William Connolley is on side of anti-science not the late Bob Carter

In the past week there have been a number of tributes to Professor Bob Carter, retired Professor of Geology and leading climate sceptic. This includes Jo Nova, James Delingpole, Steve McIntyre, Ian Pilmer at the GWPF, Joe Bast of The Heartland Institute and E. Calvin Beisner of Cornwall Alliance. In complete contrast William Connolley posted this comment in a post Science advances one funeral at a time

Actually A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it, but I’m allowed to paraphrase in titles. And anyway he said it in German, naturally. Today brings us news of another such advancement in science, with the reported death of Robert Carter.

Below is a comment I posted at Climate Scepticism

I believe Max Planck did have a point. In science people tenaciously hold onto ideas even if they have been falsified by the evidence or (as more often happens) they are supplanted by better ideas. Where the existing ideas form an institutionalized consensus, discrimination has occurred against those with the hypotheses can undermine that consensus. It can be that the new research paradigm can only gain prominence when the numbers dwindle in the old paradigm. As a result the advance of new knowledge and understanding is held back.

To combat this innate conservatism in ideas I propose four ideas.

First is to promote methods of evaluating competing theories that are independent of consensus or opinion. In pure science that is by conducting experiments that would falsify a hypothesis. In complex concepts, for which experiment is not possible and data is incomplete and of poor quality, like the AGW hypothesis or economic theories, comparative analysis needs to be applied based upon independent standards.

Second is to recognize institutional bias by promoting pluralism and innovation.

Third is to encourage better definition of concepts, more rigorous standards of data within the existing research paradigm to push the boundaries.

Fourth is to train people to separate scientific endeavours from belief systems, whether religious, political or ethical.

The problem for William Connolley is that all his efforts within climatology – such as editing Wikipedia to his narrow views, or helping set up Real Climate to save the Mannian Hockey Stick from exposure of its many flaws – are with enforcing the existing paradigm and blocking any challenges. He is part of the problem that Planck was talking about.

As an example of the narrow and dogmatic views that Connolley supports, here is the late Bob Carter on his major point about how beliefs in unprecedented human-caused warming are undermined by the long-term temperature proxies from ice core data. The video quality is poor, probably due to a lack of professional funding that Connolley and his fellow-travellers fought so hard to deny.

Kevin Marshall

ATTP on Lomborg’s Australian Funding

Blogger …and then there’s physics (ATTP) joins in the hullabaloo about Bjorn Lomberg’s Lomborg’s Consensus Centre is getting A$4m of funding to set up a branch at the University of Western Australia. He says

However, ignoring that Lomborg appears to have a rather tenuous grasp on the basics of climate science, my main issue with what he says is its simplicity. Take all the problems in the world, determine some kind of priority ordering, and then start at the top and work your way down – climate change, obviously, being well down the list. It’s as if Lomborg doesn’t realise that the world is a complex place and that many of the problems we face are related. We can’t necessarily solve something if we don’t also try to address many of the other issues at the same time. It’s this kind of simplistic linear thinking – and that some seem to take it seriously – that irritates me most.

The comment about climatology is just a lead in. ATTP is expressing a normative view about the interrelationship of problems, along with beliefs about the solution. What he is rejecting as simplistic is the method of identifying the interrelated issues separately, understanding the relative size of the problems along with the effectiveness and availability of possible solutions and then prioritizing them.

This errant notion is exacerbated when ATTP implies that Lomborg has received the funding. Lomborg heads up the Copenhagen Consensus Centre and it is they who have received the funding to set up a branch in Australia. This description is from their website

We work with some of the world’s top economists (including 7 Nobel Laureates) to research and publish the smartest solutions to global challenges. Through social, economic and environmental benefit-cost research, we show policymakers and philanthropists how to do the most good for each dollar spent.

It is about bringing together some of the best minds available to understand the problems of the world. It is then to persuade those who are able to do something about the issues. It is not Lomborg’s personal views that are present here, but people with different views and from different specialisms coming together to argue and debate. Anyone who has properly studied economics will soon learn that there are a whole range of different views, many of them plausible. Some glimpse that economic systems are highly interrelated in ways that cannot be remotely specified, leading to the conclusion that any attempt to create a computer model of an economic system will be a highly distorted simplification. At a more basic level they will have learnt that in the real world there are 200 separate countries, all with different priorities. In many there is a whole range of different voiced opinions about what the priorities should be at national, regional and local levels. To address all these interrelated issues together would require the modeller of be omniscient and omnipresent. To actually enact the modeller’s preferred policies over seven billion people would require a level of omnipotence that Stalin could only dream of.

This lack of understanding of economics and policy making is symptomatic of those who believe in climate science. They fail to realize that models are only an attempted abstraction of the real world. Academic economists have long recognized the abstract nature of the subject along with the presence of strong beliefs about the subject. As a result, in the last century many drew upon the rapidly developing philosophy of science to distinguish whether theories were imparting knowledge about the world or confirming beliefs. The most influential by some distance was Milton Friedman. In his seminal essay The Methodology of Positive Economics he suggested the way round this problem was to develop bold yet simple predictions from the theory that, despite being unlikely, are nevertheless come true. I would suggest that you do not need to be too dogmatic in the application. The bold predictions do not need to be right 100% of the time, but an entire research programme should be establishing a good track record over a sustained period. In climatology the bold predictions, that would show a large and increasing problem, have been almost uniformly wrong. For instance:-

  • The rate of melting of the polar ice caps has not accelerated.
  • The rate of sea level rise has not accelerated in the era of satellite measurements.
  • Arctic sea ice did not disappear in the summer of 2013.
  • Hurricanes did not get worse following Katrina. Instead there followed the quietest period on record.
  • Snow has not become a thing of the past in England, nor in Germany.

Other examples have been compiled by Pierre Gosselin at Notrickszone, as part of his list of climate scandals.

Maybe it is different in climatology. The standard response is that the reliability of the models is based on the strength of the consensus in support. This view is not proclaimed by ATTP. Instead from the name it would appear he believes the reliability can be obtained from the basic physics. I have not done any physics since high school and have forgotten most of what I learnt. So in discerning what is reality in that area I have to rely on the opinions of physicists themselves. One of the greatest physicists since Einstein was Richard Feynman. He said fifty years ago in a lecture on the Scientific Method

You cannot prove a vague theory wrong. If the guess that you make is poorly expressed and the method you have for computing the consequences is a little vague then ….. you see that the theory is good as it can’t be proved wrong. If the process of computing the consequences is indefinite, then with a little skill any experimental result can be made to look like an expected consequence.

Climate models, like economic models, will always be vague. This is not due to being poorly expressed (though they often are) but due to the nature of the subject. Short of rejecting climate models as utter nonsense, I would suggest the major way of evaluating whether they say something distinctive about the real world is on the predictive ability. But a consequence of theories always being vague in both economics and climate is you will not be able to use the models as a forecasting tool. As Freeman Dyson (who narrowly missed sharing a Nobel Prize with Feynman) recently said of climate models:-

These climate models are excellent tools for understanding climate, but that they are very bad tools for predicting climate. The reason is simple – that they are models which have very few of the factors that may be important, so you can vary one thing at a time ……. to see what happens – particularly carbon dioxide. But there are a whole lot of things that they leave out. ….. The real world is far more complicated than the models.

This implies that when ATTP is criticizing somebody else’s work with a simple model, or a third person’s work, he is likely criticizing them for looking at a highly complex issue in another way. Whether his way is better, worse or just different we have no way of knowing. All we can infer from his total rejection of ideas of experts in a field to which he lacks even a basic understanding, is that he has no basis of knowing either.

To be fair, I have not looked at the earlier part of ATTP’s article. For instance he says:-

If you want to read a defense of Lomborg, you could read Roger Pielke Jr’s. Roger’s article makes the perfectly reasonable suggestion that we shouldn’t demonise academics, but fails to acknowledge that Lomborg is not an academic by any standard definition…….

The place to look for a “standard definition” of a word is a dictionary. The noun definitions are


8. a student or teacher at a college or university.

9. a person who is academic in background, attitudes, methods, etc.:

He was by temperament an academic, concerned with books and the arts.

10. (initial capital letter) a person who supports or advocates the Platonic school of philosophy.

This is Bjorn Lomborg’s biography from the Copenhagen Consensus website:-

Dr. Bjorn Lomborg is Director of the Copenhagen Consensus Center and Adjunct Professor at University of Western Australia and Visiting Professor at Copenhagen Business School. He researches the smartest ways to help the world, for which he was named one of TIME magazine’s 100 most influential people in the world. His numerous books include The Skeptical Environmentalist, Cool It, How to Spend $75 Billion to Make the World a Better Place and The Nobel Laureates’ Guide to the Smartest Targets for the World 2016-2030.

Lomborg meets both definitions 8 & 9, which seem to be pretty standard. Like with John Cook and William Connolley defining the word sceptic, it would appear that ATTP rejects the authority of those who write the dictionary. Or more accurately does not even to bother to look. Like with rejecting the authority of those who understand economics it suggests ATTP uses the authority of his own dogmatic beliefs as the standard by which to evaluate others.

Kevin Marshall

Freeman Dyson on Climate Models

One of the leading physicists on the planet, Freeman Dyson, has given a video interview to the Vancouver Sun. Whilst the paper emphasizes Dyson’s statements about the impact of more CO2 greening the Earth, there is something more fundamental that can be gleaned.

Referring to a friend who constructed the first climate models, Dyson says at about 10.45

These climate models are excellent tools for understanding climate, but that they are very bad tools for predicting climate. The reason is simple – that they are models which have very few of the factors that may be important, so you can vary one thing at a time ……. to see what happens – particularly carbon dioxide. But there are a whole lot of things that they leave out. ….. The real world is far more complicated than the models.

I believe that Climate Science has lost sight of what this understanding of what their climate models actually are literally attempts to understand the real world, but are not the real world at all. It reminds me of something another physicist spoke about fifty years ago. Richard Feynman, a contemporary that Dyson got to know well in the late 1940s and early 1950s said of theories:-

You cannot prove a vague theory wrong. If the guess that you make is poorly expressed and the method you have for computing the consequences is a little vague then ….. you see that the theory is good as it can’t be proved wrong. If the process of computing the consequences is indefinite, then with a little skill any experimental result can be made to look like an expected consequence.

Complex mathematical models suffer from this vagueness in abundance. When I see supporters of climate arguing the critics of the models are wrong by stating some simple model, and using selective data they are doing what lesser scientists and pseudo-scientists have been doing for decades. How do you confront this problem? Climate is hugely complex, so simple models will always fail on the predictive front. However, unlike Dyson I do not think that all is lost. The climate models have had a very bad track record due to climatologists not being able to relate their models to the real world. There are a number of ways they could do this. A good starting point is to learn from others. Climatologists could draw upon the insights from varied sources. With respect to the complexity of the subject matter, the lack of detailed, accurate data and the problems of prediction, climate science has much in common with economics. There are insights that can be drawn on prediction. One of the first empirical methodologists was the preeminent (or notorious) economist of the late twentieth century – Milton Friedman. Even without his monetarism and free-market economics, he would be known for his 1953 Essay “The Methodology of Positive Economics”. Whilst not agreeing with the entirety of the views expressed (there is no satisfactory methodology of economics) Friedman does lay emphasis on making simple, precise and bold predictions. It is the exact opposite of the Cook et al. survey which claims a 97% consensus on climate, implying that it relates to a massive and strong relationship between greenhouse gases and catastrophic global warming when in fact it relates to circumstantial evidence for a minimal belief in (or assumption of) the most trivial form of human-caused global warming. In relation to climate science, Friedman would say that it does not matter about consistency with the basic physics, nor how elegantly the physics is stated. It could be you believe that the cause of warming comes from the hot air produced by the political classes. What matters that you make bold predictions based on the models that despite being simple and improbable to the non-expert, nevertheless turn out to be true. However, where bold predictions have been made that appear to be improbable (such as worsening hurricanes after Katrina or the effective disappearance of Arctic Sea ice in late 2013) they have turned out to be false.

Climatologists could also draw upon another insight, held by Friedman, but first clearly stated by John Neville Keynes (father of John Maynard Keynes). That is on the need to clearly distinguish between the positive (what is) and the normative (what ought to be). But that distinction was alienate the funders and political hangers-on. It would also mean a clear split of the science and policy.

Hattips to Hilary Ostrov, Bishop Hill, and Watts up with that.


Kevin Marshall

Fundamentals that Climate Science Ignores

Updated 08/09/13 am

Updated 08/09/13 pm – M The Null Hypothesis

Climate Science is a hugely complex subject, dealing with phenomena that are essentially chaotic, with vague patterns. Yet the promotion of that science is banal and superficial. Below are some of the fundamentals that have been addressed in established areas like economics, philosophy and English Common Law, but which the Climate Science community ignores. Most overlap, or are different ways of looking at the same thing.

A Positive and Normative

I do not hold with the logical positivism in vogue in the early parts of the C20th and later underpinning the “positive economics” ideas of Milton Friedman that was popular in the 1950s to 1980s. But it made the useful distinction between positive statements (empirically based statements) and normative statements (what ought to be). The language of climate science is heavily value-laden. There is not attempt to distinguish positive from normative in language, nor highlight that competency in the sphere of positive statements is not necessarily an indication of competency in normative ones.  For instance, when scientists make statements about the moral imperative for policy, they may overemphasize the moral questions raised as they may be too close to the subject. In fact believing that that rising greenhouse gas levels causes a worsening of climate can lead to a bias towards the simplified solution to constrain that growth. It takes understanding of the entirely separate fields of economics and public policy-making to determine whether this is achievable, or the best solution.

B Boundary conditions

There is no clear definition of science in general or the study of climate in particular. The only underlying definitions are tantamount to saying that science is what scientists do, and scientific statements are those made by scientists. Without a clear definition of science, scientists end up making unsupported statements, outside their area of competency. For instance, scientists often make statements about the economic case for policy. With the term “climate change” encompassing both, the general public are misled into believing that “climate scientists” cover both areas.

C Open and closed questions

A closed question can by answered by a single word. The narrowest closed questions are those can be answered “Yes/No” or “True/False”. Open questions need fuller answers. Climate change is not just about closed questions. It is about how much, how likely, when and where. If terms of boundary, there is not a closed question of science versus non-science – with the boundary in actual work being between that published in a peer-reviewed journal and that published outside. That leads onto non-triviality and quality conditions and relevancy

D Trivial v. Non-trivial

The strongest evidence for global warming suggests a trivial issue. In one aspect this is true by definition. The non-trivial part – the potential climate catastrophe that policy seeks to avert – relies upon future projections. This relies on temperature rises many times greater than so far experienced. Projections will always be, weaker that the actual evidence. But there is an empirical aspect as well. If the actual trends are far below those predicted (surface temperature warming trends), or fail to show a switch to a path pointing to catastrophe (acceleration in the rate of sea level rise)

E Quality

There is good quality science and poor quality. Peer review should help, but (as suggested in the Climategate emails) acceptance/rejection can be based on criteria other than science. In most areas of science, and indeed in many professions, efforts have been made to improve the quality of results. One minor step towards improvement of quality is the insistence on publishing the data behind peer-reviewed articles. This has led to the quick exposure of shoddy work like Gergis et al 2012 and LOG12 papers, whereas it took many years of persistence by Steve McIntyre to get the full data on Keith Briffa’s deeply flawed Yamal tree-ring temperature proxy. However, as the forthcoming UNIPCC AR5 report will demonstrate, increasing quality is sacrificed in promoting climate catastrophism.

F False Positives and False Negatives

A particular subset of the quality issue is that of false positives and false negatives. With activists pressuring governments and scientific bodies to agree with the dogma, and promotion of pejorative language (e.g. deniers, fake skeptics), misattribution of significant weather events to climate change is a consequence. Whilst in cancer screening there have been efforts made to reduce the number of false positives and false negatives, in climate science there seems to be every effort to increase the numbers of false positives. (Superstorm Sandy that hit New York state last year, the extreme heat wave in Europe in 2003, the low sea ice point in September 2012).

G Relevancy and significance

Some pieces of information, or scientific papers, are more important than others. The vast majority of papers published are on trivial issues and/or fail to make a lasting impact. In terms of catastrophic global warming, most papers in the field are tangential to the subject. The same is true of items of information, statistics and opinions.

H Necessary and Sufficient

For a climate policy to give net benefits, a number of conditions are necessary, both in the science (greenhouse gas effect, significant warming, adverse consequences) and in policy area (policy with theoretical net benefits > costs of doing nothing, large enough policy area, effective policy management). Sufficient for policy success (net policy benefits > costs of doing nothing) all are to some extent necessary. For policy failure, it is only sufficient for one of the necessary conditions to fail. It does not matter whether this is

–       climate sensitivity being much lower than assumed

–       or adaptation at the non-governmental local level is much more effective than assumed

–       or the net adverse consequences of any given amount of warming are grossly exaggerated

–       or the theoretical economic case for policy is flawed (such as demand for energy is far more inelastic with respect to price over time than assumed, or that renewable energy is not a close substitute to fossil fuel energy)

–       or the actual policy enacted does not encapsulate the economic theory, diluting or nullifying the effectiveness

–       or unilateralist policy where success requires that the vast majority of the biggest economies to participate

–       or the policy on paper is potentially successful, but it is not project managed to drive through the maximum benefits at least cost

I Levels of evidence

In the legal systems, especially in criminal law, it has long been recognized that there are different qualities of evidence. The strongest is DNA, fingerprints, or catching somebody in the act. There is then secondary evidence from witnesses. There is then circumstantial evidence, such as the accused being near to the scene at the time, with no clear reason to be there. The lowest form of evidence, and usually rejected, is hearsay evidence. That is opinions of people with little interest in the case, giving unsupported opinions. The judicial process also views more highly evidence that is corroborated by other pieces of evidence, and evidence that on its own seems quite strong is downgraded or ruled out by contrary evidence, or alternative explanations.

J Values of the Legal Process in Reverse

Climate science, fails to grapple with the grading of evidence, as some its strongest arguments – consensus amongst scientists – is actually hearsay. Improving the quality of evidence would mean critically examining past forecasts in the light of evidence. In the judicial process, creating prejudice in the eyes of the jury against the defendants, or seeking to deny the accused a defence, is forcefully dealt with. Creating prejudice and denying a voice to those who question the climate change dogmas is viewed as part of the cause.

K Underdetermination Thesis

“The underdetermination thesis – the idea that any body of evidence can be explained by any number of mutually incompatible theories”

Quote from Kuhn vs Popper – Steve Fuller 2003

The global warming hypothesis is but one of a number of hypotheses trying to explain why climate changes over time. The problem is not just of a potential number of competing theories. It is that there might be a number of different elements influencing climate, with the various weightings dependent on the method and assumptions in analysis. It is not just trying to determine which one, but which ones and to what extent that they interplay.

L Vulnerability

Every scientific hypothesis is vulnerable to being refuted. Human-caused catastrophic global warming (CAGW) is based on extremely tentative assumptions, and is a forecast of future events. As the warming the past one hundred years is tiny compared that forecast to happen in the future, and that warming is partly obscured by natural variations, then the signal of future catastrophe will be weak. The issue is further clouded by the lack of long periods of data on climate variability before when human emissions became significant. That is data prior to 1945, when the post war economic boom led to a huge increase in human emissions. Assuming the forecasts of CAGW are correct, the hypothesis becomes incredibly vulnerable to rejection.
But if CAGW is false, or massively exaggerated, then the hypothesis is deeply susceptible to confirmation bias by those who only look to find evidence of its truth. The core belief of climate science is that the catastrophist hypothesis is true and the job of the “science” is to reveal this truth. The core mission of many co-believers is to stop any questioning of these core beliefs. The alternative view is that evidence for CAGW has become stronger over the last twenty-five years, making the hypothesis less vulnerable over time. This can be tested by looking at the success of the short-term predictions.

M The Null Hypothesis

Wikipedia’s definition is

In statistical inference of observed data of a scientific experiment, the null hypothesis refers to a general or default position: that there is no relationship between two measured phenomena,…… Rejecting or disproving the null hypothesis – and thus concluding that there are grounds for believing that there is a relationship between two phenomena …………….. – is a central task in the modern practice of science, and gives a precise sense in which a claim is capable of being proven false.

It applies to AGW theory, as the hypotheses are empirical relationships. With highly complex, and essentially chaotic, systems it is only by confronting the data using a battery of statistical tests that you can disprove the null hypothesis. Without the null hypothesis, and without such rigorous testing, all the data and observations will only confirm what you want to believe. Some of the best established empirically-based hypotheses, like “HIV causes AIDS” and “long-term heavy smoking significantly reduces life expectancy” have been confronted with the null hypothesis many times against large, high quality data sets. At extremely high levels of significance, the null hypothesis of no relationship can be rejected.

It could be claimed that the null hypothesis in not applicable to AGW theory as it forecasts something much worse happening than has so far been experienced. However, it is more important because of this. There is no bridge between reality and the theoretical relationships (with assumed magnitudes) in the climate models. The null hypothesis (general or default position) for testing against actual data is not that there is no relationship, but the double-negative of no non-trivial relationship. So the null hypothesis for testing “CO2 causes warming”, is not “CO2 does not affect temperature”, but “CO2 has no non-trivial impact on warming”. The reason is that the claimed requirement for policy is avoidance of a climate catastrophe, with relationships being non-trivial in magnitude.

Lewandowsky et al 2012 from two alternative philosophies of science

The following comment was made on Joanne Nova’s blog, in response to a comment by Jonathan Fordsham that Stephen Lewandowsky did not know what he was getting into by publishing his paper and the subsequent defence of that paper.

Whilst Lewandowsky may not have known what he was getting into, the aim of the paper was to find further reasons to dogmatically dismiss any views that question the established orthodoxy. It is from a view of science that sees conformity and belief in that orthodoxy as the mark of a scientist. From this conformity is the importance of opinion polls and declarations of belief by scientific bodies to this view. Promoting evidence or hypotheses that contradicts orthodoxy risks being branded a heretic or denier.

The alternative, “Popperian” view of science is that progress is often made by over-turning existing hypotheses, or subsuming them within more profound theories. Getting results that contradict hypotheses is a cause for celebration. It then raises a whole series of questions. In this view of science, belief in a specific hypothesis is dangerous. People do not like having their beliefs contradicted, and it would be hugely damaging psychologically to constantly attempt to undermine one’s core beliefs. Belief instead is in finding new understanding of the world by the most rigorous method.

The questionnaire, despite all its biases, clearly showed that the vast majority of respondents, whether skeptic or alarmist rejected cranky conspiracy theories. Lewandowsky’s theory about climate “deniers” having a conspiracist orientation was clearly contradicted by the evidence. A team of people then spent 18 months producing the paper. There is strong circumstantial evidence that the time was spent manipulating the data, choosing the best statistical methods to corroborate their story, and carefully phrasing what they wrote to claim the opposite of what the data revealed.

The “orthodox” view of science was clearly Lewandowsky’s enemy when the evidence contradicted his hypothesis. He could not publish the full results for risk of his status as a scientist and for future funding of his work. The “Popperian” view would have still allowed publication, as it falsifies a hypothesis that Lewandowsky and others believe in.

Kevin Marshall.