In a figure that took considerable work, IPCC AR5 (First Draft) compared 5 regional proxy reconstructions to model output. In Australia, they used the Gergis (Neukom) et al 2012 reconstruction, In South America, they used a Neukom et al 2011 (Clim Dyn) reconstruction. In 2011, Neukom refused to provide me with the data versions used in this article (many of which are not public). I recently wrote to the editor of Climate Dynamics without acknowledgement. Their Table 2 lists 19 “proxies” used in their winter temperature reconstructions – one of which is Law Dome, in a remarkable highly truncated version.
Neukom et al 2011 (Climate Dynamics) has almost as many coauthors (18) as selected winter proxies: R. Neukom, J. Luterbacher, R. Villalba, M. Küttel, D. Frank, P. D. Jones, M. Grosjean, H. Wanner, J.-C. Aravena, D. E. Black, D. A. Christie, R. D’Arrigo, A. Lara, M. Morales, C. Soliz-Gamboa, A. Srur, R. Urrutia, L. von Gunten.
Neukom et al start with 144 climate “sensitive” proxies, from which 20 are selected into their winter network. As one would expect in a paper coauthored or influenced by Luterbacher, some of the “proxies” are not actually proxies, but instrumental records. Three of the “proxies” are long instrumental temperature records. Three other “proxies” are grid cells of v-wind vectors from the CLIWOC/ICOADS database.
Law Dome
In the figure below, I’ve highlighted the Law Dome item in their list of the 19 winter proxies:
For some reason, Neukom used a severely truncated version (only back to 1800(!)) of the Law Dome O18 series.
Neukom had purported to and had been funded to make a comprehensive collection of sh proxies and could hardly have been unaware of the longer available Law Dome O18 record. It’s cited in Neukom and Gergis 2011. Neukom’s coauthor Phil Jones was aware that earlier values of Law Dome were available, as he’d received them from Tas van Ommen in 2003. Plus Law Dome was even discussed in AR4.
And yes, inclusion of Law Dome would have “mattered”. It has an elevated medieval values. In their Australia article, they accepted a reconstruction with only two proxies (Cook’s Tasmania and Oroko tree rings.) So they should have been able to extract a winter SSA reconstruction with the longer available Law Dome reconstruction.
Law Dome is located almost due south of western Australia, half a world away from South America. Readers might well wonder why, in the “peer reviewed literature” being relied upon by IPCC, Law Dome is used as a proxy for South American winter temperature, but not a proxy for nearby Australia. I wonder the same thing.
Screening Procedure
Given the importance of screening in Gergis et al, looking at the corresponding algorithm in Neukom et al 2011 (Clim Dyn) seems timely. They describe their “methodology” as follows:
We established the set of predictors used for our summer and winter temperature reconstructions using two steps.
2.1. Identification of potential summer and winter temperature predictors
Out of the original database of 144 proxies (Tables S1-S3) that are related to SSA climate (e.g. temperature, precipitation or atmospheric pressure), we selected the predictors with temporally consistent and significant correlations with SSA summer or winter temperatures (potential predictor matrices). To evaluate the temporal stability, the 30-year running Spearman correlation coefficients of each proxy series with the 20th century instrumental CRU TS3 grid at the “best location” were calculated. As “best location” we defined the grid cell with the highest absolute correlation with the proxy over the overlapping period (between 70 and 106 years within 1901-2006). If the running correlation curve showed instabilities (i.e. changes in sign, or fluctuations in the coefficient that exceed ±0.2/decade) the relation between the proxy and the predictand was considered not stable and the proxy series was not included into the potential predictor matrix. In total, 44 (27) series were included into the potential predictor matrix for the summer (winter) temperature reconstructions. They are specified in the last two columns of Table S1 (tree ring clusters), Table S2 (individual tree ring records) and Table S3 (other records).2.2. Selection of the final proxy sets
In a next step, we optimized the potential predictor matrices by identifying the optimal subset in terms of pre-defined reconstruction skill measures for each season. Due to computation limitations it was not possible to test all possible combinations of the available 44 (summer) and 27 (winter) temperature predictors. We therefore combined the proxies into meaningful sub-groups of maximum eight records based on their starting years. We then performed the PCR reconstructions and verifications for all possible combination of proxies within the oldest group and selected the combination with the highest skill scores. This set was then combined with all possible combinations of the next younger group and again, the set with the highest skill was evaluated. This procedure was repeated for all sub-groups. Finally, we used the leave-one-out (“add-one-more”) method to test, whether the quality could be further improved by removing (adding) some of the selected (excluded) predictors. For the SSA 5 mean reconstructions (see Table 3 in the main text) we used the average of the RE and r2 scores as measure for the quality. The spatial reconstructions were assessed based on the average number of grid cells with positive REs. We performed the evaluation by computing an SSA mean and a spatial reconstruction with each set and equally weighting both criteria. Independent use of the two criteria lead to two very similar predictor sets for the SSA mean and spatial reconstructions (not shown). Verification of the results by comparing the skill scores of selected subsets with the corresponding results of CPS and RegEM showed that the rankings of the subsets are relatively robust and similar for the three methods (not shown). The final set of 22 (20) summer (winter) temperature proxies and the temporal evolution of the number of predictors are presented in Table 1 (Table 2) and Figure 1 in the main text.
Even if they provided their networks (which they haven’t), this bizarre procedure would not be replicable in finite time. It’s also hard to figure out any conceivable statistical rationale.
There appears to be an interaction between their truncation of Law Dome and their screening procedure. It appears that they began their procedure for the accretion of proxies with the longest proxy group first. They should have included Law Dome in their long network and worked forward. It would also have to be checked in their summer network as well, the long portion of which has only four series: two Quelccaya series (accumulation, d18O), Oroko Swamp from NZ – also used in the Gergis Australian reconstruction and only one “new” series: Laguna Aculeo pigments from von Gunten et al. (2009).
Climate Audit 
29 Comments
“To evaluate the temporal stability, the 30-year running Spearman correlation coefficients of each proxy series with the 20th century instrumental CRU TS3 grid at the “best location” were calculated. As “best location” we defined the grid cell with the highest absolute correlation with the proxy over the overlapping period (between 70 and 106 years within 1901-2006)”
Am I reading that correctly as saying proxies were considered “good” if they had a high correlation on any gridcell thousands of miles away ? (It would be interesting if they could define their teleconnections in advance, or confirm the physical mechanism after “discovering” it). Otherwise it’s just more magic.
My comment was a genuine question. Are they really calculating the proxies correlations using whichever gridcell each proxy had the best correlation against temperature with, regardless of where the cell was ? If so, it would be very interesting to see the distribution of proxy-to-cell distances.
That is how I read it also. Makes no sense at all. Talk about the screening fallacy: not merely selecting proxies which might by change be correlated with temperature, but allowing for the best match of a proxy and any grid cell out of hundreds. This almost guarantees a false inclusion of proxies.
Steve: Mann et al 2008 only did a pick two.
That statement “As “best location” we defined the grid cell with the highest absolute correlation with the proxy over the overlapping period (between 70 and 106 years within 1901-2006).” is very general and leaves the authors (and reviewers) wide open to criticism. If I were reviewing that I would have asked:
(a) over what distance from the nominal location of the proxy were they searching for correlations?
(b) Was there a limit on the distance of the search? If so, it should be clearly stated what the limit is and what the basis is for arguing that the distance used is physically meaningful. If there is no limit on the distance of the search the paper should have been rejected on the grounds of spurious correlation.
(c) did they search for the first significant correlation or keep searching for the best correlation irrespective of distance, or up to some maximum distance?
Not specifically stating the search criteria leaves one wondering why not? It could just be sloppy writing and reviewing, or it could be another pea under the thimble.
I think that fig 2 is from neukom etal 2010, not 2011.
They’re using individual TR records? At least Yad061 was averaged in with a dozen others!
Actually, as the penguin flies, Law Dome is only a quarter of a world from SA, but point well taken. 😉
Steve: in context, “individual” tree ring records are site chronologies.
Hu, you are dragging the sterling reputation of our host’s site into the gutter by using scientifically inaccurate phrasing – alarmists are doomsayers noted for their lack of humor.
You may wish to issue a correction to change the bird or the mode of travel: “as the penguin flies” indeed!
You could say that penguins do fly, just not in the air. They move through water by flapping their wings.
BREAKER BREAKER
ATTN: STEVE
In an op-ed article in Friday’s _Vancouver Sun_, Mike “The Mangler” Mann states that you and Ross receive funds from the Fraser Institute. Is that claim correct?
You have mentioned on numerous occasions that you do not accept funds any public organizations but only donations from private individuals.
You should check this article out. If he is lying, make sure the readers knows this.
Call him out, then gun him down.
Steve: Ross is a fellow of the Fraser Institute and, as a I understand it, is not remunerated by them. I have no connection to the Fraser Institute nor did Mann say this in the article. He describes me as an “energy industry consultant” which I’m not. I’ve worked in the hard-rock mineral exploration business, most recently in gold exploration. Doing work in climate costs me money. As a matter of fact, I haven’t received contributions from corporations or from governments for that matter. Would I refuse a contribution from the insurance companies associated with Kerry Emanuel? The situation hasn’t arisen. If I spent my time responding to every one of Mann’s untruths and disinformation, I’d be doing nothing else.
I have been regular visitor here from square one. The statement in VS implies that you and Ross receive funds from the FI. From the VS:
(Fraser Institute-funded economist Ross McKitrick and energy industry consultant Steve McIntyre)
Most readers of the VS would probably concluded that you receive funds from the FI. Keep in mind that the poeple in Lotus Land aren’t too bright.
You and Ross should send a _short_ letter to the VS with the title, “Setting the Record Straight”.
You can not let the Mangler get away with this. You have to defend yourself. The Mangler and his mob know that most people won’t take the time to fight back.
I am going send a letter to the VS which states the no reputable scientist would never use term “denier”. Indeed, no scientist would never evers use such language against his worst enemy in public discourse.
I am shocked to learn that Michael Mann has a low opinion of us. Steve, however, is not affiliated with Fraser so no doubt Mann will revise his opinion at once. I, on the other hand, have a long and happy affiliation with Fraser as a Senior Fellow. Up until quite recently it was pro bono but time is scarce so I do now ask for an honorarium for some of my services. But I don’t do any climate-related work with them currently, and they don’t fund any of my academic research. Instead, I now have a sizable research grant from another billionaire-backed economics think tank to develop my T3 tax idea. If Mann, or anyone, wants to dig up the nefarious right wing connections to my project sponsor, dig here and here and here and here.
I missed this revelation at the end Ross, until now. Congratulations.
Personally I thought Mann calling SM a ‘climate denier’ was more relevant. When someone says that (about a climate non-denier) it’s akin to them standing up and shouting ‘I’m a fundamentalist!’
I still think it is quite offensive (and meant to be) but at the same time it is staggeringly bizarre.
Steve: Mann has nothing to do with this thread.
Congratulations Steve on more good detective work. When McIntyre is on the job, the Warmists have nowhere to hide their decline,((nothing to see here folks, move along now!)
Your quote from the Neukom paper appears to explain how one could do PCR with proxies that do not extend to the entire period of reconstruction:
It seems that they could do the reconstruction in segments using only the proxies that overlap the period, presumably doing a separate PCR for each segment. However, this would raise a new issue of concatenating the different segments of the reconstructions. I would hope that they didn’t just tack the ends together!
The errors would also jump at the connection points.
There is also a Climategate email in which Neukom tells Phil Jones just how aggressively he tests his “ensembles” of proxies to end up with just the right final recipe:
Neukom to Phil Jones on the juggling of recipes (“ensembles”) to get to just the SH proxy list he wants for the South American reconstruction
The overall method they describe in the quote above is “unprecedented in a thousand years” and when they say “similar” and “relatively robust” but “(not shown)”, check for your wallet and keys, someone is pulling a fast one. What these guys think is “similar” is not the same as in the real world.
Just glad I am not paying their electricity bill to run all of those combos. The magic year 1800 seems to be about as far back as they really want to go in this reconstruction.
That is right in the midst of the Little Ice Age, remember, frost parties on the Thames and all. From there the temperatures triumphally rise like a phoenix into the 19th and
20th centuries. Makes a great visual. I would like to have some clarification on their use of finding the grid cell that maximizes correlation between the proxy and instumental
temperature. If, for instance, the tree rings are near Santiago, Chile, are they looking at cells near Santiago, or somewhere else, say the Falkland Islands, or Tibet? Just how close are the grid cells to the proxies?
A small point, but summer and winter have different consequences on different parts of the globe.
Near the Poles, where there are long summer “days” and long winter “nights” a daily resolution means something rather different to one at the Equator. So, by extension, does a monthly or even a 6-monthly resolution. Mechanisms/responses near Poles might be inapplicable in the Tropics. This is a problem when one aggregates bundles of proxies. The time base can be non-comparable.
A major point has been expressed many times by many others. If, as the Neukom 2011 authors note, only some selected proxies behaved acceptably in the instrumented period, how can one make the giant logic leap that it was these proxies and only these proxies that behaved acceptably before instrumented times, sometimes for several centuries?
Finally, a nit-pick. It is acceptably scientific to use frequent superlatives, as in this passage? “We therefore combined the proxies into meaningful sub-groups of maximum eight records based on their starting years. We then performed the PCR reconstructions and verifications for all possible combination of proxies within the oldest group and selected the combination with the highest skill scores. This set was then combined with all possible combinations of the next younger group and again, the set with the highest skill was evaluated. This procedure was repeated for all sub-groups. Finally, we used the leave-one-out (“add-one-more”) method to test, whether the quality could be further improved by removing (adding) some of the selected (excluded) predictors.” Skill has traditionally been accorded by reviewers and learned readers, though I concede its special meaning in statistics. Quality, however, is more absolute.
I’m probably wrong, but I want to point out again the difference between the 2010 and 2011 papers… http://www.geo.umass.edu/climate/papers2/Neukom_et_al_2010.pdf (your highlighted law dome)
and
Click to access Neukom_Gergis_2011.pdf
Law Dome 112.80 66.77 1370 179b 2005 18O, accumulation, chem.
species.
Van Ommen and Morgan (2010),
Unpublished (M. Curran, personal
communication, 2010)
am I missing something? probably… 😉
and just to add to the mix, the only ‘climategate’ email with neukom is this one:
http://www.ecowho.com/foia.php?file=1901.txt&search=Neukom
Steve: They are different papers. The longer Law Dome series was available for the earlier 2010-written paper. Neukom was supposedly collecting long SH proxies. Law Dome is an obvious one, having been referred to in prior multiproxy studies. Neukom should have used a longer version.
” Due to computation limitations it was not possible to test all possible combinations”
Sorry if this is a daft question. Why can’t they test all possible combinations or at least most?
They can hide the data but can’t run the numbers?
“If the running correlation curve showed instabilities (i.e. changes in sign, or fluctuations in the coefficient that exceed ±0.2/decade) the relation between the proxy and the predict and was considered not stable and the proxy series was not included into the potential predictor matrix. ”
Hang on. The thermometer record is full of inconsistencies and errors. The only hope of getting any signal from the mess is by averaging over the thousands of records in the hope that a lot of the errors will be something like normally distributed and will cancel out.
More over, all we have from CRU is their unverified, processed data since Jones is still playing games and the cat ate the originals.
If, for example some the CRU data has a spurious rise, either as a result of CRUTological manipulations or data sampling errors, this pre-selection will pick out proxies that confirm the spurious rise and reject potentially more accurate proxies.
The “changes in sign, or fluctuations in the coefficient that exceed ±0.2/decade” could just as easily be due issues with the thermometer data as with the proxy.
This method is mathematically formulated confirmation bias.
Much Australian temperature data changed convention from deg F to deg C officially in Sept 1972. The conversion of F to C then back again is ambiguous if there is less than 1 place after the decimal. However, we managed to show that very many – perhaps 30-50% – of official Australian temp records pre-1972 were recorded in whole numbers. This might be one source of difference in error estimates. See
http://joannenova.com.au/2012/03/australian-temperature-records-shoddy-inaccurate-unreliable-surprise/
One would have to examine if this type of complication was present at sea and in other countries. It signals care in the use of USA records collected in F and converted to C.
Same old trick. They find correlations in the instrumental temp period including inverted proxies, then choose those that aggregate to give the flatish historic temps they need. Trouble is the proxies never correlate well with each othe outside the instrumental period chosen. That lack of inter correlation shows that they are not all proxies for the same thing, and they can’t all be proxies for temperature.
Steve: I’d dial back the inverted proxy line of rhetoric. The corals ex ante are believed to have a negative relationship of d18O to temperature so they are not “upside down” in a Mannian sense.
How is it that Steve is doing better science than richly funded academic PhD scientists? And he’s doing this on his own time. In comparison, Gergis et al. were given $300,000 to run their flawed 3-year study. Just boggles the mind, really.
I honestly believe that it should be made a criminal offense to announce via media results of scientific studies prior to the studies being independently checked and verified by relevant experts–too much pseudoscience is being released to the public.
All scientific journals must also make data-sharing a prerequisite for getting published. How do we go about making this a requirement at all scientific journals? Write to our political representatives? Start an online petition? I think this is something realistic that we can change.
Phil, Re money, there could be more than one grant or contract. Perhaps your $340,000 mention is for the first and the $950,000 from the Gergis blog is for one or more of the later. The partner is presumably the Australian Federal Dept of Climate Change, but I can’t see with a short search any category that extends specific research beyond Australia. It might be there, I just can’t see it quickly.
Grants
Title, Role, Funding Source, Scheme, Award Date
Reconstructing pre-20th century rainfall, temperature and pressure for south-eastern Australia using palaeoclimate, documentary and early weather station data. Chief Investigator. AUST RESEARCH COUNCIL. Linkage Projects, 01/01/2009.
Contracts
Title, Role, Funding Source, Award Date
ESTIMATING NATURAL CLIMATE VARIABILITY IN THE AUSTRALASIAN REGION OVER THE PAST 2,000 YEARS: DATA SYNTHESIS FOR THE IPCC 5TH ASSESSMENT REPORT. Chief Investigator.DEPT OF CLIMATE CHANGE. 01/01/2011.
ESTIMATING NATURAL CLIMATE VARIABILITY IN THE AUSTRALASIAN REGION OVER THE PAST 2,000 YEARS: DATA SYNTHESIS FOR THE IPCC 5TH ASSESSMENT REPORT. Chief Investigator. 15/07/2011.
PALAEO RECONSTRUCTION OF RAINFALL AND STREAMFLOW FOR MELBOURNE WATER CATCHMENTS. Chief Investigator. MELBOURNE WATER CORP. 01/04/2012.
Additional Grant and Contract Information
Reconstructing pre-20th century rainfall, temperature and pressure for south-eastern Australia using palaeoclimate, documentary and early weather station data, Australian Research Council Linkage Project LP0990151
http://climatehistory.com.au
From http://www.findanexpert.unimelb.edu.au/researcher/person203094.html
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I seems odd to me that Law Dome is considered “South America” at all, given that it’s in Antarctica.
That varied array of supposed proxies for temperature is what one would expect when a model/reconstruction is over fit with in-sample data. The proxy does not have to be explained in physical terms but merely has to fit the model. I have seen this very process carried out with investment strategies where criterion are used because it provides a large return and not that it makes financial sense.
With 18 coauthors, who I have to assume concur with this selection strategy, the reviewers of the paper, the editors of the journal and the IPCC people reviewing and using this paper, I have to conclude that there are lots of people connected with climate science who have no appreciation what these processes do to the statistics for evaluating a valid proxy. OMG IIWTIT.
The authors’ description of their method sounds more like a recipe for a witches’ brew than a statistical technique. I’m surprised eye of newt and kelp from the belly of a pregnant manta ray were not included.
One Trackback
[…] Comparison to PAGES2K The present dataset is closely related to data used for the South American and Australasian regional PAGES2K reconstruction used in IPCC AR5. I previously discussed the PAGES2K South American reconstruction here. pointing out that it had used the Quelccaya O18 and accumulation data upside-down to the orientation employed by specialists and upside-down to Thompson’s own reports. I also discussed Neukom’s South American network in the context of the AR5 First Draft here. […]