Steig et al 'Antarctica Warming Paper' process is finally replicated, and dealt a blow to "robustness".

Jeff Id emailed me today, to ask if I wanted to post this with the caveat “it’s very technical, but I think you’ll like it”. Indeed I do, because it represents a significant step forward in the puzzle that is the Steig et all paper published in Nature this year ( Nature, Jan 22, 2009) that claims to have reversed the previously accepted idea that Antarctica is cooling. From the “consensus” point of view, it is very important for “the Team” to make Antarctica start warming. But then there’s that pesky problem of all that above normal ice in Antarctica. Plus, there’s other problems such as buried weather stations which will tend to read warmer when covered with snow.  And, the majority of the weather stations (and thus data points) are in the Antarctic peninsula, which weights the results. The Antarctic peninsula could even be classified under a different climate zone given it’s separation from the mainlaind and strong maritime influence.

A central prerequisite point to this is that Steig flatly refused to provide all of the code needed to fully replicate his work in MatLab and RegEM, and has so far refused requests for it. So without the code, replication would be difficult, and without replication, there could be no significant challenge to the validity of the Steig et al paper.

Steig’s claim that there has been “published code” is only partially true, and what has been published by him is only akin to a set of spark plugs and a manual on using a spark plug wrench when given the task of rebuilding an entire V-8 engine.

In a previous Air Vent post, Jeff C points out the percentage of code provided by Steig:

“Here is an excellent flow chart done by JeffC on the methods used in the satellite reconstruction. If you see the little rectangle which says RegEM at the bottom right of the screen, that’s the part of the code which was released, the thousands of lines I and others have written for the rest of the little blocks had to be guessed at, some of it still isn’t figured out yet.”

RegEM Satellite data flow chart. Courtesy Jeff C - click for larger image

With that, I give you Jeff and Ryan’s post below. – Anthony

Antarctic Coup de Grace

Posted by Jeff Id on May 20, 2009

I was going to hold off on this post because Dr. Weinstein’s post is getting a lot of attention right now it has been picked up on several blogs and even translated into different languages but this is too good not to post.

Ryan has done something amazing here, no joking. He’s recalibrated the satellite data used in Steig’s Antarctic paper correcting offsets and trends, determined a reasonable number of PC’s for the reconstruction and actually calculated a reasonable trend for the Antarctic with proper cooling and warming distributions – He basically fixed Steig et al. by addressing the very concern I had that AVHRR vs surface station temperature(SST) trends and AVHRR station vs SST correlation were not well related in the Steig paper.

Not only that he demonstrated with a substantial blow the ‘robustness’ of the Steig/Mann method at the same time.

If you’ve followed this discussion whatsoever you’ve got to read this post.

RegEM for this post was originally transported to R by Steve McIntyre, certain versions used are truncated PC by Steve M as well as modified code by Ryan.

Ryan O – Guest post on the Air Vent

I’m certain that all of the discussion about the Steig paper will eventually become stale unless we begin drawing some concrete conclusions. Does the Steig reconstruction accurately (or even semi-accurately) reflect the 50-year temperature history of Antarctica?

Probably not – and this time, I would like to present proof.


As some of you may recall, one of the things I had been working on for awhile was attempting to properly calibrate the AVHRR data to the ground data. In doing so, I noted some major problems with NOAA-11 and NOAA-14. I also noted a minor linear decay of NOAA-7, while NOAA-9 just had a simple offset.

But before I was willing to say that there were actually real problems with how Comiso strung the satellites together, I wanted to verify that there was published literature that confirmed the issues I had noted. Some references:



(Ground/Satellite Temperature Comparisons)

The references generally confirmed what I had noted by comparing the satellite data to the ground station data: NOAA-7 had a temperature decrease with time, NOAA-9 was fairly linear, and NOAA-11 had a major unexplained offset in 1993.


Fig. 1: AVHRR trend (points common with ground data).

Let us see what this means in terms of differences in trends.


Fig. 2: Difference in trend between AVHRR data and ground data.

The satellite trend (using only common points between the AVHRR data and the ground data) is double that of the ground trend. While zero is still within the 95% confidence intervals, remember that there are 6 different satellites. So even though the confidence intervals overlap zero, the individual offsets may not.

In order to check the individual offsets, I performed running Wilcoxon and t-tests on the difference between the satellites and ground data using a +/-12 month range. Each point is normalized to the 95% confidence interval. If any point exceeds +/- 1.0, then there is a statistically significant difference between the two data sets.


Fig. 3: Results of running Wilcoxon and t-tests between satellite and ground data.

Note that there are two distinct peaks well beyond the confidence intervals and that both lines spend much greater than 5% of the time outside the limits. There is, without a doubt, a statistically significant difference between the satellite data and the ground data.

As a sidebar, the Wilcoxon test is a non-parametric test. It does not require correction for autocorrelation of the residuals when calculating confidence intervals. The fact that it differs from the t-test results indicates that the residuals are not normally distributed and/or the residuals are not free from correlation. This is why it is important to correct for autocorrelation when using tests that rely on assumptions of normality and uncorrelated residuals. Alternatively, you could simply use non-parametric tests, and though they often have less statistical power, I’ve found the Wilcoxon test to be pretty good for most temperature analyses.

Here’s what the difference plot looks like with the satellite periods shown:


Fig. 4: Difference plot, satellite periods shown.

The downward trend during NOAA-7 is apparent, as is the strange drop in NOAA-11. NOAA-14 is visibly too high, and NOAA-16 and -17 display some strange upward spikes. Overall, though, NOAA-16 and -17 do not show a statistically significant difference from the ground data, so no correction was applied to them.

After having confirmed that other researchers had noted similar issues, I felt comfortable in performing a calibration of the AVHRR data to the ground data. The calculated offsets and the resulting Wilcoxon and t-test plot are next:


Fig. 5: Calculated offsets.


Fig. 6: Post-calibration Wilcoxon and t-tests

To make sure that I did not “over-modify” the data, I ran a Steig (3 PC, regpar=3, 42 ground stations) reconstruction. The resulting trend was 0.1079 deg C/decade and the trend maps looked nearly identical to the Steig reconstructions. Therefore, the satellite offsets – while they do produce a greater trend when not corrected – do not seem to have a major impact on the Steig result. This should not be surprising, as most of the temperature rise in Antarctica occurs between 1957 and 1970.


One of the items that we’ve spent a lot of time doing sensitivity analysis is the PCA of the AVHRR data. Between Jeff Id, Jeff C, and myself, we’ve performed somewhere north of 200 reconstructions using different methods and different numbers of retained PCs. Based on that, I believe that we have a pretty good feel for the ranges of values that the reconstructions produce, and we all feel that the 3 PC, regpar=3 solution does not accurately reproduce Antarctic temperatures. Unfortunately, our opinions count for very little. We must have a solid basis for concluding that Steig’s choices were less than optimal – not just opinions.

How many PCs to retain for an analysis has been the subject of much debate in many fields. I will quickly summarize some of the major stopping rules:

1. Kaiser-Guttman: Include all PCs with eigenvalues greater than the average eigenvalue. In this case, this would require retention of 73 PCs.

2. Scree Analysis: Plot the eigenvalues from largest to smallest and take all PCs where the slope of the line visibly ticks up. This is subjective, and in this case it would require the retention of 25 – 50 PCs.

3. Minimum explained variance: Retain PCs until some preset amount of variance has been explained. This preset amount is arbitrary, and different people have selected anywhere from 80-95%. This would justify including as few as 14 PCs and as many as 100.

4. Broken stick analysis: Retain PCs that exceed the theoretical scree plot of random, uncorrelated noise. This yields precisely 11 PCs.

5. Bootstrapped eigenvalue and eigenvalue/eigenvector: Through iterative random sampling of either the PCA matrix or the original data matrix, retain PCs that are statistically different from PCs containing only noise. I have not yet done this for the AVHRR data, though the bootstrap analysis typically yields about the same number (or a slightly greater number) of significant PCs as broken stick.

The first 3 rules are widely criticized for being either subjective or retaining too many PCs. In the Jackson article below, a comparison is made showing that 1, 2, and 3 will select “significant” PCs out of matrices populated entirely with uncorrelated noise. There is no reason to retain noise, and the more PCs you retain, the more difficult and cumbersome the analysis becomes.

The last 2 rules have statistical justification. And, not surprisingly, they are much more effective at distinguishing truly significant PCs from noise. The broken stick analysis typically yields the fewest number of significant PCs, but is normally very comparable to the more robust bootstrap method.

Note that all of these rules would indicate retaining far more than simply 3 PCs. I have included some references:

I have not yet had time to modify a bootstrapping algorithm I found (it was written for a much older version of R), but when I finish that, I will show the bootstrap results. For now, I will simply present the broken stick analysis results.


Fig. 7: Broken Stick Analysis on AVHRR data.

The broken stick analysis finds 11 significant PCs. PCs 12 and 13 are also very close, and I suspect the bootstrap test will find that they are significant. I chose to retain 13 PCs for the reconstruction to follow.

Without presenting plots for the moment, retaining more than 11 PCs does not end up affecting the results much at all. The trend does drop slightly, but this is due to better resolution on the Peninsula warming. The rest of the continent does not change if additional PCs are added. The only thing that changes is the time it takes to do the reconstruction.

Remember that the purpose of the PCA on the AVHRR data is not to perform factor analysis. The purpose is simply to reduce the size of the data to something that can be computed. The penalty for retaining “too many” – in this case – is simply computational time or the inability for RegEM to converge. The penalty for retaining too few, on the other hand, is a faulty analysis.

I do not see how the choice of 3 PCs can be justified on either practical or theoretical grounds. On the practical side, RegEM works just fine with as many as 25 PCs. On the theoretical side, none of the stopping criteria yield anything close to 3. Not only that, but these are empirical functions. They have no direct physical meaning. Despite claims in Steig et al. to the contrary, they do not relate to physical processes in Antarctica – at least not directly. Therefore, there is no justification for excluding PCs that show significance simply because the other ones “look” like physical processes. This latter bit is a whole other discussion that’s probably post worthy at some point, but I’ll leave it there for now.


We’ve also spent a great deal of time on RegEM. Steig & Co. used a regpar setting of 3. Was that the “right” setting? They do not present any justification, but that does not necessarily mean the choice is wrong. Fortunately, there is a way to decide.

RegEM works by approximating the actual data with a certain number of principal components and estimating a covariance from which missing data is predicted. Each iteration improves the prediction. In this case (unlike the AVHRR data), selecting too many can be detrimental to the analysis as it can result in over-fitting, spurious correlations between stations and PCs that only represent noise, and retention of the initial infill of zeros. On the other hand, just like the AVHRR data, too few will result in throwing away important information about station and PC covariance.

Figuring out how many PCs (i.e., what regpar setting to use) is a bit trickier because most of the data is missing. Like RegEM itself, this problem needs to be approached iteratively.

The first step was to substitute AVHRR data for station data, calculate the PCs, and perform the broken stick analysis. This yielded 4 or 5 significant PCs. After that, I performed reconstructions with steadily increasing numbers of PCs and performed a broken stick analysis on each one. Once the regpar setting is high enough to begin including insignificant PCs, the broken stick analysis yields the same result every time. The extra PCs show up in the analysis as noise. I first did this using all the AWS and manned stations (minus the open ocean stations).


Fig. 8: Broken stick analysis on manned and AWS stations, regpar = 8.


Fig. 9: Broken stick analysis on manned and AWS stations, regpar=12.

I ran this all the way up to regpar=20 and the broken stick analysis indicates that 9 PCs are required to properly describe the station covariance. Hence the appropriate regpar setting is 9 if all the manned and AWS stations are used. It is certainly not 3, which is what Steig used for the AWS recon.

I also performed this for the 42 manned stations Steig selected for the main reconstruction. That analysis yielded a regpar setting of 6 – again, not 3.

The conclusion, then, is similar to the AVHRR PC analysis. The selection of regpar=3 does not appear to be justifiable. Additional PCs are necessary to properly describe the covariance.


So what happens if the satellite offsets are properly accounted for, the correct number of PCs are retained, and the right regpar settings are used? I present the following panel:


Fig. 10: (Left side) Reconstruction trends with the post-1982 PCs spliced back in (Steig’s method).

(Right side) Reconstruction trends using just the model frame.

RegEM PTTLS does not return the entire best-fit solution (the model frame, or surface). It only returns what the best-fit solution says the missing points are. It retains the original points. When imputing small amounts of data, this is fine. When imputing large amounts of data, it can be argued that the surface is what is important.

RegEM IPCA returns the surface (along with the spliced solution). This allows you to see the entire solution. In my opinion, in this particular case, the reconstruction should be based on the solution, not a partial solution with data tacked on the end. That is akin to doing a linear regression, throwing away the last half of the regression, adding the data back in, and then doing another linear regression on the result to get the trend. The discontinuity between the model and the data causes errors in the computed trend.

Regardless, the verification statistics are computed vs. the model – not the spliced data – and though Steig did not do this for his paper, we can do it ourselves. (I will do this in a later post.) Besides, the trends between the model and the spliced reconstructions are not that different.

Overall trends are 0.071 deg C/decade for the spliced reconstruction and 0.060 deg C/decade for the model frame. This is comparable to Jeff’s reconstructions using just the ground data, and as you can see, the temperature distribution of the model frame is closer to that of the ground stations. This is another indication that the satellites and the ground stations are not measuring exactly the same thing. It is close, but not exact, and splicing PCs derived solely from satellite data on a reconstruction where the only actual temperatures come from ground data is conceptually suspect.

When I ran the same settings in RegEM PTTLS – which only returns a spliced version – I got 0.077 deg C/decade, which checks nicely with RegEM IPCA.

I also did 11 PC, 15 PC, and 20 PC reconstructions. Trends were 0.081, 0.071, and 0.069 for the spliced and 0.072, 0.059, and 0.055 for the model. The reason for the reduction in trend was simply better resolution (less smearing) of the Peninsula warming.

Additionally, I ran reconstructions using just Steig’s station selection. With 13 PCs, this yielded a spliced trend of 0.080 and a model trend of 0.065. I then did one after removing the open-ocean stations, which yielded 0.080 and 0.064.

Note how when the PCs and regpar are properly selected, the inclusion and exclusion of individual stations does not significantly affect the result. The answers are nearly identical whether 98 AWS/manned stations are used, or only 37 manned stations are used. One might be tempted to call this “robust”.


Let us assume for a moment that the reconstruction presented above represents the real 50-year temperature history of Antarctica. Whether this is true is immaterial. We will assume it to be true for the moment. If Steig’s method has validity, then, if we substitute the above reconstruction for the raw ground and AVHRR data, his method should return a result that looks similar to the above reconstruction.

Let’s see if that happens.

For the substitution, I took the ground station model frame (which does not have any actual ground data spliced back in) and removed the same exact points that are missing from the real data.

I then took the post-1982 model frame (so the one with the lowest trend) and substituted that for the AVHRR data.

I set the number of PCs equal to 3.

I set regpar equal to 3 in PTTLS.

I let it rip.


Fig. 11: Steig-style reconstruction using data from the 13 PC, regpar=9 reconstruction.

Look familiar?

Overall trend: 0.102 deg C/decade.

Remember that the input data had a trend of 0.060 deg C/decade, showed cooling on the Ross and Weddel ice shelves, showed cooling near the pole, and showed a maximum trend in the Peninsula.

If “robust” means the same answer pops out of a fancy computer algorithm regardless of what the input data is, then I guess Antarctic warming is, indeed, “robust”.


Code for the above post is HERE.


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I thought I had a vague idea of what was being said until I read “Bootstrapped eigenvalue and eigenvalue/eigenvector” and realised the whole thing is the world’s most complex ever anagram competition.


Wow – I am thoroughly impressed!
Ryan, I’m sure that the critics will be all over this, but after reading all the comments on Steig, et all on CA – well done sir! As esoteric as some of this is, I can still follow it.

Pieter F

Keep this up and WUWT will be the best science blog for a second year.


It would be interesting to hear Eric Steig’s comments on all this. He must surely be back from his 3 months in Antarctica now. Perhaps you could ask him.

Dave Wendt

Great work! I hope you plan on submitting this for publication to the same folks that so eagerly offered Steig et al a soapbox to trumpet their obviously less worthy work. Of course, if they do actually to publish it, I’ll owe you a six pack of Guinness, ’cause I’m betting their bias won’t allow them to do it.

Frederick Michael

It’ll be interesting to see if Steig can mount a defense of using only 3 PCs. I’m betting he won’t even bother — either ignore you or reply ad hominem. The intellectual community will, despite their biases, step up (I think/hope).

John F. Hultquist

When this paper by Steig et al. was first being discussed I think I wrote something to the effect that in some types of analyses (socio/economic) where the first few components do have a meaningful interpretation one should go beyond those with caution, but in this case it shouldn’t matter. That was meant to imply that one should use all that helped in the reconstruction. Many years have passed since I’ve worked with such techniques (punched cards on an IBM 360) but I’ve retained just enough to appreciate what you have done. You have done an amazing amount of work. Also, I’m amazed that I can follow along. Must be your excellent writing skills. Good job, John.

David Ball

Excellent job on a herculean task!!! What we need is a brave journalist to risk his livelihood to hand this to the editor/producer. I happen to know the planet is cooling. Last night I awoke to find 2 feet of ice in my bed. Both of them belonged to my wife. 8^]


Somewhere in all this there must be a joke about how many PHD’s it takes to read a thermometer.
Why is measuring temperature such a pseudoscience? If an accurate answer is so important lets develop some new temp stations recalibrate them once or twice a year and take an ave temp. Remove the outliers and voila we have the answer of it getting colder or hotter over some arbitrary timespan. Lets find a way to calibrate the satellite data with high altitude balloons or something.
To me if you have to apply a multitude of algorithms to it the data is not even worth using. We are ultimately talking about measuring temps not tweaking an atom smasher to recreate the big bang. Why is this so hard?

Richard deSousa

Steig had a reputation of being a nice guy but hanging around Michael Mann has tarnished his reputation.


I think it should be added that there is cooling instead of warming, if the starting date is shifted a few years forward, falsifying the CO2 thesis even more drastically.


@ FatBigot (21:19:30) :
I believe the Jackson article referenced in the text is: Stopping Rules in Principal Components Analysis: A Comparison of Heuristical and Statistical Approaches, Donald A. Jackson (1993) which corresponds to the referenced url:

Mike McMillan

FatBigot (21:19:30) :
I thought I had a vague idea of what was being said until I read “Bootstrapped eigenvalue and eigenvalue/eigenvector” and realised the whole thing is the world’s most complex ever anagram competition.

I’ve always had trouble with eigenvalues, too. I do remember that in “No Way Out” while looking for who killed Gene Hackman’s mistress, the CIA took a throwaway Polaroid backpaper, kicked up the eigenvalue, and came up with a studio quality photo of Kevin Costner. Impressive technology.
This is similarly a great piece of crime scene investigation.
It’s nice to know we have a few folks who aren’t gee-whizzed by the “real” scientists’ techspeak. Excellent work, Jeff, Jeff, and Ryan.

steptoe fan

After the Seattle Times ran a story giving coverage to this fiasco ( Steig et al ), I emailed both the paper and the ” scientist ” protesting the very unscientific methods and conclusion of this ” piece of work “. I received no response from the individual and the Times editor ignored my email
This man gives computer science and the state of Washington no service.
Perhaps readers here would like to drop a postal mail to the individual and invite him to come here and defend his ” slop ” ?
Eric J. Steig
Department of Earth and Space Sciences and Quaternary Research Center, University of Washington, Seattle, Washington 98195


Saw a report yesterday in the UK about climate protestors in Washington, angry about coal as a fuel, who were trying to close down a power generatation plant. James Hansen was amongst them.
I noticed that there was snow in Washington. Was this recent? Is snow in mid-May usual in this part of the world?

Evan Jones

If an accurate answer is so important lets develop some new temp stations recalibrate them once or twice a year and take an ave temp.
No, it’s far more important to spend that huge pile of money they just got to spruce up the home office in Asheville.


Great post. Of course what was done at the end should have been the very first step performed by the Steig team. “If we create a plausible data set, then run our algorithms on it, do we more or less get a summary of the original data set back out”. That is science. Instead it went through the meat grinder and came out with the answer they wanted and that of course was enough to get it published.


While looking at previous posts on this, a key issue identified was that 35% of the weather stations were in the peninsula which is 5% of the land mass. We know that the peninsula is warming for other (including Urban Heat Island) effects. Another issue was that four weather stations on offshore islands were thrown in for good measure. As I understood it, the approach of Steig was to essentially pretend that the weather stations were evenly spread.
This of course seems like a nonsensical approach to the average layman. Many posters here likened it to trying to map the climate history of the United States based on temperatures in Florida.
So this gets me to the question. This article would seem to imply that the underlying methodology is sound, but that the statistical manipulation is wrong.
… or are both the underlying methodology and the statistical manipulation wrong?
In any case, incredible work.


As suspected it is the Steig methodology that is flawed.
Well done to everyone for a great effort.
Anthony should consider giving you guys a medal for this work.


Impressive on all fronts – I hope this work can find its way to publication.


So is Steig’s work/publication in Nature, now falsified?.. this is really the crucial question.

UK Sceptic

I haven’t a clue what most of that means and my eyes began to glaze over after the first couple of graphs. However, I was able to conclude that the warmists have been caught cooking the books yet again.
Well done!

Chris H

Fantastic work! Now if only the Establishment would admit this work even exists. I guess no chance of getting Nature to retract Steig’s paper….

Chris H

IMHO it puts Steig’s work in nearly as bad light as Mann’s infamous hockey stick. Which is to say it’s a badly done analysis, which tends to give the Alarmists the answer they want (i.e. more warming than is likely to have actually occurred).
Whether or not this was intentional, one can only speculate. I guess Steig’s response (or lack thereof) will determine that.


I am speculating, but I sense that the real story here is how the data was Mann-handled into fitting the theory, rather than Steig’s work. RegEM and PCA were the root of the hockey stick, I believe it was shown that the process mined data for hockey sticks, now a fathered-out-of-wedlock version of the same thing produces a predetermined result in the Antarctic. I sense a pattern.
Aren’t there lots of gaps in tropical troposphere radiosonde data, and an overlap of satellite and balloon data sets? The script almost writes itself. Tropical troposphere hotspot revealed!!! Mike Mann et al.


Wow. Just like the hockey stick. No matter what you put in…..


Excellent. Objective efforts clearly explained (such as this one) advance knowledge (which is the highest praise I can give).

Leon Brozyna

Perhaps Steig et al should take their books and consider taking part in a reality show. Something along the lines of FOX Broadcasting’s Hell’s Kitchen. Perhaps they could compete against Mann et al.
Reading this gave me déjà vu all over again. ☺

I hope this gets a writeup like Bishop Hill’s Caspar and the Jesus Paper so that all those whose eyes glaze over with eigenvalues can come to understand enough of the science as well as the story.
Thank you Jeff Id Jeff C Ryan O and all who’ve done the sterling work. We maybe should establish an alternative Nobel prize here… though really, I’d rather the real Nobel Prize got freed from its corruption by work like this.
Why are all the heads of official science establishments on the gravy train?

Ron de Haan

This is a job well done.
It’s hard proof of the fact that the scientific world is infected with a breed of scientists that have sold their integrity to a political attempt to achieve absolute power.
Let us be clear about the consequences for all of us if this power grab succeeds.
It’s tyranny, nothing more nothing less.
Who would have expected that 30 years after the fall of the Iron Curtain, which event ended te Cold War, our freedom once again is threatened, this time by an enemy from within?
We now have a clear example how the data was falsified to serve the outcome of a warming Arctic.
Let’s hope we will be able to use this research against those who decided to serve the dark agenda of Anthropogenic Global Warming.
The publication here at WUWT is an important step because it shows that people will not bend to tyranny of any kind.
It’s a clear statement that falsified science, doctrines and political schemes based on lies and manipulation is not accepted.

Adam Soereg

The most outstanding problem with Steig et al [2009] reconstruction is that the whole study completely ignores the fact that in the last 20-25 years you can’t find any warming in the Antarctic region. Even the Antarctic penisula shows no warming after a very steep temperature increase in the 1970’s. See the temperature records of some stations, Rothera Point for example.
In Steig et al the whole continent has an almost homogeneus warming trend of about 0,1°c/decade for the 1957-2006 period as shown above. According to the available instrumental data, this statement is ridiculous. The Amoundsen-Scott Base a South Pole, the Russian station of Vostok and the Australian Casey station near the Ross Ice Shelf are showing a cooling trend for the period examined by Steig et al. The only area on the whole Antarctic continent which has warmed significantly is the Antarctic Penisula. It is less than 5% of the total area of the Antarctic continent. And don’t forget: even the penisula shows no net warming in the last 25 years.
More than 10 years after the first appearance of the widely discredited MBH98 hockey stick, the Steig et al paper has brought climate science to a new low. How can a ‘high-profile’ scientific journal like Nature publish such a nonsense?
This paper has been peer-reviewed like the ‘hockey paper’ in 1998. It is quite clear that peer-review cannot guarantee good science. One more thing: the findings of the MBH98 study were used as smoking gun evidence in the IPCC Third Assessment Report. I bet that the ‘precious’ work of Steig and his colleagues will appear in the next IPCC report. Any opinion?

Claude Harvey

For the vast majority of the voting public, any attempt to judge the validity of any of this would be like serving on a jury in a trial where all the attorneys and their witnesses spoke only Greek. The jury would be left searching for clues on the expressions of the witnesses’ faces. In such a case, the jury would likely end up simply believing whatever they chose to believe regardless of the testimony (“We liked his tie!”).
Unless this paper can gain an official seal of authenticity in some quarter recognized by the public (The Goracle has his Nobel Prize), it is just so much spit in the ocean from a public perspective.
That said, I applaud this mountain of work for its own sake in the pursuit of scientific truth.

Indiana Bones

I rather like the Webster 5th definition of *ROBUST*:
” of, relating to, resembling, or being a relatively large, heavyset australopithecine (especially Australopithecus robustus and A. boisei) characterized especially by heavy molars and small incisors adapted to a vegetarian diet.”
I recommend inserting this verbiage wherever the alarmists use rob-us-t…


In real science, the refusal of a scientist to release the methods used to make a finding is reason enough to impeach the credibility of the finding and the scientist claiming to have the finding.
In AGW, on the other hand, secrecy and non-reproducible work is just the way things are.


I wonder if the magic number 3 gives the highest possible trend. Ought to graph number of PC’s verses trend.

Bill Illis

Good job Jeff Id (and to the others which helped).
Considering how “herculean” (someone said) this effort was, it it clear this paper did not receive a proper peer review in the sense that one would think – some kind of replication of the methods.
Not that peer review needs to involve a great measure of replication, but when one is doing a novel technique, using novel data about something this important to a scientific field, Nature should not be putting it on its front cover unless at least one of the reviewers can say “it looks like the methodology was done correctly.”
Well, it wasn’t (double-checked or done correctly).
And it has happened before in this field and large parts of it are based on these novel mathematical calculations that are not replicated or tested in a experimental sense. The more we dig into the calculations and methodologies and check the experimental/empirical data, the less sense one gets that the science is being done objectively.


You ask how high profile publications can participate in promoting AGW frauds.
Historians will puzzle over how AGW became such a fixation and was able to mislead and dominate public policy for many years.
Social movements like this are very corrosive and impose a high price. The bad ideas developed to solve non-existent problems come at the expense of good ideas.
AGW profiteers are taking advantage of the distractions they have caused very well.

Ellie in Belfast

UK Sceptic (02:50:07) :
“….my eyes began to glaze over after the first couple of graphs.”
Yeah, I have the same problem, but glad I persevered. This one really could do with an executive summary.

John W.

Very nicely done.

John Galt

Can somebody tell me what exactly is the definition of academic fraud and why Steig’s work does not qualify?

John Galt

OT: Global warming may be twice as bad as previously expected
By Doyle Rice, USA TODAY
Global warming will be twice as severe as previous estimates indicate, according to a new study published this month in the Journal of Climate, a publication of the American Meteorological Society.
Because the computer models tell them so!


All I see is tha any type of reconstruction, with all corrections you want, still give a warming Antarctica. When I think how many time I’ve read here and there that this conclusion was “obviously false” or “proved that data were manipulated”, I seriously wonder how the final result could be turned into a “victory” of some sort… A “coup de grace”? For skeptics?

Mr Lynn

Claude Harvey (05:00:25) :
For the vast majority of the voting public, any attempt to judge the validity of any of this would be like serving on a jury in a trial where all the attorneys and their witnesses spoke only Greek. . .
Unless this paper can gain an official seal of authenticity in some quarter recognized by the public (The Goracle has his Nobel Prize), it is just so much spit in the ocean from a public perspective. . .

Exactly. So long as the AGW establishment has a stranglehold on the ‘official’ scientific bodies (AAAS, NSF, NASA, NOAA, the professional societies, etc.) and the peer-reviewed journals, critiques such as this one will be dismissed by the media as the ravings of an Internet fringe, and the public at large will follow blindly along.
The big question for the scientists who have not jumped onto the AGW gravy train should be this: “How do we break that stranglehold?”
I hope that the authors of the post above will submit it to Nature, and if rejected, take whatever steps they can to challenge that rejection.
Is it time for legal action, on grounds that learned societies and journals have broken with their solemn obligation to scientific objectivity and have instead become handmaidens of a political agenda?
It might be futile, but could get media attention. And a lot more scientists now sitting on the sidelines might be encouraged to speak up within their associations and departments.
Tuesday the President of the United States said this:
“We have over the course of decades slowly built an economy that runs on oil. It has given us much of what we have — for good but also for ill. It has transformed the way we live and work, but it’s also wreaked havoc on our climate.”
That last of course is simply not true. But how can Joe Public counter it? The stakes are becoming enormously high. The further the US and other Western governments pursue the ‘climate change’ chimera, the more damage they will do to their national economies, our standard of living, and ultimately our very freedom and autonomy.
Laymen cannot turn this around. It’s up to the scientists who understand arcana like “Bootstrapped eigenvalue and eigenvalue/eigenvector” (thanks FatBigot!) to break through and challenge the dominant establishment. Once that happens, the media will start to pay attention, and if they do, then the politicians will have to as well.
/Mr Lynn

John Silver

Lucy Skywalker (04:08:46) :
“We maybe should establish an alternative Nobel prize here… though really, I’d rather the real Nobel Prize got freed from its corruption by work like this.”
Surely you are not mistaken the peace prize (always a bad joke from Oslo, Norway) with the real prices? (Royal Swedish Academy of Science, Stockholm, Sweden)

You warned me that it was a bit technical so I don’t want to waste too much of anyone’s precious time but can someone tell me what are the physical realities that Steig correlates with his three PCs and (how) does he justify that the others are not significant – we are talking about 0.07degC/decade! Is it likely that he did an analysis similar to the above and then selected the one that best fit the AGW models? This kind of forensics should be done on all the AGW models.

John Silver

I forgot: The Norwegian Nobel Committee (Den norske Nobelkomité) awards the Nobel Peace Prize each year. Its five members are appointed by the Norwegian parliament.
They are politicians!! Got that?

Adam Soereg

A correction to my previous comment:
I mentioned cooling trends near the Ross Ice Shelf, but the Casey station is about 1000 kms away from there. <a="; McMurdo is located next to the ice shelf and shows no significant trend in the last 30 years.
The Casey station is on the edge of the East Antarctic Ice Sheet, and shows a clear cooling trend since about 1980: see this graph.


Ah, but Ryan’s methodology differs from that of Steig and Mann. The two analyses therefore cannot be compared. We have apples vs. oranges.
That will be the response from the team. The fact that Steig’s methods are held back or incompletely described will not be included in any response.
Jeff Id and Ryan O, if they try to publish their study in Nature will have languish it for a year and then receive a rejection.
The best route is to submit it elsewhere, where it has a chance of being accepted. E&E may not have the distribution and “pretige” of Science or Nature, but it will provide a citable reference for posterity – a reminder in 50 years that not all of science was corrupted by AGW nonsense.

Wow thats what I call dropping the hammer, facts wise. It took me some time to read all the information. Maybe I should do what congress is doing.