDEN RULE and commented:
More seriously questionable data, “evidence” and conclusions from the CAGW scientists, but this is not science, it is basically garbage, as pointed out by Willis Eschenbach.
thingodonta says:
March 13, 2013 at 11:06 pm
I work in mineral exploration and have learnt to have little to no time for ‘averages’. Too many examples to explain, but Steve’s Macintyre’s experience with minerals would probably be similar.
————————————————-
I am no mathematician or scientist, but over the years have had to evaluate ‘statistics’ about social policy issues like health and housing. Since I am lucky enough to have some experience on the ground in these areas, I long ago worked out that ‘averages’ are junk when anything remotely complex is under discussion.
Why so-called scientists pretend that this stuff is more than one of many indicators is beyond me. Even a not-too-bright real estate agent knows that ‘average’ prices in one area for a pecific period are only slightly more useful than an ashtray on a motorbike when you get down to cases.
And that’s leaving aside the whole question of how good the data is in the first place.
“• Established, quantitative temperature proxies”
————————————————
Gergis et al failed with improper screening, and here we go with no screening for proxy quality at all ?
Why did a whole generation of scientists screen data, when it is so much easier to take everything supposed to respond to temperature (among other variables) and regardless of individual proxy issues ?
I have always enjoyed reading good science fiction, for whatever man can imagine usually turns out to be possible. This is science fantasy that belongs in a section of the library that is political new age fantasy science, thus beyond my capabilities of understanding.
Once again the ‘professionals ‘ work at a standard unacceptable for a student taking a degree course , for the failure to filter out such proxies would probable lead to the failure to get a pass mark .
You have to ask , are there actual any standards within climate ‘science ‘ ?