PAGES2019: 30-60S

Aug 26, 2021 – 2:24 PM

The 30-60N latitude band gets lots of attention in paleoclimate collections – probably more proxies than the rest of the world combined. The 30-60S latitude band is exactly the same size, but it is little studied. It is the world of the Roaring Forties and Furious Fifties, a world that is almost entirely ocean. The only land is New Zealand, Tasmania and the southern coast of Australia facing Antarctica, the tip of South Africa and the narrow part of South America: southern Chile and Argentina. But 96% or so is ocean.

No Ocean Proxies

Although the 60-30S is almost entirely ocean, PAGES 2019 did not use a single ocean proxy in its data. They used only eight series (out of 19 PAGES 2017). Seven tree ring series: two from New Zealand (both less than 500 years), three from Tasmania (one long, two less than 500 years), two from southern South America (both less than 500 years) and one weird lake sediment from Chile (a “singleton” proxy using pigments in the sediments).

Only One Long Proxy

Only one proxy in the network has values prior to AD750 and only two proxies have values prior to AD1450. Thus, the only information directly comparing medieval and modern values comes from these two proxies: Mt Read, Tasmania (a series used as long ago as Mann et al 1998 and Jones et al 1998) and many times since and the Laguna Aculeo pigment series – neither of which have shapes remotely similar to the PAGES2K 60-30S latband reconstruction – see below. (The latband reconstruction was calculated from the enormous file at NOAA here).

Take a look at the underlying data (converted to SD Units) – more commentary below.

PAGES 2019 20-60S Proxies (SD Units). Red dots show year 2000 values. Together with PAGES 2019 CPS 60-30S reconstruction.

Comments on the PAGES 60-30S HS

Quite aside from many issues about the PAGES2019 selection of 60-30S proxies, obvious questions arise about how they derived their latband reconstruction.

  • the blade of the reconstruction HS goes from -1 sigma in early 20th century to more than 4 sigma in 2000. Yet there is no comparable deviation in any of the underlying proxies. The three South American proxies and the long Mt Read, Tasmania tree ring chronology don’t have anything like a blade; the four short tree ring chronologies (two Tasmania and two New Zealand) have increase sharply in 20th century, but not enough to yield the PAGES 2019 HS. (These tree chronologies have been selected from a much larger candidate populaion – a screening process that already imparts a serious bias.)
  • the only 30-60S proxy with a value in the year 2000 is Mount Read, which has a value of ~1 sigma. Yet the PAGES 2019 30-60S (CPS) reconstruction has a value of over 4 sigma. How did they do that?
  • PAGES 2019 provide code for the generation of figures from reconstructions, but didn’t archive the code for the generation of the reconstructions. (At least in the links provided in any of the articles.) So it’s impossible to precisely diagnose what’s going on.
  • although PAGES proclaim the importance of public archiving as a selection criterion, only one of the tree ring chronologies (the long Mount Read chronology) can be firmly associated with ITRDB measurement data archives. Both South American tree ring chronologies derive from lead author Neukom’s calculation on unarchived South American data. D’Arrigo’s 1995 data remains unarchived, as does the Duncan New Zealand data. At the time of the PAGES 2013 publication of the two Allen tree ring chronologies from Tasmania, no relevant measurement data was archived; since then, Allen has archived measurement data from Tasmania, but PAGES 2019 doesn’t contain any citation.
  • the Laguna Aculeo series is a purported temperature reconstruction from pigments. At present, there are no other similar temperature reconstructions, leaving this series as a sort of ad hoc singleton.

High-Resolution Ocean Proxies

But most of all, given that the 60-30S latband is almost entirely (~96%) ocean, it seems bizarre that PAGES 2019 did not use any ocean core proxies, especially since there are physical formulas for estimating SST from alkenone or Mg/Ca measurements. Any conversion of tree ring widths to temperature in deg C is the result of ad hoc statistical fitting, not a universal formula. Alkenone values have been measured all over the modern ocean and nicely fit known ocean temperatures. In addition, alkenone values for ocean cores going back to deeper time (even to the Miocene) give a consistent and reproducible narrative. So there’s a lot to like about them as a candidate for a “good” proxy.

While there are numerous high-resolution (10 year resolution) alkenone and Mg/Ca measurements in the North Atlantic with values through the last millennium and up to the present, to my knowledge, there were not any such series as of PAGES 2013 or PAGES 2017. (In my opinion, IPCC AR5 ought to have noted this and suggested that this deficiency be remedied.)

PAGES 2017 included three ocean core proxy series in the 30-60S, all from offshore Chile. Their resolutions ranged from 24 to 83 years. There are some thus far undiscussed puzzles in the PAGES 2017 version of these series – as, in each case, modern values available in the underlying archive series were deleted. In each case, unsurprisingly, the effect of the deletion was to hide a decline. I will discuss this series below.

Subsequent to PAGES2017, the very first high-resolution (less than 10 years) 30-60S ocean core alkenone (or Mg/Ca) proxy was published: MD07-3093. [Collins, JA et al. (2019): Centennial-scale SE Pacific sea surface temperature variability over the past 2300 years. Paleoceanography and Paleoclimatology link.] It has values dated from 372 BC to 1992 AD, with a resolution of 5.4 years. The appearance of the high-resolution MD07-3093 is obviously very different – even opposite – to the PAGES 2019 reconstruction.

The three 30-60S ocean cores that were in PAGES 2017 (and dropped from PAGES 2019) are shown below. In each case, I’ve compared the NOAA or Pangaea original archive data (black) to the PAGES 2017 version (red). In each case, the PAGES2017 version was shortened by removal of a few closing values: CF7-33 was shortened from AD1874 close to AD1784; GeoB 3313-1 shortened from AD1884 to AD1650; and GeoB 7186-3 shortened from AD1938 to AD1900.

Although each of these series is lower resolution than the new MD07-3093 series, they tell the same story: a 1-1.5 deg C decrease in temperatures from the first millennium to the 20th century. And MD07-3093 indicates that the decrease has been maintained into the late 20th century (at least in these offshore Chile ocean core datasets.)

Conclusion

Given that the 60-30S latband is almost entirely ocean, it seems logical that IPCC and PAGES2K should use data from ocean proxies to estimate past temperature in this latitude band. But this isn’t what they’ve done. Instead, they’ve purported to estimate past temperature from a few scattered tree ring chronologies, only one of which reaches earlier than AD1850; and an idiosyncratic singleton pigment series. Ironically, the only 30-60S proxy series in PAGES 2019 that reaches back into the first millennium – the Mount Read, Tasmania tree ring series – was used by Mann et al 1998-1999, Jones et al 1998 and numerous other supposedly “independent” multiproxy studies. Neither of the two series reaching back to the medieval period permit the conclusion that modern period is warmer than medieval period. Caveat: I’m not saying that it isn’t; only that this data doesn’t show it, let alone support the big-bladed HS cited by IPCC. High-resolution alkenone measurements from ocean cores offshore Chile show a consistent decrease in ocean temperatures over the past two millennia that is neither reported nor discussed by IPCC (or PAGES 2019).

To be clear, some of the technical articles on 30-60S ocean core proxies by specialist authors are truly excellent and far more magisterial than the IPCC mustered, in particular, several articles on offshore Chile. Here are a few:

Mohtadi et al, 2007. Cooling of the southern high latitudes during the Medieval Period
and its effect on ENSO link

Killian and Lamy 2012. A review of Glacial and Holocene paleoclimate records from southernmost Patagonia (49-55degS) link

Collins et al 2019. Centennial‐Scale SE Pacific Sea Surface Temperature Variability Over the Past 2,300 Years link


By Stephen McIntyre | Posted in Uncategorized | Comments (7)

PAGES19 Asian Tree Ring Chronologies

Aug 15, 2021 – 3:25 PM

About 20% of the PAGES 2019 proxies are 50 Asian tree ring chronologies, all of which were originally published as chronologies in PAGES (2013). At the time, none of these series (and certainly not in these digital versions, had ever been published in technical literature, peer reviewed or otherwise. Nothing in the Supplementary Information to any of these articles says who calculated these chronologies or how they were calculated. PAGES (2017) does cite a couple of academic articles (especially Cook et al 2013) for many of these series, but none of these chronologies actually appears in any of these academic articles or their supplementary information.

PAGES (2013) was originally rejected by Science in 2012, because peer reviewers (including Michael Mann) objected to the introduction of so many new proxies in what was ostensibly a review paper; they sensibly recommended that components first be peer reviewed in relevant specialist journals. However, PAGES2K results had already been incorporated into a pending IPCC assessment (AR5), so the authors, now under a very short deadline, submitted to Nature, which was confronted by the same review problems that led to the rejection by Science. Keith Briffa had a clever, too clever, solution: publish the PAGES2K submission as a “Progress Article” – a classification that did not require the peer review procedure required for a Research Article. This would qualify the article for IPCC and nobody would notice the sleight-of-hand. (Even I didn’t notice it at the time; someone told me.)

One of the consequences of the 2013 manoeuvring was that several hundred Asian tree ring chronologies were introduced to paleoclimate archives with no technical publication or technical peer review, no information on how they were calculated or even who among the PAGES2K (2013) authors had calculated them.

Having been introduced through the back door, so to speak, nearly all of the 200+ Asian tree ring chronologies were carried forward into the PAGES (2017) compilation, and then a subset of 50 chronologies (more or less the most hockey stick shaped) was screened to become a substantial component of PAGES (2019) – the source of the IPCC Summary for Policy-makers Hockey Stick.

In an earlier post, I had commented on the extreme closing uptick in one of these series (Asia_207). In 2013, despite PAGES2K’s professed insistence on using proxies with public archives, measurement data for this chronology was not available, so it was impossible to see what was going on at the time.

In the SI to PAGES (2017), the data is cited to the site denoted by NOAA as paki033, a site located in a mountainous region in northern Pakistan near Gilgit. As a short editorial digression, I visited Gilgit briefly in 1968 and was there when we learned, via shortwave radio, that Bobby Kennedy had been assassinated. Twenty years later (1988), Osama bin Laden, then a CIA protege, announced himself by slaughtering the Shia population of Gilgit. (In today’s US intel nomenclature, since they were Shia, the murdered Shia would presumably be labeled as “Iran-backed” as though that were both justification and sufficient explanation.)

But back to main programming.

Measurement Data and Chronology Construction

From the measurement data for paki033.rwl at NOAA, I calculated a site chronology using the rcs function from Andy Bunn’s dplR package. The resulting chronology does NOT have the huge uptick of PAGES2019 – indeed it declines over the 20th century. (Diagram below used dplR function – see script below).

Code for this diagram is as follows:

library(dplR)
loc=”https://www.ncei.noaa.gov/pub/data/paleo/treering/measurements/asia/paki033.rwl”
download.file(loc,”e:/temp/temp.rwl”)
rwl=read.rwl(“e:/temp/temp.rwl”)
Po=data.frame(series=names(rwl),po=1)
rwi=rcs(rwl,po=Po) #646 18
crn=chron(rwi, prefix = “033”)
plot(crn,main=”Mushkin PIGE – paki033″)

I got an almost identical chronology by fitting a single Hugershoff curve (rw = A+B* (x^D)*exp(-C*x) to allow for growth prior to chronology calculation.

An observation here: although the overall appearance of the chronologies is very different, there is a high correlation (~0.5) between the PAGES version and the other versions – that high a correlation strongly indicates to me that they are representing the same data. (Also the start and end dates of the PAGES2K version exactly match the measurement data.)

What could possibly account for the huge uptick in the PAGES version? It turns out that the paki033 dataset consists of only 10 trees (18 cores). Only two of the trees are dated prior to the 18th century – well below usual minimums for calculating a chronology. Only 6 trees have cores extending to the last year (2007). This is a very small total – indeed, so small that it’s possible to plot actual measurements for all 6 trees very easily so we can look for ourselves at what’s going on.

Here is a plot of actual measurements for the two cores from each of six trees for the period 1700-2007. One tree (MUSP04) is relatively old and slow-growing. Most of the trees were relatively young (dating from 19th century) and showed characteristic decline in measured ring width as the tree got older (and diameter increased.) Nothing in this data shows an upspike in 2007.

So who calculated the Asia_207 chronology? And how was it calculated?

At the time (2013), Briffa and Melvin of the University of East Anglia were hyping a method that they called “signal-free” tree ring chronology calculation, which, in the examples that they showed, resulted in a more HS-shaped chronology than produced by ordinary chronology. It’s possible that the PAGES2K chronology was produced with some variation of this method. Melvin’s article does not provide a clear description of the mathematical procedure in their algorithm. They used ugly Fortran code that might be possible to figure out. But it takes time to parse this stuff and, without knowing for sure that this technique was used in PAGES2K, I’ve got other things to do.

But, even if the chronology calculation can be determined to be Melvin’s method (or some equivalent), this example ought to raise serious issues about the validity of the method- whatever it was. There is nothing in the actual ring width measurements that justifies the huge upspike in the archived PAGES2K Asia_207 chronology. The implication is that there is something wrong with the chronology algorithm used by PAGES2K (2013) authors. If so, the defect would affect not just the Asia_207 chronology, but a vast swathe of other PAGES2K chronologies relied upon in the IPCC diagram. I checked a couple of others and was unable to replicate them either.

As a caveat, I’m not saying that “everything” in the IPCC diagram stands or falls with this particular issue. There are many issues with this diagram – I listed many in my first post on this topic and am aware of many aware. It’s possible that I’ve overlooked something. If a possible error in this analysis is identified, I’ll promptly evaluate and amend if required.

By Stephen McIntyre | Posted in Uncategorized | Comments (33)

The IPCC AR6 Hockeystick

Aug 11, 2021 – 3:14 PM

Although climate scientists keep telling that defects in their “hockey stick” proxy reconstructions don’t matter – that it doesn’t matter whether they use data upside down, that it doesn’t matter if they cherry pick individual series depending on whether they go up in the 20th century, that it doesn’t matter if they discard series that don’t go the “right” way (“hide the decline”), that it doesn’t matter if they used contaminated data or stripbark bristlecones, that such errors don’t matter because the hockey stick itself doesn’t matter – the IPCC remains addicted to hockey sticks: lo and behold, Figure 1a of its newly minted Summary for Policy-makers contains what else – a hockey stick diagram. If you thought Michael Mann’s hockey stick was bad, imagine a woke hockey stick by woke climate scientists. As the climate scientists say, it’s even worse that we thought.

Curiously, this leading diagram of the Summary of Policy-Makers does not appear in the Report itself. (At least, I was unable to locate it in Chapter 2.) However, it is clearly the progeny of PAGES2K Consortium (Nature 2019) and Kaufman et al (2020), both of which I commented on briefly on Twitter (see here).

It’s hard to know where to begin.

The idea/definition of a temperature “proxy” is that it has some sort of linear or near-linear relationship to temperature with errors being white noise or low-order red noise. In other words, if you look at a panel of actual temperature “proxies”, you would expect to see series that look pretty similar and consistent.

But that’s not what you see with the data used by the IPCC. You’d never know this from the IPCC report or even from the cited articles, since authors of these one- and two-millennium temperature reconstructions scrupulously avoid plotting any of the underlying data. It’s hard for readers unfamiliar with the topic to fully appreciate the extreme inconsistency of underlying “proxy” data, given the faux precision of the IPCC diagram.

Many of the series discussed in this post, including nearly all of any HS-shaped series, have been previously discussed in Climate Audit blog posts (tag/pages2k) from 2, 5, 10 or even 15 years ago or in tweets from 2019 and 2020 (see here).

The PAGES2019 is not a “random” selection of proxies, but winnowed through ex post criteria. As Rosanne d’Arrigo explained to the NAS panel many years ago: if you want to make cherry pie, you first have to pick cherries.

The PAGES2019 dataset consists of 257 proxies, selected from the prior PAGES2017 dataset consisting of 692 proxies, which had previously been selected from thousands of proxy series accumulated by many authors over the years.

In order to give readers an overview of the underlying data – not the massaged final product, I’ve plotted three batches of 11 randomly selected series from each of PAGES2017, PAGES2019 and then PAGES2019 North American tree rings and then commented on each batch. (The samples were selected by R formula sample(1:K, 11) where K is the size of dataset being sampled.) In each case, there were usually series that I had already studied plus numerous non-descript series, which are notable and important to show precisely because the majority of proxies are non-descript and you need to see this to understand it.

This post will be a work in progress for a few days, as I have some sections on special issues that I will try to add as I have time.

A First Batch: PAGES2017 Proxies

As a first illustration, below is a random sample of 11 PAGES2017 series. The series carried forward to PAGES2019 are in blue. For reference, the IPCC curve is shown in red. As you can easily see, most of the series are non-descript and short. Only one series in this sample (Cape Ghir temperature alkenones) has a hockey stick shape, but it goes down.

The Cape Ghir series, shown above, is in deg C, but has an obvious problem: it goes down. (See prior Climate Audit discussion of Cape Ghir alkenone series here). And this is not a case where the raw proxy measurement has an inverse relationship to temperature (e.g. coral Sr or coral d18O), but a case where the temperature estimate from the proxy goes down. Alkenones are a very unique proxy because there are widely accepted formulas for converting alkenone measurements directly to deg C. Alkenones are widely used to estimate ocean temperature in deep time, yielding consistent estimates for millions of years. This is totally different than tree ring measurements, where ring widths have first to be adjusted for age and location, prior to trying to develop an ad hoc local formula to estimate local temperature from a sort of average of ring widths.

Precisely why local Cape Ghir (offshore Morocco) temperatures were going down is somewhat of a quandary. Rather than figuring out this quandary, Neukom and the woke just turn the series upside down, following the example of Upside Down Mann by orienting the series according to its correlation with target instrumental temperature, even in their “CPS” reconstruction – a technique that is normally resistant to opportunistic flipping of proxies to enhance HS-ness of a final reconstruction.

Watch what Neukom et al did with their “CPS” method:

CPS (to my knowledge) in all prior reconstructions by non-woke authors is an average of scaled data that has been oriented ex ante by known properties of the proxy. I.e. it won’t flip over an alkenone temperature estimate simply because it goes the wrong way. But this salutary property is not maintained in Neukom’s bastardized implementation of CPS – a bastardization that ought to have been resisted by reviewers somewhere along the line. PAGES2K produced temperature reconstructions by seven different methods, all of which yielded somewhat similar results to CPS – strongly suggesting that these other methods also flip series like Cape Ghir.

A Second Batch: PAGES2019 Proxies

Here’s a second random sample of proxies, this time all from the additionally screened PAGES2019 subset. Take a look, comments below.

It’s not as though PAGES2K made a composite from 257 series that are two millennia long, all or a majority having a HS shape. One series in this sample does look a lot like the IPCC stick and will be discussed at length below, but the others look very different.

Four of the series in the sample are very short – three of them are actually shorter than the instrumental record. These are all coral Sr or coral d18O series, which make up 25% of the PAGES2019 data set. The extremely short records illustrated above are typical, indeed almost universal, in this class of proxy. They do have a pronounced trend in the instrumental period. This contrasts with the lack of trend that one sees in the two long proxies in the middle column above – a tree ring series from Mt Read, Tasmania (also used in MBH98) and a 1983 ice core series by Fisher from Devon Ice Cap on Baffin Island (also available to 1990s vintage multiproxy studies).

The short coral series do not contribute information to the medieval and earlier periods which one is trying to compare to the modern period. So what is their function? Do they contribute anything other than painting a moustache on the non-descript longer series?

The tree ring series in this sample are rather short; the screening procedures have somewhat concentrated series with slight upticks. (The stripbark bristlecone chronologies that were so prominent in the Mann et al Hockey Stick continue to be used in PAGES2019 – as discussed below.) I discussed the series in the left column with large uptick (Asi_MUSPIG aka paki033) in a 2019 tweet thread here. I located the underlying ring width measurements at NOAA and re-calculated the tree ring “chronology” using standard methodology – see below. The high-frequency details match, showing that the underlying measurement data is apples-to-apples. No chronology from original authors is archived at NOAA: so how did PAGES2K manage to get such a hockey stick? I have no idea.

The most “interesting” series in this sample batch is the borehole temperature reconstruction that has such an uncanny resemblance to the eventual IPCC reconstruction. By coincidence (or not), I wrote about this borehole temperature reconstruction (from WAIS Divide, Antarctica) in February 2019, a few months before publication of PAGES 2019 – see here – scroll down – for a more thorough analysis.

I’ve written multiple posts on the mathematics of borehole inversion calculations, which purport to estimate temperatures for thousands of years into the past from modern day temperatures measured downhole. These calculations require the inversion of a multicollinear matrix (with determinant close to 0). As far as I’m concerned, nearly all the details that specialists pontificate about are a sort of Chladni pattern artifact.

But that’s another story. Here the problem was much stranger. A few years earlier, I had (circuitously) managed to obtain a copy of the code used to calculate this borehole inversion (which is not archived anywhere.) The code showed that they had deleted the top 15 meters of the core from their calculation.

I’ve had a LOT of trouble getting the underlying borehole temperatures for some famous series. (The 2006 NAS panel cited one such result, but the original author (a US government employee) refused to make the data available, and, to my knowledge, it remains unavailable.) However, in this case, the underlying downhole temperatures had been archived, including the values had been deleted. Needless to say, they went down. An inversion using all the data would not have resulted in the impressive Hockey Stick in the PAGES2019 dataset, but a substantial recent decline.

Prima facie, another example of “hide the decline”.

To be fair, as I observed in the earlier post, there is a dramatic seasonal fluctuation in temperatures in the top portion of the Antarctic ice sheet, which makes the already formidable (and probably impossible) inversion problem even more intractable. In my Feb 2019 post, I showed a diagram from van Ommen et al (1999) which showed the dramatic changes in downhole temperature as the seasons changed: a sort of damped sinusoidal pattern can be discerned. In the top 15 meters of the core, seasonal changes dominate.

Note that the blade on the hockey stick in this IPCC series is entirely dependent on the choice of 15 meters as a cutoff point for the borehole inversion. A choice of 20 meters would have probably eliminated the blade altogether.

The fact that the top portion of the core has to be excluded because of seasonal effects also creates a strange irony: the layers at 15 meters at WAIS date back to the 1960s. So IPCC has ended up relying on a series that purports to reconstruct temperature up to 2007, but without using any of the ice core dating from ~1965 to 2007. The calculation is entirely done from ice core layers dated prior to the 1960s. Does this seem reliable to any of you? Doesn’t to me.

Furthermore, the WAIS Divide borehole temperature reconstruction yields a totally different result than the widely replicated and well understood d18O isotope series.

Given the questions and defects surrounding the WAIS borehole inversion series, it is absurd that this series (a singleton, to boot) should be used in a policy-relevant document. That the final IPCC diagram is so similar to this garbage series also makes one wonder about what is happening under the hood of the multivariate calculations.

A Third Batch: PAGES2019 North American Tree Rings

North American tree rings (including some Arctic series) make up ~25% of PAGES2019 proxies. Here’s a random sample.

The majority are short and rather non-descript – nothing like the final IPCC diagram.

There are one series with an enormous hockey stick: Mackenzie Delta (Porter 2013); and two series (“GB [Great Basin]” and nv512) with noticeable closing upticks. Sharp-eyed readers may have already figured out some of this story.

I discussed the Mackenzie Delta super-stick of Porter et al (2013), a new entry to hockey stick fabrication technology, in July 2019 here on Twitter. It comes from Yukon, Canada, an area that, in a 2004 study by d’Arrigo et al, had been a type location for the classic “divergence problem” – ring widths going down, while temperatures went up. So how did Porter et al manage to get a super-stick that had eluded Jacoby and d’Arrigo, long-time searchers for hockey sticks in tree ring data and not shy about picking cherries in order to make cherry pie?

They took “hide the decline” to extremes that had never been contemplated by prior practitioners of this dark art. Rather than hiding the decline in the final product, they did so for individual trees: as explained in the underlying article, they excluded the “divergent portions” of individual trees that had temerity to have decreasing growth in recent years. Even Briffa would never have contemplated such woke radical measures.

To be fair, Porter et al’s original article showed both the actual (non-descript) chronology from all trees, together with superstick resulting from “hide the decline” on individual trees: the decision to use the spurious superstick belongs to Neukom and PAGES2019.

Stripbark Bristlecone Chronologies

As noted above, sharp-eyed readers may recall the identifier nv512. It is one of the classic Graybill stripbark bristlecone chronologies (Pearl Peak), which we had observed to dominate both the MBH98 PC1 and the final MBH98 reconstruction. It (and other key stripbark sites) was listed in McIntyre and McKitrick (2005 GRL) Table 1:

Readers will also recall that the 2006 NAS Panel recommended that “stripbark” chronologies be “avoided” in temperature reconstructions. Although the climate community has professed to implement the recommendations of the NAS Panel, they are addicted to stripbark chronologies, the properties of which are well known. Five different PAGES2019 series use stripbark bristlecones (three from original Graybill versions): nv512 (Pearl Peak); nv513 (Mount Washington); ca529 (Timber Gap Upper); SFP (an update of San Francisco Peaks, incorporating az510) and GB (a composite of Pearl Peak, Mount Washington and Sheep Mountain, using both Graybill and updated information).

In 2018, I looked at how North American tree ring networks had changed since MBH98. The one constant was the addiction of paleoclimatologists to stripbark chronologies- a phenomenon that I had commented on long before Climategate (citing Clapton et al and Paeffgen et al), much to the annoyance of dendros, but the comment remains as true now as it was then.

South American Proxies

add

Other Proxies

add

Conclusion

I discussed many of these problems in July 2019, within a couple of days of publication of the underlying article (see here). While I don’t necessarily expect IPCC reviewers to be paying rapt attention to my twitter feed, one surely presumes that IPCC climate scientists, who are employed full time on these topics, to be competent enough to notice things that I was able to observe in my first day or so of looking at PAGES2019. But their obtuseness never ceases to amaze.

By Stephen McIntyre | Posted in Uncategorized | Comments (149)

Milankovitch Forcing and Tree Ring Proxies

Mar 2, 2021 – 5:05 PM

Mar 2, 2021. This post was written in 2015 but, for some reason, I didn’t publish it at the time.  Seems just as valid today as when it was written.

 

Esper et al 2012, Orbital Forcing of Tree Ring Data pdf SI, is one of the few paleoclimate articles in past decade which really made me stop and think. It connected two obvious points:

  • high-latitude tree ring proxies are sensitive to summer (JJA, even JJ) temperature, not annual temperature.
  • high-latitude NH summer insolation, which has long had special interest as the “prime forcing” of Milankovitch theory of ice ages, had declined by ~6 w m-2 over the past 2000 years, the period covered by many popular IPCC temperature reconstructions. An amount that is approximately four times larger than anthropogenic forcing from CO2 since 1750 AD (~1.5 w m-2).

From these two points, they made plausible and compelling observation that the very large changes in high-latitude Holocene summer insolation should be visible in long high-latitude tree ring chronologies, especially those chronologies reaching back to the Roman period and earlier.

But it isn’t, as they demonstrated in an important graphic, which, unfortunately, was buried in the SI where it passed unnoticed. (One of the authors drew my attention to it several years ago or I too would have missed it.) Long tree ring chronologies have negligible millennial-scale variance – one more reason to distrust the temperature reconstructions of PAGES2K and IPCC.

Esper Figure S1

Here is the interesting figure S1 from Esper et al 2012. It compared three long tree ring width chronologies (grey-black) to Norwegian glacier equilibrium line (blue) and Yamal treeline (km north of present treeline.)  While the glacier equilibrium line (and Yamal tree line) have both migrated lower (southerly) with

However, as shown in Figure S1 of Esper et al 2012 (shown below), these long chronologies have more of less zero millennium-scale variability over the past 7000 years i.e. in addition to other defects in tree ring chronologies as temperature proxies, they only show high-frequency variability.  In contrast, Holocene-scale changes were visible in equilibrium lines of Norwegian glaciers and the treeline in Yamal.

Figure 2. Esper et al 2012 Figure S1. Original Caption: Showing multi-millennial TRW records from Sweden, Finland, and Russia (all in grey)
together with reconstructions of the glacier equilibrium line in Norway(blue), northern treeline in Russia (green), and JJA temperatures in the 60-70°N European/Siberian sector from orbitally forced ECHO-G7,8 (red) and ECHAM5/MPIOM9 (orange) CGCM runs10. All records, except for the treeline data (in km) were normalized relative to the AD 1500-2000 period. Resolution of model and TRW data were reduced (to ~ 30 years) to match the glacier data. Comment: Tree ring width chronologies (grey) are Grudd et al, 2002 (Tornetrask, northern Sweden); Helama et al 2010 (Finland); and Hantemirov and Shiyatov 2002 (Yamal); Norwegian glacier equilibrium lines (blue) are Aspvatnet (Bakke et al 2005a) and Lyngen (Bakke et al 2005b); treeline northing (in km) is from Yamal (Hantemirov and Shiyatov, 2002). 

 

In their important diagram in the Supplementary Information, Esper et al showed proxies back to 7000 BP, but neglected to show or discuss insolation changes earlier in the Holocene. These are even more dramatic as shown in figure below. Summer insolation at 50N has decreased by more than 35 w m-2 (!!!) since the early Holocene (10000 BP) and is presently at levels characteristic of the Last Glacial Maximum (19000 BP). The disintegration of the Laurentide ice sheet, previously covering Canada, took place primarily in the period of maximum summer insolation (12000-8000 BP). I’ve shown the scale of modern anthropogenic forcing in red for reference.

In older paleoclimate texts, paleoclimatologists reported signs of “neo-glaciation” during the past 4000 years, consistent with Milankowitch factors.  In the 19th century, ice-rafted debris (IRD) was observed at Hvitarvatn lake for the first time since the LGM due to expanded local glaciers. (This proxy has been repeatedly discussed at Climate Audit.) Varve thicknesses at Hvitarvatn also increased dramatically in the Little Ice Age, reaching their maximum in the 19th and early 20th century. BSi productivity at Hvitarvatn was at its maximum from 9000-5000 BP, slightly after the insolation maximum – presumably delayed until LGM glacier had sufficiently receded.

Climate Audit readers will recall that PAGES2K (2013) used Hvitarvatn data upside-down – interpreting wide varves at the height of the Little Ice Age – as evidence of warmth, rather than the opposite, as I noticed almost immediately – see ^. Aside from the use of data upside down being an embarrassing, almost Mannian, gaffe, one has to wonder at the apparent lack of understanding of underlying data on the part of the multiproxy collaters. I have an identical beef in respect to Baffin Island data. Glaciers in Baffin Island – a past center of Laurentide glaciation – similarly expanded in the Little Ice Age through the 19th century. 19th and early 20th century varve thicknesses from Baffin Island, where the time series data pattern is astonishingly similar to Iceland, are nonetheless interpreted by PAGES2K (and IPCC) as evidence of warmth.

Because tree ring width chronologies were unresponsive to large but slow changes in insolation, Esper et al observed that temperature reconstructions relying on long tree ring chronologies (most of the popular IPCC two millennium chronologies) would be similarly unresponsive. Esper stated this conclusion as follows:

an evaluation of long-term temperature reconstructions, even over the past 7,000 years from across northern Eurasia, demonstrates that TRW-based records fail to show orbital signatures found in low-resolution proxy archives and climate model simulations (Supplementary Fig. S1). These discrepancies not only reveal that dendrochronological records are limited in preserving millennial scale variance, but also suggest that hemispheric reconstructions, integrating these data, might underestimate natural climate variability.

This conclusion impacts PAGES2K, Mann et al 2008 and all other temperature reconstructions relied upon by IPCC.

Norwegian Glacier Equilibrium Lines

Details on the two Norwegian glacier equilibrium line series are shown below (slightly different horizontal scale).  At both locations, glaciers are believed to be absent in the early Holocene (during highest summer insolation) and to have formed around 5000-4000 BP (neo-glaciation).  During the late Holocene, the glaciers expanded until ~2000 BP with maximum Holocene extent in the Little Ice Age – a pattern that is characteristic in many locations. During the 20th century, there has been a noticeable retreat of the glaciers – back to levels characteristic of the early first millennium.

Yamal Treeline

The treeline series illustrated in Esper et al 2012 was derived from Hantemirov and Shiyatov Figure 2 (but excluding its Early Holocene portion). It showed mid-Holocene treelines extended approximately 30 km north of present treelines. However, this 30 km figure represented the northern limit of the survey, NOT the actual Holocene treeline. By the time of Hantemirov’s thesis in 2009, the survey – and the mid-Holocene treeline – had been extended nearly 120 km north of the current treeline (see middle panel). It appears that the Holocene treeline may have been even further north: in 1941, Tikhonov reportedly observed sub-fossil Holocene trees at 70N, approximately 275 km north of the present treeline. So, while Esper et al were right to note that Holocene treeline was further north, their diagram dramatically under-estimated the actual distance further north of the Holocene treeline, not just absolutely, but in respect to what was known in Russian literature at the date of their article.

Note that, in the 20th century, the Yamal treeline finally reversed its long march south, though still located far south of its Holocene location. This reversal corresponds to the 20th century reversal of the equilibrium line of Norwegian small glaciers – neither effect being apparent in the Esper et al figure.

Vinther et al 2009

The long decline in Holocene

Vinther et al 2009 (Nature) is a seminal article on the interpretation of Greenland d18O which makes the popular Alley (2000) temperature reconstruction from GISP2 totally obsolete.  Vinther observed that the elevation of the Greenland ice sheet had decreased substantially over the Holocene and that this had a material impact on d18O values at the summit (where GISP2 and GRIP are located): by flattening out the curve through the Holocene. Vinther observed that elevation changes through the Holocene were negligible at Renland (Greenland) and Agassiz (Ellesmere Island) and proposed (convincingly in my opinion) that the d18O records at these locations provided a more accurate record of climate change through the Holocene, and could even be used to estimate elevation changes at the summit of the ice sheet (where GISP2 was located.) Rather than being stable through the Holocene, Renland d18O showed a steady decline through the Holocene.

 

Conclusion

Over the past two millennia, the Norwegian glacier equilibrium line series in Esper et al Figure S1 (blue in excerpt at right) do have a sort of hockey stick shape that is not derived from ex post screening, stripbark bristlecone ring widths or other Mannian tricks. However, in a longer Holocene context, the reversal is both modest in scale and in a direction that mitigated intensifying neo-glaciation from Milankovitch factors.  One possible interpretation of this data is that anthropogenic CO2 has mitigated and even slightly reverse the Milankovitch forcing into potentially much expanded NH glaciation (compare to Ganopolski’s “near miss” article).

 

By Stephen McIntyre | Posted in Uncategorized | Tagged , , | Comments (19)

A “Good” Proxy on the Antarctic Peninsula?

Jul 8, 2020 – 4:35 PM

Nearly all of the text of this article on an interesting ice core proxy series (James Ross Island) from the Antarctic Peninsula was written in June 2014, but not finished at the time for reasons that I don’t recall.  This proxy was one of 16 proxy series in the Kaufman 12K pdf. 60-90S reconstruction.

I originally drafted the article because it seemed to me that the then new James Ross Island isotope series exemplified many features of a “good” proxy according to ex ante criteria that I had loosely formulated from time to time in critiquing “bad” proxies, but never really codified (in large part, because it’s not easy to codify criteria except through handling data.)

Although this series is in the Kaufman 60-90S reconstruction, its appearance is quite different than the final 60-90S reconstruction: indeed, it has a very negative correlation (-0.61) to Kaufman’s final CPS reconstruction. I’ll discuss that in a different article.

Following is mostly 2014 notes, with some minot updating for context.

Continue reading →

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IPCC AR5 WG2 on Yield Sensitivity: Statistical Malpractice

Mar 2, 2020 – 2:12 PM

This post was written on Aug 12, 2014, but not published until Mar 2, 2020 (today).

One of the signature findings of IPCC AR5 WG2 has been that climate change has already had a negative impact on crop yields, especially wheat and maize. These findings are prominent in the WG2 Summary for Policy Makers and were featured in WG2 press coverage. The topic of crop yields are a specialty of WG2 Co-Chair Christopher Field. Field’s frequent co-author, David Lobell, was a Lead Author of the chapter on Food (chapter 7), which in turn cited and relied on a series of Lobell articles, in particular, Lobell et al (Science 2011, Climate Trends and Global Crop Production Since 1980, pdf), which was a statistical analysis of crop yields from 1980 to 2008 (or to 2002 in some analyses) for four major crops (wheat, maize, rice, soy) for 185 countries.

In the period 1980-2008, both crop yields and temperatures have positive trends (notwithstanding the pause/hiatus in the 21st century). Because both series have positive trends, there is therefore a positive correlation between crop yields and temperatures for the vast majority of crop-country combinations.

Given that both series are going up, it is an entirely valid question to wonder who Lobell and coauthors arrived at their signature negative impact merely by applying elementary statistical methods to annual data of yields, temperature and precipitation. I’ll look at this question in today’s post.

Data

In 2011, I obtained the data for Lobell et al 2011 from lead author Lobell (who undertook at the time to place both data and code online, neither of which appears to be done.) I had asked Lobell to archive code, because it wasn’t entirely clear what he had done. Lobell collated temperature and precipitation data from both UDel and CRU. (For the latter, Lobell used the CRU TS data made famous by the Harry Readme.) In the figure below, I’ve plotted Lobell’s yield and temperature data for the China-wheat combination (both standardised to SD units), as an example of both series going up.

lobell_china_wheat

Lobell regressed Yield (actually log Yield) against time, temperature and precipitation variables, describing the procedure as follows:

Translating these climate trends into potential yield impacts required models of yield response. We used regression analysis of historical data to relate past yield outcomes to weather realizations. All of the resulting models include T and P, their squares, country-specific intercepts to account for spatial variations in crop management and soil quality, and country-specific time trends to account for yield growth due to technology gains (6).

The precipitation and quadratic terms don’t appear to affect the regression very much, i.e. the main effects are delivered by the model in which Yield is regressed against time and temperature as follows:

(1) Yield ~ Year + Temperature

Using conventional regression nomenclature, the regression coefficient b is given by the formula

(2) b= (X^T * X)^{-1} X^T y

where the X matrix of independent variables if {Year; Temperature} and y is the Yield vector.

For convenience (and thus is irrelevant to the point that I’m working towards), normalize the data.

X^T y is simply the vector of correlations of Yield to Time (the normalized trend) and Temperature.

(X^T * X) is nothing more than the correlation matrix between Year and Temperature i.e. the off-diagonal element r is the temperature trend (normalized units) as follows:

| 1 r |
| r 1 |

The calculation of the OLS regression coefficients uses the inverse of this matrix,

| 1 -r | * 1/(1-r^2)
| -r 1 |

The negative term in the off-diagonal means that the OLS coefficient for the regression of Yield onto Time and Temperature is calculated as a function of the correlation between yield and temperature, the trend in yield, the trend in temperature as follows:

b_temperature = 1/(1-r^2) (-r*trend_yield + cor_yield_temp)

In other words, if the correlation between Yield and temperature is less than the product of the trend in yields and trend in temperature (both normalized), then the regression coefficient is negative. This has nothing to do with yields or temperatures, but is a trivial property of the matrix algebra.

As an example, for the Chinese wheat series shown above, although there is a positive correlation between yield and temperature (0.5096), the OLS regression coefficient of a regression of Yield against Year and Temperature results in a negative coefficient. Applying the above formula, the normalized trends (correlations between year and item) for yield and temperature are 0.984 and 0.548, yielding 0.5096- 0.984*0.584 <0.

By Stephen McIntyre | Posted in Uncategorized | Tagged | Comments (38)

Gregory et al 2019: Does climate feedback really vary in AOGCM historical simulations?

Oct 31, 2019 – 1:21 PM

A guest post by Nic Lewis

Introduction

The recent open-access paper Gregory et al 2019 “How accurately can the climate sensitivity to CO2 be estimated from historical climate change?” discusses, inter alia, the use of regression to estimate historical climate feedback. As I wrote in a previous article, Gregory et al. consider a regression in the form R = α T, where T is the change in global-mean surface temperature with respect to an unperturbed (i.e. preindustrial) equilibrium and R is the radiative response of the climate system to the change in T, however caused; α is thus the applicable climate feedback parameter for that cause. The corresponding effective climate sensitivity (EffCS) is then F2xCO2/α  where F2xCO2 is the effective radiative forcing (ERF) for a doubling of preindustrial atmospheric carbon dioxide concentration. Continue reading →

By niclewis | Posted in Uncategorized | Comments (12)

Gregory et al 2019: Unsound claims about bias in climate feedback and climate sensitivity estimation

Oct 17, 2019 – 12:27 PM

A guest post by Nic Lewis

The recently published open-access paper “How accurately can the climate sensitivity to CO2 be estimated from historical climate change?” by Gregory et al.[i] makes a number of assertions, many uncontentious but others in my view unjustified, misleading or definitely incorrect. Perhaps most importantly, they say in the Abstract that “The real-world variations mean that historical EffCS [effective climate sensitivity] underestimates CO2 EffCS by 30% when considering the entire historical period.” But they do not indicate that this finding relates only to effective climate sensitivity in GCMs, and then only to when they are driven by one particular observational sea surface temperature dataset.

However, in this article I will focus on one particular statistical issue, where the claim made in the paper can readily be proven wrong without needing to delve into the details of GCM simulations. Continue reading →

By niclewis | Posted in Uncategorized | Comments (53)

CG2 and Ex Post Picking

Jul 31, 2019 – 6:20 PM

Jul 31, 2019: Noticed this as an unpublished draft from 2014. Not sure why I didn’t publish at the time. Neukom, lead author of PAGES (2019) was coauthor of Gergis’ papers.

One of the longest-standing Climate Audit controversies has been about the bias introduced into reconstructions that use ex post screening/correlation.   In today’s post, I’ll report on a little noticed* Climategate-2 email  in which a member of the paleoclimatology guild (though then junior) reported to other members of the guild that he had carried out simulations to test “the phenomenon that Macintyre has been going on about”, finding that the results from his simulations from white noise “clearly show a ‘hockey-stick’ trend”, a result that he described as “certainly worrying”.  (*: WUWT article here h/t Brandon).

A more senior member of the guild dismissed the results out of hand:  “Controversy about which bull caused mess not relevent.”  Members of the guild have continued to merrily ex post screen to this day without cavil or caveat.

Continue reading →

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Hack, Now Ex-Bellingcat, Gets Climategate Timezones Backwards

Jul 4, 2019 – 10:33 AM

Bellingcat’s Iggy Ostanin, [update: who Eliot Higgins says is now ex-Bellingcat]  recently claimed to have discovered that the nomenclature of Climategate-1 emails was based on Unix timestamps and that the nomenclature proved that Russians hacked CRU from timezone +05:00. Amidst much uninformed hyperventilating. Ostanin’s assertions were swiftly retweeted by Andy Revkin, Roger Harrabin, Ken Rice and many others. However, his claims are backwards – or perhaps, in true Mannian style, upside down.

The connection of CG email nomenclature to Unix timestamps was observed as early as Dec 7, 2009 (see WUWT commenter crosspatch here)m who similarly noticed discrepancies between nomenclature and email times, but concluded that they showed that hacker used a computer set to Eastern North American time (-05:00 Standard).

I pointed the error out on Twitter with technical analysis. I also linked Ostanin to the original WUWT comment making similar point.

Ostanin  responded by claiming that my (correct) replication of CG1 nomenclature was “needlessly complicated” and doubled down with his incorrect assertion that “time seen in hacked email headers is 5 hours behind – to the second – of the time in the decoded email file names”:

Ostanin challenged everyone “to try to see for themselves” – pointing to a internet utility:

After I re-iterated my technical criticism, Iggy stated that he wasn’t “sure if either of [me or Charles Wood] ever came across a Kremlin narrative they didn’t endorse”. Then, in true Mannian (and Eliot Higgins) style, Ostanin blocked me on Twitter.

While it’s a bit absurd to waste time on this trivia, Iggy’s falsehoods remain in circulation. He hasn’t conceded anything. Nor have Revkin, Harrabin, Rice or other re-tweeters conceded that Iggy’s analysis was nonsensical.

In my tweets, I observed that Iggy’s analysis was based on an email sent from GMT timezone and that the 5-hour difference between nomenclature and email time only held for emails from that time zone.  What any competent analyst (and we may safely exclude Iggy from that category) would have done is to compare email timestamp to nomenclature across multiple timezones and Daylight/Standard times. I’ve done so in the table below.

Nomenclature for GMT timezone emails in winter are 5 hours ahead, but only 4 hours ahead in summer. This should have caused Iggy to pause.  Nomenclature for emails sent from Eastern timezone exactly matched the email time – both in Standard (winter) and Daylight (summer) time. Nomenclature for emails sent from Mountain time (two hours behind Eastern) were – 2 hours in both winter and summer.

Ironically, the very first email in the Climategate dossier was sent from Iggy’s Ekaterinaburg (+05:00).  But instead of the nomenclature exactly matching the email time, the nomenclature was 10 hours ahead.

In other words, Ostanin got everything pretty much backwards and upside down. It’s about as bad a bit of analysis as it is possible to imagine. And, instead of simply conceding that he’d made a mistake (which is easy enough to do), Ostanin got belligerent and shut his ears. Unfortunately, Ostanin’s falsehoods are now in circulation and, like Mann’s, will probably fester forever.

 

By Stephen McIntyre | Posted in Uncategorized | Comments (38)