NASA corrects errors in the GISTEMP data

In estimating global average temperatures there are a number of different measures to choose from. The UNIPCC tends to favour the British Hadley Centre HADCRUT data. Many of those who believe in the anthropogenic global warming hypothesis have a propensity to believe in the alternative NASA Goddard Institute for Space Studies data. Sceptics criticize GISTEMP due to its continual changes, often in the direction of supporting climate alarmism.

I had downloaded both sets of annual data in April 2011, and also last week. In comparing the two sets of data I noticed something remarkable. Over the last three years the two data sets have converged. The two most significant areas of convergence are in the early twentieth century warming phase (roughly 1910-1944) and the period 1998 to 2010. This convergence is mostly GISTEMP coming into line with HADCRUT. In doing so, it now diverges more from the rise in CO2.

In April 2011 I downloaded the HACRUT3 data, along with GISTEMP. The GISTEMP data carries the same name, but the Hadley centre now has replaced the HADCRUT3 data set with HADCRUT4. Between the two data sets and over just three years, one would expect the four sets of data to be broadly in agreement. To check this I plotted the annual average anomalies figures below.

The GISTEMP 2011 annual mean data, (in light blue) appears to be an outlier of the four data sets. This is especially for the periods 1890-1940 and post 2000.

To emphasise this, I found the difference between data sets, then plotted the five tear centred moving average of the data.

The light green dotted line shows the divergence in data sets three years ago. From 1890 to 1910 the divergence goes from zero to 0.3 degrees. This reduces to almost zero in the early 1940s, increases to 1950, reduces to the late 1960s. From 2000 to 2010 the divergence increases markedly. The current difference, shown by the dark green dotted line shows much greater similarities. The spike around 1910 has disappeared, as has the divergence in the last decade. These changes are more due to changes in GISTEMP (solid blue line) that HADCRUT (solid orange).

To see these changes more clearly, I applied OLS to the warming periods. The start of the period I took as the lowest year at the start, and the end point as the peak. The results of the early twentieth century were as follows:-

GISTEMP 2011 is the clear outlier for three reasons. First it has the most inconsistent measured warming, just 60-70% of the other figures. Second is that the beginning low point is the most inconsistent. Third is the only data set not to have 1944 as the peak of the warming cycle. The anomalies are below.

There were no such issues of start and end of the late twentieth century warming periods, shown below.

There is a great deal of conformity between these data sets. This is not the case for 1998-2010.

The GISTEMP 2011 figures seemed oblivious to the sharp deceleration in warming that occurred post 1998, which was also showing in satellite data. This has now been corrected in the latest figures.

The combined warming from 1976 to 2010 reported by the four data sets is as follows.

GISTEMP 2011 is the clear outlier here, this time being the highest of the four data sets. Different messages from the two warming periods can be gleaned by looking across the four data sets.

GISTEMP 2011 gives the impression of accelerating warming, consistent with the rise in atmospheric CO2 levels. HADCRUT3 suggests that rising CO2 has little influence on temperature, at least without demonstrating another warming element that was present in early part of the twentieth century and not in the latter part. The current data sets lean more towards HADCRUT3 2011 than GISTEMP 2011. Along with the clear pause from 1944 to 1976, it could explain why this is not examined too closely by the climate alarmists. The exception is by DANA1981 at Skepticalscience.com, who tries to account for the early twentieth century warming by natural factors. As it is three years old, it would be interesting to see an update based on more recent data.

What is strongly apparent from recent changes, is that the GISTEMP global surface temperature record contained errors, or inferior methods, that have now been corrected. That does not necessarily mean that it is a more accurate representation of the real world, but that it is more consistent with the British data sets, and less consistent strong forms of the global warming hypothesis.

Kevin Marshall

How Skeptical Science maintains the 97% Consensus fallacy

Richard Tol has at last published a rebuttal of the Cook et al 97% consensus paper. So naturally Skeptical Science, run by John Cook publishes a rebuttal by Dana Nuccitelli. It is cross-posted at the Guardian Climate Consensus – the 97%, that is authored by Dana Nuccitelli. I strongly believe in comparing and contrasting different points of view, and winning an argument on its merits. Here are some techniques that Dana1981 employ that go counter to my view. That is discouraging the reader from looking at the other side by failing to link to opposing views, denigrating the opponents, and distorting the arguments.

Refusing to acknowledge the opponents credentials

Dana says

…… economist and Global Warming Policy Foundation advisor Richard Tol

These are extracts from Tol’s own biography, with my underlines

Richard S.J. Tol is a Professor at the Department of Economics, University of Sussex and the Professor of the Economics of Climate Change…. Vrije Universiteit, Amsterdam. Formerly, he was a Research Professor (in), Dublin, the Michael Otto Professor of Sustainability and Global Change at Hamburg University …..He has had visiting appointments at ……. University of Victoria, British Colombia (&)University College London, and at the Princeton Environmental Institute and the Department of Economics…….. He is ranked among the top 100 economists in the world, and has over 200 publications in learned journals (with 100+ co-authors), 3 books, 5 major reports, 37 book chapters, and many minor publications. He specialises in the economics of energy, environment, and climate, and is interested in integrated assessment modelling. He is an editor for Energy Economics, and an associate editor of economics the e-journal. He is advisor and referee of national and international policy and research. He is an author (contributing, lead, principal and convening) of Working Groups I, II and III of the Intergovernmental Panel on Climate Change…..

Dana and Cook can’t even get close – so they hide it.

Refusing to link the Global Warming Policy Foundation

There is a link to the words. It goes to a desmogblog article which begins with the words

The Global Warming Policy Foundation (GWPF) is a United Kingdom think tank founded by climate change denialist Nigel Lawson.

The description is the GWPF’s website is

We are an all-party and non-party think tank and a registered educational charity which, while open-minded on the contested science of global warming, is deeply concerned about the costs and other implications of many of the policies currently being advocated.

Failing to allow reader to understand the alternative view for themselves

The Guardian does not link to Tol’s article. The SkS article links to the peer-reviewed paper, which costs $19.95. Bishop Hill blog also links you to Tol’s own blog, where he discusses in layman’s terms the article. There is also a 3 minute presentation video, created by the paper’s publishers, where Tol explains the findings.

Distorted evidence on data access

Dana says

The crux of Tol’s paper is that he would have conducted a survey of the climate literature in a slightly different way than our approach. He’s certainly welcome to do just that – as soon as we published our paper, we also launched a webpage to make it as easy as possible for anyone to read the same scientific abstracts that we looked at and test the consensus for themselves.

Tol says

So I asked for the data to run some tests myself. I got a fraction, and over the course of the next four months I got a bit more – but still less than half of all data are available for inspection. Now Cook’s university is sending legal threats to a researcher who found yet another chunk of data.

The Mystery, threatened, researcher

The researcher is Brandon Shollenberger.

Dana says

In addition to making several basic errors, Tol cited numerous denialist and GWPF blog posts, including several about material stolen from our team’s private discussion forum during a hacking.

Brandon gives a description of how obtained the data at “wanna be hackers?“. It was not hacking, in the sense of by-passing passwords and other security, but following the links left around on unprotected sites. What is more, he used similar methods to those used before to get access to a “secret” discussion forum. This forum included some disturbing Photoshop images, including this one of John Cook, complete with insignia of the Sks website.

A glowing endorsement of counter critiques

Dana says

An anonymous individual has also published an elegant analysis
showing that Tol’s method will decrease the consensus no matter what data are put into it. In other words, his 91% consensus result is an artifact of his flawed methodology.

So it must be right then, and also the last word?

Failing to look at the counter-counter critique

Dana, like other fellow believers, does not look at the rebuttal.

Bishop Hill says

This has prompted a remarkable rapid response from an anonymous author here, which says that Tol has it all wrong. If I understand it correctly, Tol has corrected Cook’s results. The critic claims to have worked back from Tol’s results to what should have been Cook’s original results and got a nonsense result, thus demonstrating that Tol’s method is nonsense.

Tol’s reply today equally quickfire and says that his critic, who he has dubbed “Junior” has not used the correct data at all.

Junior did not reconstruct the [matrix] T that I used. This is unfortunate as my T is online…

Junior thus made an error and blamed it on me.

Demonstration of climate science as a belief system

This is my personal view, not of Tol’s, nor of Sks.

Tol in his short presentation, includes this slide as a better categorization of the reviewed papers.

My take on these figures is that 8% give an explicit endorsement, and two-thirds take no position. Taking out the 7970 with no position gives 98.0%. Looking at just those 1010 that take an explicit position gives a “97.6% consensus”.

I accept Jesus as my Lord and Saviour, but I would declare as bunkum any similar survey that scanned New Testament theology peer-reviewed journals to demonstrate the divinity of Christ from the position taken by the authors. People study theology because they are fellow Christians. Atheists or agnostics reject it out of hand. Many scholars are employed by theological colleges, that exit to train people for ministry. Theological journals would be unlikely to accept articles that openly questioned the central tenets of Christianity. If they did many seminaries (but not many Universities) would not subscribe to the publication. In the case of climatology, publishing a paper openly critical of climatology gets a similar reaction to publishing views that some gay people might be so out of choice, rather than discovering their true nature, or that Vladimir Putin’s annexation of Crimea is not dissimilar to Hitler’s annexation of Sudetenland in 1938.

The lack of disagreement and the reactions to objections, I would interpret as “climate science” being an alternative belief system. People with a superior understanding of their subject area have nothing to fear from allowing comparison with alternative and inferior views.

 Kevin Marshall

 

 

Stephan Lewandowsky – a self-confessed danger to democracy

Australian Climate Madness takes a swipe at Stephan Lewandowsky’s latest taxpayer-funded polemic. This is an extended version of my comment.

Lewandowsky’s sneaky request “to mention only my assistant’s name, Charles Hanich, on the online survey” has particular relevance to what followed. Before Joanne Nova published her “Lewandowsky show skeptics are nutters… post, she contacted a number of skeptic bloggers to search their inbox for Lewandowsky’s survey. There was no mention of his research assistant in the paper, so naturally all the resultant searches drew a blank. On this basis I wrote on 03.09.12:-

The claim in the paper that they contacted five sceptical blogs to improve the spread of views is highly suspect.

It turns out that my suspicions were correct. Stephen Lewandowsky had not contacted any of the skeptic sites, and deliberately kept people in the dark as to this fact.

Lewandowsky posted on 10.09.12 at Shaping Tomorrow’s World

1. When will an apology be forthcoming for the accusations launched against me? And how many individuals should now be issuing a public apology?

To explore the magnitude of this question we must take stock of public statements that have been made about my research. For example, one blogger considered it “highly suspect” whether I had contacted any “skeptic” sites. (emphasis mine)

Linking to my comment, Prof. Lewandowsky, knowing my suspicions to be true, brazenly demands that I apologize for daring to suspect him.

He digs himself a deeper hole by saying later

we now know that the presumed lack of evidence was actually evidence for a measure of carelessness or shoddy record keeping among the individuals contacted.

It gets worse. Prof Lewandowsky co-wrote with John Cook a short pamphlet called The Debunking Handbook.

It’s self-evident that democratic societies should base their decisions on accurate information. On many issues, however, misinformation can become entrenched in parts of the community, particularly when vested interests are involved. Reducing the influence of misinformation is a difficult and complex challenge.

What Lewandowsky engaged in was misinformation. He asked to keep secret his identity, gave obscure (or non-existent) clues to emails and then claimed bloggers “amnesia” when they failed to find emails sent to them by unidentified individual. He did this whilst believing that such misinformation would work to the advantage of himself and his unsupported beliefs, whilst undermining democracy.

He later went onto attack my simple analysis using pivot tables. Yet such analysis revealed much the LOG12 paper omitted. For example

- how few skeptic responses there were (c.15%)

- how few supported many of the conspiracy theories (e.g. Moon landing hoax = 10/1145, AIDS created by US Govt = 9/1145)

- That key to the higher proportion of skeptics supporting conspiracy theories were two rogue responses.

The whole paper is misinformation, aimed at getting an alleged majority to discriminate against those who have alternative points of view. Lack of any counter-balance is the major factor that makes people vulnerable to misinformation. Further research on belief in conspiracy theories would reveal that they are more predominant in communities where there are strong belief systems with enforced dominance.

Kevin Marshall

Anyone who wishes to contact me can do so through the comments. I will not publish any such request made in a non-threatening fashion. I will publish counter-arguments, so that others might compare and contrast for themselves.

The Role of Pivot Tables in Understanding Lewandowsky, Oberauer & Gignac 2012

Summary

Descriptive statistics, particularly in the form of pivot tables enable a bridging of the gap between the public pronouncements and the high level statistical analysis that can only be performed by specialists. In empirically-based scientific papers, data analysis by spread sheet enables the robust questions to be asked by the non-specialist and the expert reviewer alike. In relation to Lewandowsky et. al 2012, it highlights the gulf between the robust public claims and the actual opinion poll results on which it is based.

Introduction

In a blog post “Drilling into Noise” on 17 September, Stephan Lewandowsky (along with co-author Klaus Oberauer) makes an interesting comment

The science of statistics is all about differentiating signal from noise. This exercise is far from trivial: Although there is enough computing power in today’s laptops to churn out very sophisticated analyses, it is easily overlooked that data analysis is also a cognitive activity.

Numerical skills alone are often insufficient to understand a data set—indeed, number-crunching ability that’s unaccompanied by informed judgment can often do more harm than good.

This fact frequently becomes apparent in the climate arena, where the ability to use pivot tables in Excel or to do a simple linear regressions is often over-interpreted as deep statistical competence.

Now let me put this in context.

    The science of statistics is all about differentiating signal from noise. This exercise is far from trivial:

A more typical definition of statistics is

Statistics is the study of how to collect, organize, analyze, and interpret numerical information from data.

So Lewandowsky and Oberauer appear to seem to have a narrow and elitist interpretation.

“it is easily overlooked that data analysis is also a cognitive activity.”

Lewandowsky and Oberauer are cognitive scientists. They are merely claiming that this is within their area of competence.

Numerical skills alone are often insufficient to understand a data set—indeed, number-crunching ability that’s unaccompanied by informed judgment can often do more harm than good.

Agreed – but that implies that what follows should demonstrate something unique, they can only be gained by higher level or “scientific” analysis.

This fact frequently becomes apparent in the climate arena, where the ability to use pivot tables in Excel or to do a simple linear regressions is often over-interpreted as deep statistical competence.

I have not found pivot tables used before to analyse data in the climate arena. Nor have I seen simple linear regressions. The heavyweight statistical analysis from those who dispute the science has centred around one person – Steve McIntyre. In fact, to my knowledge, the first instance of when pivot tables were presented are primary analysis by sceptics was when I published my analysis

I would quite agree that pivot tables are not a replacement for deep statistical analysis. But it has role. My analysis using pivot tables, published on 1st September has a number of things which I identified independently which are not brought out in the original paper. These I present below. Then I will suggest how the reporting in the mainstream media might have been somewhat different if they had seen the pivot table summaries. Finally I will make some suggestions as to how the low level statistical analysis can contribute to relating to more “scientific” statistics.

Analysis using pivot tables

How Many Sceptics?

When I first glanced through the paper at the end of July, I wrote

It was an internet based survey, with links posted on 8 “pro-science” blogs. Five skeptic blogs were approached. As such, one would expect that “pro-science” responses would far outweigh “denialist” responses. I cannot find the split.

On obtaining the data, this was what first looked at. In the posting I looked at the 4 Climate Science questions, classifying into acceptors and rejectors (“denialist”) of the science.


Or summarising into 3 categories


Those who dogmatically rejected every question were outnumbered more than 10 to 1 by those who dogmatically accepted. Those who accept the science comprise three-quarters of the respondents. Most people would believe this to be material to a paper analysing those who reject the science.

NASA faked the moon landing|Therefore (Climate) Science is a Hoax

This is the beginning of the title of the paper. Pivot tables are great analysing this. The row labels are “Climate Science Belief”, the columns are CYMoon, and under “∑ values” enter the count of another column of values.

After a bit of formatting, and three more columns of simple formulas, I got this.


Just 10 out of 1145 respondents agree that NASA faked the moon landings. (I was not the first to publish this result. Anthony Watts piped me by a few hours.)

Strictly this is a claim against the “Climate Change” conspiracy theory CYClimChange and CYMoon. I did this table as well


Of the 64 who strongly accept that the climate change conspiracy theory, just 2 also strongly accept CYMOON. Even worse the title is the other way round. So the sample of those who believe NASA faked the moon landings is just 10. The sample size was just too small to make a prediction. Even worse, you could make the wrong result due to the next issue.

Identification of scam responses

One test was to look at the average agreement to each of 12 conspiracy theories that were independent of the climate area. So I rounded the average response to the nearest whole number for each respondent. And then did a pivot table.


I believe I was the first to identify publically the two that averaged 4 on the conspiracy theories and rejected the climate science. These are the two that Steve McIntyre has dubbed “Super-scammers”.

The biggest conclusion that I see is that the vast majority of respondents, no matter what their views on climate, don’t have much time for conspiracy theories. In fact, if you take out the two super-scammers, the most sceptical bunch are the group that dogmatically reject climate science.

This is confirmed if you take the average conspiracy score for each group.


Taking out the two super-scammers brings the average for the dogmatic rejectors from 1.63 to 1.49. With such small numbers, one or two outliers can have an impact on the data.

Measuring up against the public perception

There were two major newspaper articles that promoted the

The Guardian article on 27th July started

Are climate sceptics more likely to be conspiracy theorists?

New research finds that sceptics also tend to support conspiracy theories such as the moon landing being faked

Even a paper such as the Guardian, which prints all sorts of extremist dogma in denigrating sceptics, would have thought twice about publishing that comment if they had been presented with the tables.

The Telegraph article of 28th August included

“NASA faked the moon landing – Therefore (Climate) Science is a Hoax: An Anatomy of the Motivated Rejection of Science”, was based on a survey of more than 1000 visitors to blogs dedicated to discussion of climate change.

An astute reporter, on the basis of my pivot tables, could reasonably ask Professor Lewandowsky how it follows from just 10 respondents who support the idea that “NASA faked the moon landing” that you can make any sort of prediction about beliefs about climate. The questionnaires were placed on climate blogs, not conspiracy-based blogs, so surely any prediction should be framed the other way round?

It also included

The lead researcher, Professor Stephan Lewandowsky, from the University of Western Australia, said conspiracy theories are the “antithesis to scientific thinking” and those who believe them are more likely to reject the scientific consensus that humans contribute to climate change.

“Science is about weeding out bad ideas,” he told The Daily Telegraph. “With conspiracy theories, you start out with a theory and stick to it no matter what the evidence. So it is not that surprising that conspiracy theorists would not accept scientific propositions … If the scientific evidence is overwhelming and you don’t like the conclusion, you have to find a way to reject those findings.”

An astute reporter, on the basis of my pivot tables, could reasonably ask why Professor Lewandowsky is still sticking to his hypothesis when such small numbers support the wacky conspiracy theories. They may then ask a supplementary question. Given that there were 15 questions on conspiracy theories (14 with results reported), and just 5 on free markets, was not the original purpose to establish the conspiracy theory hypothesis and the secondary one on political orientation?

Suggestions for the Role of Low Level Statistical Analysis

In summary, whilst would quite agreeing that spread sheet analysis using pivot tables are not a replacement for deep statistical analysis there are a number of ways where it can be a powerful aid.

Firstly, it is a quick way of getting a sense of what the data is suggesting. Pivot tables can enable a quick summary visually in lots of different ways. It may need additional classifications, such as my acceptors / rejectors. It also needs thought, and an almost a manic sense of trial and error.

Second, it can give a quick comparison to what is being derived from the higher level statistics or modelling. For scientists it is a way of reviewing the data, to make sure that they have the most important points, and have not gone up blind alleys. For non-scientists (and for those scientists reviewing the work of others) it is a way of quickly getting a sense of whether the conclusions are substantiated by the empirical evidence.

Thirdly, and most importantly, it is a means of communicating to the wider public. It provides a bridge between the mainstream media and the scientists. If climate scientists want to win the trust of the wider public, then they need to relate their work in more intelligible terms, capable of being cross-examined. Instead we have the high level models and a then lot of shouting about how wrong and biased are any criticisms. That leads to a lot of scientists, including Lewandowsky, who are totally incapable of perceiving that they could be wrong, or that there could be even modicum of truth in what the critics say. This denial is best summarized in the graphic displayed in the Lewandowsky and Oberauer posting of the “skeptics” view on recent warming trends. It is a total misrepresentation, used as a means of avoiding intelligent discussion.

 

Kevin Marshall

A Reply to Lewandowsky’s sideswipe

In looking analysing the data on the Lew et al paper I made the following comment.

If you sample some of their articles, you will find a dogmatic defence of climate change, and blocking, editing or denigration views that are contrary to their own. The claim in the paper that they contacted five sceptical blogs to improve the spread of views is highly suspect. Jo Nova contacted 24 such blogs (including all the most prominent ones), with not a single one remembering such an approach. Prof. Lewandowsky is currently refusing to divulge the names of the blogs contacted. As there was no proper control of the answers, there could be rogue results generated.

It turns out that Prof. Lewandowsky’s assistant Charles Hanich did contact 5 “skeptic” blogs with requests. These requests were either ignored or rejected with little or no thought nearly two years ago. On his blog Stephan Lewandowsky stated

At this juncture one might consider a few intriguing questions:

1. When will an apology be forthcoming for the accusations launched against me? And how many individuals should now be issuing a public apology?

To explore the magnitude of this question we must take stock of public statements that have been made about my research. For example, one blogger considered it “highly suspect” whether I had contacted any “skeptic” sites.

It troubled me greatly this comment. Why had I failed to trust the word of a professor of psychology? A science which I have never studied? I will not give excuses, but give the reasons that were going through my mind at the time.

Firstly, I was prejudiced against Prof. Lewandwosky. I had first heard of him in relation to the Peter Gleick affair. This was when a so-called scientist impersonated someone else to fraudulently obtain documents from the Heartland Institute. He was “outed” because the key document – which was fabricated – was in the style of Peter Gleick. Yet, Lewandowsky’s believed Gleick’s lying to defend “science” was on the same moral plane as Churchill’s lying to deceive Hitler. Further, he accepted Gleick’s statement that he was sent the forged document in the post. In my eyes that was a choice between strong circumstantial evidence and the statement of a self-confessed liar. Also, for Gleick, admission of fabrication might be a far more serious crime, than his claim to receiving something in the post gullibly accepting it as genuine. So whatever the truth, there might be motive for an additional lie. Further, I do not believe that climate denial is as evil as Nazism. In fact I happen to believe that the term “climate denial” is a vicious smear.

Secondly, my prejudices were further exaggerated when I came across a climate opinion survey at “Watching the Deniers” blog. I not only answered this opinion survey, but recorded the questions and commented upon them. When I saw the Lewandowsky paper, with the some of the same questions on free markets and conspiracy theories, I erroneously thought that this was the same questionnaire. In fact, the questionnaire I answered is probably a later development of the survey behind the Lewandowsky paper. Looking at the actual questionnaire, my comments can be applied to the earlier and shorter survey.

Thirdly, I saw the paper and read the opening paragraphs. I see Lewandowsky’s belief (and the climate scientists as being) along the lines of climate scientists are the experts with PhDs, and are in strong agreement. I believe that far from the strong foundation sufficient to declare anyone who disagrees a motivated denier of the truth.

Fourthly, I am also prejudiced against using psychology to declare that critics sub-normal after reading in the 1980s about the abuses of psychiatry in the Soviet Union, to consign dissidents to mental institutions. Or the arguments the KGB put forward to dissidents of how they could possibly disagree with the huge consensus. Maybe this is an analogy that Lewandowsky will cry foul as one who knows the subject, but this is the honest truth.

Fifthly, I then looked at the data. I found a number of misleading statements in the paper, including the small minority of skeptic responses; the fact that the typical respondent wanted little or anything to do with any conspiracy theory not related to climate. In the extreme case of the “NASA Faked the Moon Landings” referred to in the title only 10 responses out of 1145 responses agreed with the proposition. Further, the two dogmatic rejecters of climate science I identified (before Tom Curtis) as being likely scammed. In other words, the dogmatic conclusions rested on little or no evidence.

My conclusion was this. Prof. Lewandowsky believes it is alright to lie and smear opponents in his “noble” cause. He has issued a highly prejudiced survey to verify a hypothesis that those who reject what he believes are nutters. He then failed to get a decent sample of skeptics and then failed to filter out the rogue responses. When the vast majority of responses failed to verify his hypothesis, he used the small differences in the minority who believed in conspiracy theories to support his dogmatic conclusions. Yet those could be accounted for by scam responses.

On the basis of all this, I had completely lost trust in any statement that Lewandowsky and his mates wrote. I believe I had more than sufficient grounds for suspecting that he had lied about contacting sceptical blogs.

What this leads me onto is something that Lewandowsky has completely missed. The claim is that we should trust climate scientists, as they are the experts.

But what happens when you betray that trust? Let me give three cases.

1. A business fails to deliver on time and what was specified. Then digs themselves into a deeper hole be making excuses and telling the customer that if they have not broken the small print of the contract. After such an experience would the customer ever trust that business again, even if dealing with a different department or people?

2. Somebody was wrongly convicted of murder due to misinterpretation of the evidence by experts, or tampering of the evidence by the police. After this is exposed, there is no action taken to release the innocent party or to stop these events occurring again. What would happen to people’s trust in the judicial process?

3. After twenty years of marriage, one of the partners sleeps with another. What happens to the trust in the marriage if the guilty partner then makes excuses, including blaming the other?

Betrayal of that trust will lead to the betrayer being viewed in a completely different light by the betrayed party. The betrayed now questions every statement and every motive. Once you have lost people’s trust, it is very hard to regain that trust – a point that Dale Carnegie makes in “How To Win Friends And Influence People”. Shifting blame, or failing to acknowledge fault, will only make matters worse. Yet this is what the climate science community has being doing for years. Look at the skeptic blogs and you will find lots of reasons for questioning the science. Some are valid, some are less valid. It is by a group of people that has, with multiple reasons, lost trust in the “science”. The response of the scientists is to call them names, question their motives and (if you look at the skepticalscience blog) provide feeble and biased excuses. By not acknowledging that differences of opinion are possible, or that the science is weak, or that misinterpretations are possible, they are destroying the trust people have in science.

In short what Lewandowsky has completely missed is that people reject the “science” because of lack of trust in scientists, for reasons that they believe in. His actions and those of climate scientists are just exacerbating the rift between the climate science community and people who live in the real world.

Final Note

I am not a scientist. But I have a degree in economics and worked for over 20 years in industry as a management accountant, mostly within the manufacturing sector. I am a Christian, who believes that people are fallible. That is human beings are prone to error, whether by design or by failing to perceive whether they are wrong. I am certainly fallible. In fact, my best work has often by analysing figures in different ways, wasting my time going up blind allies, learning and eventually getting to better solutions. But I strongly believe that those who believe themselves to be the most infallible are those who are usually the most wrong.

I have used an anonymous handle for various reasons, including that people who support “science” think that is alright to make unsubstantiated character assassinations against those who question them.

Kevin Marshall

Lewandowsky et al. 2012 MOTIVATED REJECTION OF SCIENCE – Part 5 the Missing Links

Jo Nova has now provided the first full list of the survey questions used for the Lewandowsky, Oberauer & Gignac paper, along with a well-written summary. However, there are a number of elements that need to be emphasised

  1. If “climate denial” is on a par with “holocaust” or “smoking” denial, why not start by referencing the clearest statement of the evidence, rather than past opinion surveys? That is, if direct evidence is available, why resort to hearsay evidence?
  2. But if opinion surveys are used, then they should at least be good ones. But the primary references are Anderegg, Prall, Harold, & Schneider, 2010 (Most climate scientists believe in what they do) and Doran & Zimmerman, 2009 (97% of climate scientists = 75/77 cut from >3000 responses).
  3. Even so, surely the association with NASA Moon Landings was correct? After all, the title is “NASA faked the moon landing|Therefore (Climate) Science is a Hoax: An Anatomy of the Motivated Rejection of Science.”
    Not when 93% of all respondents gave it a firm thumbs down.
  4. When Lewandowsky says over >1100 responses, and only talks about those who “reject the science”, it surely implies that all (or at least the vast majority) of responses were from the people he is attacking? Actually, around 15% of responses were from skeptics, in terms of answers to four “climate science” questions. Professional polling organisations in the UK state these figures. But a scientific journal seems not to have insisted.
  5. There are loads of conspiracy theories. But one of the most popular in recent years is something like “Climate denial only exists as a serious force due to significant funding by oil and tobacco interests.” Lewandowsky and his junior partners cannot have missed that one.

The basic psychology behind this can be found in “The Debunking Handbook” on the front page of the skepticalscience website. Here is the justification for lying, ad hom attacks and continued government grants to a failed research program. They know the truth, and are claiming a monopoly of that truth. But to legitimately claim a monopoly it is necessary to show the corollary. The corollary is that every person who disagrees with you is wrong on everything. In empirical sciences this leaves no gap for different interpretations from the same data; no gap for the unexplained; no gap for hypotheses or assumptions to be falsified; and no gap for new data contradicting old data or forecasts. Lewandowsky’s opinion poll applies the truth in the “The Debunking Handbook” to justify one version of climate science having a continued monopoly by showing that opponents are a load of undesirable nutters. It is not just full of gaps. Like past claimants to the throne of dictators of truth, he is more wrong than his detractors.

But if you do not have a monopoly of the truth in climate science, what is the alternative? What if there is a potential future threat, which is very real, but for which there is very little firm evidence? A tentative proposal will be the subject of my next posting.

The Bias of Climatology – Pulling Recent Strands Together

David Evans has provided a succinct explanation of why climate scientists’ theories, ignore some fundamental data. The views that feedbacks amplify the effects of CO2 (see Evans’s diagram below) is due to a highly selective reading of the data in a number of different ways.


Now we need to pull the recent strands together.

On actual temperature history we are getting evermore examples of data manipulation, whether on US temperatures (A Watts), Australian Temperatures (See Jo Nova), or the GISSTEMP global surface temperatures (Steven Goddard).

On past temperature history, we have the famous hockey stick graphs, starting with Mann et al in 1998 and culminating in the recent Gergis et al Australasian temperature reconstruction. All need a combination of one, or a few, very poor data sets that are promoted to prominence by statistical techniques unique to climatologists, and ignoring better quality data sets.

Something else needs to be added to the mix to obtain the high role for feedbacks – climate modelling. If recent temperature trends are exaggerated AND past temperature fluctuations smoothed out, then running a model that tries to look at relative influence of natural and anthropogenic factors on temperature will massively over-estimate the anthropogenic over the natural influences.

But go the other way. Look at the more accurate satellite data for recent temperatures and the temperature rises do not track the CO2 rises nearly so well. Go back to the raw data from the thermometers (adjusting properly for UHI), along with homogenization techniques developed by professional statisticians and the C20th warming deflates.

Then take the widest range of proxy records over a long period (even leave in the lowest quality ones) and suddenly the picture looks very different.

Then look at the role of feedbacks from a number of different perspectives, like Sherwood Idso, (possibly further corroborated by Esper et al 2012) and the real picture becomes clearer. Global average temperatures have increased in the last 200 years. Not quite as much in recent years as the temperature records maintain, but are now significantly higher than in during the 17th century. Furthermore, there is circumstantial evidence that a part of this increase (even up to 0.4 Celsius if non-C02 GHGs are included) has been due to the human greenhouse gas emissions. But this is a curiosity for a few academics to ponder, whilst the thrust of the research effort is put into improving the accuracy and integrity of the data.

Defence of the Consensus

The response of mainstream climatology (and with it a vast array of hangers-on) is not to improve the standards and moderate their wilder comments. Instead it has been to shut down debate by attacking the opponents. Australia has the unfortunate achievement to be home to two of the vilest the proponents of this assault on dissent. Prof Stephan Lewandowsky’s latest instalment is publishing a survey which associates climate skeptics with the worst of the conspiracy theorists. John Cook, a climatologist, ignores expert etymologists to justify calling his site skepticalscience.com

Climatology does not rank as a true science, as it has long since abandoned the search for challenging questions and improvements in quality of answers. Rather than explain the anomalies and meet the challenge of alternative explanations, climatology protects itself by employing intellectual bully-boys.

97% of Climate Scientists claim they are not “Climate Deniers” Survey

In the back of my mind on analysing Charles Hanich‘s bogus Climate & Science questionnaire recently, was another, more prominent, survey. The 2009 questionnaire by Peter T. Doran and Maggie Kendall Zimmerman, amongst scientists, concluded

It seems that the debate on the authenticity of global warming and the role played by human activity is largely non-existent among those who understand the nuances and scientific basis of long-term climate processes. The challenge, rather, appears to be how to effectively communicate this fact to the policy makers and the public who mistakenly perceive debate among scientists.

Laurence Solomon has shown has biased the result actually was. First by excluding scientists who might be give greater emphasis on natural causes, like “solar scientists, space scientists, cosmologists, physicists, meteorologists and astronomers.” Second, by whittling down the 3146 responses from “earth scientists” to just 77, they create an insignificant sample. Here I want to consider some points that can be drawn from the method and the conclusion

Questions do not isolate the trivial from the catastrophic

The Survey Questions were

1. When compared with pre-1800s levels, do you think that mean global temperatures have generally risen, fallen, or remained relatively constant?

2. Do you think human activity is a significant contributing factor in changing mean global temperatures?

Most people would accept that temperatures have risen in the past 200 years. Most climate scientists who are active in the field of researching anthropogenic global warming will tend to think human activity has a significant impact. However, this could not mean as little as 10% or over 100% of recent surface temperature warming could be accounted for by human activity. As such the questions are far from sufficient to establish consensus that there on a high level problem that requires a high level policy response.

Identifiable responses create bias

Laurence Solomon has shown has biased the result actually was. First by excluding scientists who might be give greater emphasis on natural causes, like “solar scientists, space scientists, cosmologists, physicists, meteorologists and astronomers.” Second, by whittling down the 3146 responses from “earth scientists” to just 77, they create an insignificant sample.

However, there is a further element. The responses were identified, hence the ability to classify the core scientists. What if you are a practicing climate scientist, who no longer believes in the scientific case for global warming? The scientist finds themselves in the position of a priest/pastor/minister of religion in the Christian Church who has lost faith. They may enjoy the status, and the work, and the people they work with. With a questionnaire such as this, there is a risk of being “outed”. There are three strategies to adopt. Firstly it is not to respond. Secondly, to respond, but rationalise or lie. The wording of the question allows for rationalising. Thirdly, is to answer truthfully, risking your career, along with possible damage to friendships and co-workers funding. This is a huge issue for opinion surveys on controversial subjects. The best way to get honest answers is to guarantee anonymity, and for the survey to be conducted by an independent polling organisation.

Publishing record is not a good indicator of scientific understanding

Climate science, like in many other empirical research areas, is full of papers with multiple authors. The issues are complex, and the workload enormous, so the bulk of the work is done by the research assistants, and often most of the science. The lead authors may act as a project manager, or even just a name to get the work published. Major journals need articles by big names to maintain readership and prestige. The leading scientists, by publishing in the major journals, and having lots of works cited are able to attract funding for further projects and thus promote the other department members and the prestige of the university or other institution to which they belong. Thus looking to a core group based on publishing record might be misleading. Some of the leading scientists might now be more managers than cutting edge scientists. Others might be so enmeshed in the detail and hard-working, that they might never step back and question the bigger picture.

On the other hand, highly intelligent people who believe that the science is flawed, or dogmatic, will never have the desire to enter the field, or move into other areas when they change their minds. Alternatively, they may stay in the subject, but keep quiet about their views, backing away from publishing.

The Boundaries of Climate Change Denial

Many of the “pro-consensus”, “pro-science” blogs call those who think the science is faulty, flawed, or unsubstantiated, “deniers” or “denialists”, without ever defining the characteristic features actually are. This survey gives us the minimum criteria for knowing that someone is not a denier. It is someone who supports the “mainstream” view that the world has warmed, and that humans are to some extent, part responsible for it. This survey can only be taken as a public proclamation by a small minority that they are true believers.

If, however, the definition of “denier” is anything different then there is the logical possibility that people can be both part of the mainstream and climate change deniers. As such the word “denier” is nothing more than a term of discrimination and abuse by those in the mainstream.

Update

Published in response to an article in Nature, mentioning “Deniers” in the Scientific literature for the first time. Responses by Anthony Watts, Bishop Hill and Warren Meyer.


George Monbiot’s narrow definition of “charlatan”

Bishop Hill quotes George Monbiot

I define a charlatan as someone who won’t show you his records. This looks to me like a good [example]: http://t.co/5hDF57sI

Personally, I believe that for word definitions one should use a consensus of the leading experts in the field. My Shorter OED has the following definition that is more apt.

An empiric who pretends to wonderful knowledge or secrets.

Like John Cook’s definition of “skeptic“, Monbiot’s definition is narrower and partisan. Monbiot was referring to maverick weather forecaster Piers Corbyn. If someone has a “black box” that performs well under independent scrutiny, then they are charlatan under Monbiot’s definition, but not the OED’s. This could include the following.

  • A software manufacturer who does not reveal their computer code.
  • A pharmaceutical company that keeps secret the formulation of their wonder drug.
  • A soft drink manufacturer, who keeps their formulation secret. For instance Irn-Bru®.

The problem is that these examples have a common feature (that Piers Corbyn would claim to share to some extent). They have predictive effects that are replicated time and time again. A soft drink might just be the taste. Climate science cannot very well replicate the past, and predictions from climate models have failed to come about, even given their huge range of possible scenarios. This is an important point for any independent evaluation. The availability of the data or records matter not one iota. It is what these black boxes say about the real world that matters. I would claim that as empirical climate science becomes more sophisticated, no one person will be able to replicate a climate model. Publishing all the data and code, as Steve McIntyre would like, will make as much difference as publishing all the data and components of a mobile phone. Nobody will be able to replicate it. But it is possible to judge a scientific paper on what it says about the real world, either through predictions or independent statistical measures of data analysis.

“Fake Skeptics” – a term of intolerance

Tamino, the handle of blogger Grant Foster, uses the term “Fake Skeptic” to describe those he believes to be wrong. I believe Foster’s first use of the term was in his “Skeptics: Real or Fake?” article of 28th June 2011.

The term is “skeptic” is ambiguous. It is either John Cook’s definition of someone who “considers all the evidence in their search for the truth” or (following the Oxford English Dictionary) it is – more broadly – one who doubts or questions. This I discussed here, a few days ago. But either way, what it says to me is that anyone who dissents knows what the truth actually is, but they pretend otherwise. It is a roundabout way of saying “You are a liar, you know it and pretend otherwise“.

What evidence do I have for this extreme accusation?

  1. Lack of Substantiation by Tamino

    To quote from the article:-


    “I’ve often discussed Arctic sea ice, and specifically mentioned that it’s one of the strongest evidences of global warming. All by itself it’s not absolute proof, but as evidence goes it’s strong. Very strong. It’s also an excellent litmus test to separate real skeptics from fake ones.”

    This is evidence of past warming. The skeptics like Warren Meyer, Joanna Nova, Lord Monckton, Prof Richard Lindzen, Anthony Watts, Bishop Hill (Andrew Montford), Prof Bob Carter and Lord Nigel Lawson of the GWPF, do not deny that the earth has warmed in the last century or so, most of which is in the Northern Hemisphere. They do dispute whether the extreme summer minima of ice was entirely due to global warming (alternatively being due to an influx of warmer currents into the Arctic Ocean, like (maybe) in 1923). What they are all united on is that they deny a future catastrophe. That is, warming will accelerate, with catastrophic consequences for the planet. That is they accept that there was about 0.7 Celsius of warming in the twentieth century, but deny that this century there will be 3 to 6 degrees of warming, with severe climate disruption. Even if this were the case (as Lawson says), the current policies would be both ineffective to combatting the problem and would be economically disastrous.

  2. Tamino perverts the truth

    Grant Foster is highly intelligent and has great skill in statistical analysis. However, he is highly intolerant of those he disagrees with, fails to discourage intolerance in his blog comments and uses his considerable intellectual powers to turn invert empirical reality and defend corrupt science.

In short, Tamino is a climate bully-boy. He does not seek to advance understanding, but seeks to suppress it. He has once before deleted his blog. He should do so again, leaving only an apology.

The views expressed are my own. Tamino is not the only climate bully-boy, but a symbol of it. He is not the worst, but probably the most intelligent. I believe that the intolerance should be met with intolerance. This is simply an extension of the 21st Century British attitudes against discrimination, the older beliefs of fair play and that the best way to understand is to compare and contrast the arguments. Furthermore, modern history shows that those who keenest to suppress dissent have the weakest or most immoral case. I will shortly be inviting Tamino to reply by posting, unedited, on this blog.

Update – cross posted to Tamino’s blog. A sign of a climate bully-boy is that they are cowards underneath. They cannot cope when confronted with the reality of what they are doing. Like in George Orwell’s 1984, they edit reality to make it appear the opposite. The right of reply is yours Tamino. Do you believe in what you are doing, or are you just preaching to the converted and promoting intolerance?

manicbeancounter | May 3, 2012 at 12:13 am | Reply

The term “fake skeptic” is a term of intolerance. [edit]

[ResponseOn the contrary, the term is exactly correct.]

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