IPCC Fraud Solutions

Concern is often expressed about the way the IPCC has been conducted, and I want to suggest a constructive solution. Recently, a climate scientist was critical of freedom of information inquiries reported at ClimateAudit, but made some points that help to illustrate the errors in the current state of thinking. Below is my solution, after extracting quotes from a couple of Michael Tobis’ posts, made in a slightly different context.

Most established climatologists didn’t seek controversy in their career choice. The model of the culture as secretive, manipulative and selfish is not a good explanation of the facts.

Formal processes are intrinsically expensive, and they also reduce the attractiveness of the work, implying greater compensation.

Such a change will in fact attract different people as well as different methods. Something will be lost in the process, and an eye to preserving as much of the collegial culture as possible is also worth considering.

Am I saying, “we are in trouble, send money”? Not really. I don’t think climate science is first order important as of now, as the big picture is pretty clear. It’s those of you who don’t trust us who should be willing to invest in the matter.

I suggest recruiting people from other sciences who don’t have a dog in the hunt. But I’m afraid you’ll get the same answer you always do. The sensitivity to CO2 doubling on a century time scale is about 3 C. Sloppy methods or not we have this thing nailed. Now you can let us keep thinking about our angles and pins, or you can hire somebody to replicate our work.

But if you insist on your sport of sniping at our informality, if you insist that we become more formal, you need to invest a lot of money to train us and/or replace us, because we weren’t trained as MDs or pharmacologists or (a few exceptions like myself notwithstanding) as engineers.

The state of academic science is what it is for a number of reasons. Climatology is unexceptional except in having to deliver some very disconcerting news. You may argue that the nature of the news is such that climatology becomes higher stakes and needs to be reorganized and formalized. I have a great deal of sympathy with that position, and in that regard among others I’m an outlier within the field. Note, though, that such endeavors are expensive and prone to failure.

The ‘opus’ that exists, the response to a need for an organized presentation, is the IPCC WGI reports. For all its flaws, the IPCC consensus process and its reports are an interesting and useful achievement.

The network of trust on which human progress is based is badly frayed these days. I don’t think Climate Audit has made matters any better, but I understand that trust can;t be manufactured on demand. All I can do is state that I have complete confidence in the intellectual competence and moral integrity of those leading figures in the field I have been privileged to work with…

It’s a problem. People are demanding forms of “proof” that aren’t well suited to the problem area. Atmospheres are complicated and interesting beasts; atmosphere-ocean-ice systems (of which we have only one non-simulated instance) the more so. They aren’t unknowable, but predictions about large experiments on a specific system will always be contingent.

Suppose rather than sneering at what is wrong you make some suggestions as to how to set it right, what scale that would require, and who should pay for it.

That said, I believe that the concept of an outside audit is sound and I advocate one for the field of economics, so I can’t consistently argue against one for climatology. I’d be interested in constructive ideas as to how we could improve our credibility if our understanding is sound, or test our understanding if it isn’t.

In my view the UN IPCC report is simply a review of the literature, useful but unsystematic, incomplete and unremarkable apart for the hype surrounding it. Medical science conducts reviews all the time, and they have found that some guiding principles of Evidence Based Practice are essential:

1. The review must be systematic. The type of evidence to be used is explicitly stated by the commissioning agency and the procedures adhered to, with a view to minimizing personal bias.

1. The review must be without conflict of interest. It must be done by people with nothing to gain from the promotion of specific studies.

3. The review must pay particular attention to the relative quality of evidence contributed by each study.

In respect to the third point, a number of different systems have been set up. Adaptation of one of the most well known, from the Centre for Evidence-Based Medicine, Oxford, leads to a hierarchy of evidence something like the following, highest level first:

Level 1. Blind and randomized studies with publicly archived data and code.
Level 2. Comprehensive and independently tested studies with publicly archived data and code.
Level 3. Observational evidence and correlation studies with publicly archived data.
Level 4. Theory, models, and case studies.
Level 5. Expert opinion.

The application of such a system to climate science is not necessarily regulatory, but methodological for evaluating existing evidence in focussed systematic reviews. This would not be expensive, or require an overhaul or massive retraining of climate scientists as Michael Tobis fears. It would provide a positive incentive for studies to be structured in ways that have been proven to yield more reliable results, with less personal bias. It would help to build a climate of trust.

For example, a review commission might stipulate that all evidence is to be level 3 and above, requiring at least publicly archived data. This would eliminate a great deal of studies cited in the IPCC review. It would however provide a strong incentive for archiving data the next time around.

A blind trial of climate models need not be any more expensive than comparison trials as they are currently conducted. As an example, accuracy of a range of niche modeling methods were evaluated in a blind trial reported here.

It would be recognized that the IPCC is just another review, and an unstructured and biased one at that. Its main in-scope goal is to find a human influence on climate, and the range of reasons for climate change are out-of-scope, creating a systematic bias against natural explanations for climate change. This predeliction is clearly stated in its reward of a Nobel Peace Prize for:

“for their efforts to build up and disseminate greater knowledge about man-made climate change, and to lay the foundations for the measures that are needed to counteract such change”

So my solution is not one thats tend to one extreme or the other, from cries of “fraud” to blind acceptance of IPCC as gospel truth. The solution is just to keep it in perspective, and for those who are financially impacted by the implications to conduct their own structured reviews of key components of the case, and let these be a guide to their policy decisions.

Introduction to Carbon Credits

The carbon credit scheme was set up to allow EU countries or companies that fail to meet designated emission reduction targets to avoid paying penalties by purchasing carbon credits. Carbon credits are issued on projects around the world that result in reductions in the emissions of greenhouse gases. They are also a traded by brokers to facilitate exchange. For example the Multi Commodity Exchange of India (MCX) has become first exchange in Asia to trade carbon credits. India has apparently generated some 30 million carbon credits and has roughly another 140 million to push into the world market.

Trading

A ‘trade’ occurs when carbon credits are secured and then surrendered or acquitted through an accredited carbon broker, carbon exchange or carbon registry. For people that want to reduce their carbon footprint, carbon credits can be purchased and (sometimes) exchanged with other environmental organizations. I have noticed a slew of websites appearing on the net that sell carbon credits to people that want to offset the carbon emissions produced as a by-product of the goods and services they consume. But what do you really get for your carbon credits? Origin Energy for $17.50 sells a gift certificate and a promise to offset 1 tonne of carbon in recognized carbon reduction activities such as energy efficiency projects, renewable energy or low-emission generation, carbon sequestration and industrial abatement like fuel substitution.

Credits

Credits can be exchanged between businesses or bought and sold in international markets at the prevailing market price. For example Origin’s Carbon Reduction Scheme can be used to finance carbon reduction schemes between trading partners and around the world. Credits are awarded to countries or groups that have reduced their green house gases below their emission quota. The quality of the credits is based in part on the validation process and sophistication of the fund or development company that acted as the sponsor to the carbon project. Once purchasing an allowance of credits, each unit gives the owner the right to emit one metric tonne of carbon dioxide or other equivalent greenhouse gas.

Price

Prices change and exchange rates fluctuate. Carbon prices are normally quoted in Euros per tonne of carbon dioxide or its equivalent (CO2e). The price range people were getting used to was about Euro 15 or maybe less per tonne of carbon. Unfortunately, there’s a hitch in this scheme that threatens to totally derail it: carbon prices are plummeting due to an excess supply. This time last year credits fell to less than 9 cents. Never mind, the UN will restore confidence in its beleaguered Clean Development Mechanism (CDM) carbon offsetting scheme and drive up the cost of carbon credits, according to a new report released on 24 June 2008.

Science

What happens if the science of the IPCC is flawed, as we often find here on this site? The idea that modern “science” is somehow pure and immune from bias is simply not realistic. There is a tendency to believe what suits one politically regardless of the science and I for one am no different. So bias is unsurprising since the member countries Australia, Canada, China, Russia, and Saudi Arabia, all of which have had a hand in editing the science and the political statement, are whittling away anything contrary. If only the climate science community was as as conscious of human bias as the medical community and adopted the standards of Evidence Based Practice in reviews of the evidence supporting their claims. If the science turns out to be flawed I expect carbon credits will continue to be a commodity, only you can’t eat them like hog’s bellies.

Selling

If you want to make money on carbon credits you need to be a seller. You can become a seller by investing in new low-emission machinery and apply for an allowance. The cost of the seller’s new machinery would be subsidized by the sale of allowances. Another seller might be a company that will offer to offset emissions through a project in the developing world, such as recovering methane from a swine farm to feed a power station that previously would use fossil fuel. Waste disposal units, plantation companies, chemical plants and municipal corporations can sell the carbon credits and make money, even selling them on eBay! Then again, you could become a management consultant and scout for buyers to sell carbon credits to.

Then again, with an alternative energy bubble in play, we could be looking at the start of the next major bull market. Good Luck!

Article with links to more information.

Greenhouse Thermodynamics and GCMs

The recent state of knowledge of global warming report released by the IPCC claims to have direct evidence of the enhanced greenhouse effect (EGE) responsible for global warming. In Chapter 3 Section 3.4 p40 of WG1 they make claims (1) the available data do not indicate a detectable trend in upper-tropospheric relative humidity, and (2) there is now evidence for global increases in upper-tropospheric specific humidity over the past two decades, which is consistent with the observed increases in tropospheric temperatures and the absence of any change in relative humidity.

Water in the upper atmosphere is important as, according to the theory, increases in greenhouse gases set off a positive feedback loop that amplifies the temperature increase, by increasing in water content in the warmer air and decreasing infared radiation is released to space. Notably, all global climate models (GCMs) show warming in the upper troposphere according to the EGE.

Now claims of direct evidence of the mechanism for global warming are particularly important, as they provide proof that increasing temperature is not due to some other mechanism. I have been looking into the veracity of this claim, here and here.

But despite the IPCC claims of no change to the relative humidity, the figure from the NCEP here shows it to be falling strongly, at all levels of the upper atmosphere and particularly in the upper troposphere (UT). A very readable paper by Minschwaner and Dessler (MD07) provides a clue. They show that while increasing temperature slightly increases water vapor and specific humidity (and thus a positive feedback increasing climate sensitivity to CO2 doubling), the amount is much less (-30%) that generally shown by the climate models that assume constant relative humidity. Their modelling shows that the increase in specific humidity is not enough to keep up with the amount needed to keep relative humidity constant for the increasing temperature, and so relative humidity falls. The paper says the models get it right about the positive feedback, but wrong about relative humidity, and so the effect is exaggerated.

While MD07 explains increasing specific humidity and falling relative humidity, and a positive feedback loop if temperature is increasing, does it provide evidence of the EGE as a cause of present day global warming? If temperatures and water vapor in the upper troposphere were actually increasing, while surface temperatures have been increasing, then this would provide the evidence for EGE they seek.

The problem is, temperatures in the upper tropospheres are not rising, as shown at the right hand side of the graph above, from Douglass et al. 2007. Despite claims by the IPCC of evidence of EGE, the only place where temperatures really rising in the upper troposphere is in the climate models themselves! The problem with rising temperatures with elevation, and erroneous constant humidity, is a double deviation from the actual observations!

Usually evidence of something means evidence in the real world, not evidence in a computer model.

Which brings me to another point — is there any evidence of EGE? While they claim small spectral differences demonstrate EGE, there are also other gaping inconsistencies between models, the literature and observations. For a start, the models assume constant relative humidity, MD07 claims this leads to exaggeration of CO2 sensitivity, and in the real world
relative humidity is decreasing. The same goes for UT temperature, and specific humidity. For there to be increased feedback, there has to be increased temperature. Reading the IPCC gives you the sort of uncomfortable feeling like a weather report that says it is sunny when its raining outside.

Two claims made in the IPCC Chapter 3 Section 3.4 p40 of WG1 are obviously false: (1) that the available data do not indicate a detectable trend in upper-tropospheric relative humidity, and (2) there is now evidence for global increases in upper-tropospheric specific humidity over the past two decades, which is consistent with the observed increases in tropospheric temperatures and the absence of any change in relative humidity.

Use of dubious evidence and false claims to support a theory indicates the degree of confirmation bias operating in global warming. Even though the science is contradictory, evidence of an enhanced EBE would be so convenient. It gives credibility to a whole raft of phenomena bundled up as anthropogenic global warming. It has the effect of leading the unwary to think that somehow the science is settled in this area, and there are no other possible explanations for recent warming. It may even lead to convictions! At least then it would go before people who differentiate models and reality.

Greenhouse Thermodynamics of Water Vapor and the IPCC

Following on from the line of investigation started here, I examine the quality of evidence the IPCC presents for global warming due to the enhancement of the greenhouse effect. The summary for policy makers apparently sums up the current state of knowledge, referencing the relevant chapter section (3.4):

The average atmospheric water vapour content has
increased since at least the 1980s over land and ocean
as well as in the upper troposphere. The increase is
broadly consistent with the extra water vapour that
warmer air can hold. {3.4}

Turning to the summary of Chapter 3 of the AR4: Chapter 3 Observations: Surface and Atmospheric Climate Change where the evidence for this claim is presented it is stated:

Similar upward trends in upper-tropospheric specific humidity, which considerably enhance the greenhouse effect, have also been
detected from 1982 to 2004. (Chapter 3 p4)

Turning to section 3.4 there is an extended discussion of the problems
of direct measurements of specific humidity via radiosondes (weather balloons)
and of controversy within the field e.g.

Changes in upper-tropospheric water vapour
in response to a warming climate have been the subject of
significant debate. (Chap 3 Sect 3.4 p39)

However, despite acknowledging a variation in the literature on this issue, and the availability of direct data that does indicate a detectable trend in upper-atmosphere, the conclude:

To summarise, the available data do not indicate a detectable
trend in upper-tropospheric relative humidity. However, there
is now evidence for global increases in upper-tropospheric
specific humidity over the past two decades, which is consistent
with the observed increases in tropospheric temperatures and
the absence of any change in relative humidity. (Chap 3 sect 3.4 p40)

The evidence for this conclusion is from the following line of reasoning:

In the absence of large changes in relative humidity, the
observed warming of the troposphere (see Section 3.4.1) implies
that the specific humidity in the upper troposphere should have
increased. As the upper troposphere moistens, the emission level
for T12 increases due to the increasing opacity of water vapour
along the satellite line of sight. In contrast, the emission level
for the MSU T2 remains constant because it depends primarily
on the concentration of oxygen, which does not vary by any
appreciable amount. Therefore, if the atmosphere moistens,
the brightness temperature difference (T2 − T12) will increase
over time due to the divergence of their emission levels (Soden
et al., 2005). This radiative signature of upper-tropospheric
moistening is evident in the positive trends of T2 − T12 for the
period 1982 to 2004 (Figure 3.21). If the specific humidity in
the upper troposphere had not increased over this period, the
emission level for T12 would have remained unchanged and
T2 − T12 would show little trend over this period (dashed line
in Figure 3.21).

In other words, if we make some obviously false assumptions of no large change in relative humidity (its falling) and increasing temperatures in the upper atmosphere (also falling), then we can conclude that the specific humidity is increasing in the upper troposphere.

As further evidence, direct measurements of specific humidity are falling, here
is the actual specific humidity measured at the upper troposphere of 300hPa, courtesy of Anthony Watts.

Does anyone else find AR4 Section 3.4 breathtaking in its misrepresentation of the evidence? The claim that “the available data do not indicate a detectable trend in upper-tropospheric relative humidity” contradicts direct evidence, and goes on to use false assumptions to make its unqualified claims. It should be noted that Brian Soden (who has published a guest commentary at RealClimate.org), the cited reference for the in the passage above, is a lead author on the chapter.

I will add it to my examples of bias I have found from my examination of evidence related to the AR4 so far.

These include:

  1. Rahmstorf, who claimed climate responding faster than expected on the basis of
    a dubious graph with no statistical test;
  2. Harries who claimed to detect the greenhouse effect from CO2 spectral brightening
    but whose later (unreported) publications were much more equivocal;
  3. Soden, who claims to have detected increase in specific water vapor from
    spectral brightening using blatantly false assumptions.

Even though the AR4 report has been applauded by the major scientific institutions of the world, a cursory review appears to reveal huge biases.
At the very least, the literature deserves to be reviewed in a truly systematic way, focussed on quality of evidence, by an unbiased panel of experts. Such a review would be commissioned with emphasis on meta-questions such as: Is it systematic? What is the system of guidance given to the authors? Is it unbiased?

Greenhouse Thermodynamics and Water Vapor

Anthony Watts has
uncovered some data
from the NOAA website that appears to show water vapor levels have been decreasing for the last sixty years.

Strangely, a number of recent peer-reviewed publications claim that water vapor is increasing:

Water Vapor Feedback is Rapidly Warming Europe

Elevated surface temperatures due to other greenhouse gases have enhanced water evaporation and contributed to a cycle that stimulates further surface temperature increases, according to a report in Geophysical Research Letters. The research could help to answer a long-debated Earth science question about whether the water cycle could strongly enhance greenhouse warming.

The following paper finds a positive trend but contradicts the findings over Europe.

Trends and variability in column-integrated atmospheric water vapor

The main region where positive trends are not very evident is over Europe, in spite of large and positive trends over the North Atlantic since 1988.

The following also finds positive feedback:

Enhanced positive water vapor feedback associated with tropical deep convection : new evidence from Aura MLS

The moistening of the upper troposphere by deep convection leads to an enhanced positive water vapor feedback, about 3 times that implied solely by thermodynamics.

Is water vapor increasing or decreasing? Is feedback positive or negative? The graph below by Ken Gregory shows a clear decreasing trend at all atmospheric levels.

Water vapor levels are another worrisome variation between the ‘consensus’ view as represented by the IPCC reports and real world data.

The decline in water vapor with an increase in greenhouse gases is one clear prediction of Miskolczi’s theory of semi-transparent atmospheres. In contrast, decline in water vapor is not predicted by the theory of infinity thick atmosphere which maintains that temperatures increase for every incremental increase in greenhouse gases, and in fact the ‘consensus’ is that water vapor increases in a positive feedback loop.

Miskolczi states:

Since the world oceans are virtually unlimited sources and sinks of the
atmospheric water vapor (optical depth), the system – depending on the time
constant of the different energy reservoirs – has many ways to restore the
equilibrium situation and maintain the steady state global climate. For
example, in case the increased CO2 is compensated by reduced H2O, then the
general circulation has to re-adjust itself to maintain the meridional energy
flow with less water vapor available. This could increase the global average
rain rate and speed up the global water cycle resulting in a more dynamical
climate, but still the energy balance equations do not allow the average surface
temperature to rise. The general circulation can not change the global radiative
balance although, changes in the meridional heat transfer may result in local or
zonal warming or cooling which again leads to a more dynamical climate.
Note that there are accumulating evidence of long term negative surface
pressure trends all over the southern hemisphere, (Hines et al., 2000), which
may be an indication of decreasing water vapor amount in the atmosphere.

Miskolczi concludes:

On global scale, however, there can not be any direct water vapor feedback mechanism, working against the total energy balance requirement of the
system. Runaway greenhouse theories contradict to the energy balance
equations and therefore, can not work.

One should not be surprised. It has been proven mathematically that “Most Published Research Findings Are False”.

Update: Anthony Watts posts a followup post containing graphs showing rising specific humidity at the surface, and falling humidity at the higher (greenhouse relevant) altitudes. The obvious questions is why do the esteemed climate scientists above create the impression in their publications that increasing water vapor levels are proof of an increasing greenhouse effect? It’s very worrying.

Another Theory of Global Warming

Here I have started to explore a new theory of global warming, not from greenhouse gas buildup in the troposphere, but from changes in stratospheric temperature caused largely by ultra-Plinian (stratosphere reaching) eruptions. A brief article entitled A Stratospheric Compensation Model of Climate Change, is in the May 8 issue of Australian Institute of Geologists Newsletter, pages 12-13.

The main lines of evidence presented for this theory are:

1. A correlation between the inverse of the global mean stratosphere and surface temperatures. This is illustrated in the figure below, showing both the short term cooling of the surface after sudden warming of the stratosphere due to two large eruptions, El Chichón (Mexico 1982) and Mt Pinatubo (Philippines 1991), and an apparent longer term warming with a delay as shown by the smoothed lines.

aig-001.png

Figure: Monthly global surface (HadCRU in gray) and inverted stratosphere (-0.9*TLS in black) temperatures. Smoothed temperatures illustrate the correlation and potential stratospheric cause of recent surface temperature changes.

The warming after these volcanoes is usually attributed to two El Ninos, with no plausible causal mechanism, however I have seen the increased probability of El Ninos after large eruptions occasionally mentioned in the volcanism literature, (see here).

2. Theoretical support for the stratospheric origin of surface temperature changes from Miskolczi’s semi-transparent model of atmosphere. He has an equation, stratospheric compensation, that suggests an inverse delta between the stratosphere and the surface.

The idea is (but I don’t know what Miskolczi thinks about it) that while the temperature of the troposphere is constrained (due to optimization of greenhouse effect), the temperature of the stratosphere and surface can pivot in a see-saw motion while maintaining the same overall energy output of the planet as a whole. This is illustrated in the figure below, and contrasted with the tropospheric theory of warming.

Slide11.png

Figure from Douglass et al. 2007 “A comparison of tropical temperature trends with model predictions” annotated to compare forcing of the GHG theory (red arrow) and stratospheric compensation theory (blue arrows).

3. Other back of envelope calculations to show that the major asymmetries of temperatures, between the Northern and Southern Hemispheres, and the glacial-interglacial periods, are possible without recourse to warming by troposphere greenhouse gases. Here I look at changes in albedo and emissivity that would be needed and if they are possible.

This is an exploratory article, based on some calculations to verify that such a theory is workable. I have since developed a more detailed model that I am presently writing up. It is taking somewhat longer than I had hoped, but in a few weeks I hope to have the basis of a comprehensive volcanic theory of climate change in place. What seemed at first to be an intriguing possibility, is actually looking interesting.

Predictions of the trajectory of temperature in the future from the stratospheric compensation model are:

“Baring major eruptions that produce immediate (~2yr) cooling and longer term warming, surface temperatures will gradually return to pre-CFC 1970 levels (-0.6K) depending on the pace of recovery of the ozone layer.”

Chaitén Eruption June

Heads up for a new volcanism blog by Erik Klemetti with a very succinct description of new developments with the ‘bad boy’ of Chile, Mt Chaitén.

The newest reports out of Chile are indicating that the eruption at Chaiten has reached levels of intensity not seen since the eruption first started over six weeks ago. I have to admit, that isn’t a good sign in terms of keeping the volcanic edifice in one piece. There have been frequent, small (m3) earthquakes along with “rumbling noises,” which might indicates that the domes are collapsing to form pyroclastic flows. Alternately (and need I remind you, very speculatively) it might be the the edifice itself beginning to show the wear of this long eruption and the emptying of the magma chamber.

The most troubling to me is this part of the report: [The military flyover] spotted two new craters. Officials said they saw bursts of gas coming from different areas around the base of the volcano. This suggests that there is enough pressure under the volcano to start opening new vents. Whether or not this leads to the formation of a ring fracture – the series of fractures around edge of a caldera that facilitate collapse – is pure speculation, but at the very least, this is a new stage of activity at Chaiten.

Over at The Blackboard, Lucia finds a huge statistical contribution of volcanic eruptions to climate variation.

How does the 2.1 C/century compare to periods with no volcanic eruptions?

Unfortunately, the historical period of time with no-volcanic eruptions and no-jet-inlet to bucket measurement noise is quite short. However, if I calculate the standard deviation of 8 year trends for the period from roughly the 20s-40s, I get a standard deviation of 0.9 C/century. This is less than 1/2 the value computed by Gavin. But, I’m not at all confident it is correct, as the period is very short.

Interpretation Bias

It is amazing how people’s view of the strength of evidence changes when it confirms their biases. Due to interpretation bias, one should approach bold statements with some skepticism. The social sciences tell us that interpretive bias will be found particularly in those sciences with particular societal interests, or a dominant ideology — such as global warming.

In 2001 a team of UK-based scientists published evidence which they said proved unequivocally that global warming is real.
According to a BBC news article, comparing data obtained from two satellites which orbited the Earth 27 years apart, they claimed to have found significantly less radiation escaping into space than previously.

In the article by Harries et al. in Nature (pdf here) they claimed:

Our results provide direct experimental evidence for a significant increase in the Earth’s greenhouse effect that is consistent with concerns over radiative forcing of climate.

This claim was repeated in 2007 in Chapter 2 of the latest IPCC report, the AR4
Working Group I Report “The Physical Science Basis”.

Harries et al. (2001) analysed spectra of the outgoing
longwave radiation as measured by two satellites in 1970 and
1997 over the tropical Pacific Ocean. The reduced brightness
temperature observed in the spectral regions of many of the
greenhouse gases is experimental evidence for an increase
in the Earth’s greenhouse effect. In particular, the spectral
signatures were large for CO2 and CH4.

Was this evidence conclusive as claimed? At least one researcher thought not. E. Raschke at the GKSS Research Center, University of Hamburg, Germany cited Harries et al. 2001 article and said:

Several greenhouse gases, which are in part or entirely produced by human activities, have accumulated in the atmosphere since approximately the middle of the 19th century. They are assumed to have an additional greenhouse effect causing a further increase of atmospheric temperatures near the ground and a decrease in the layers above approximately 15 km altitude. The currently observed near-surface warming over nearly the entire globe is already considered by a large fraction of our society to be result of this additional greenhouse effect. Complete justification of this assumption is, however, not yet possible, because there are still too many unknowns in our knowledge of participating processes and in our modeling capabilities.

When I searched the 2007 IPCC document for Raschke’s name the result was “No instances found.”. The number of citations for Raschke’s paper is zero, compared with 39 for Harries’ 2001 Nature article. Clearly, skepticism does not pay.

Delving further into the claims of Harries et al. 2001, John Daly posted a balanced review, pointing out an error which he claims incidentally resulted in an erratum being published by Harries. Overall he argues that the effect observed by Harries et al. was very small, that CO2 gives only weak
indications in this study, well within the range of instrument error between two very different instruments separated by technologies 27 years apart, as shown on the figure below.

Even if we accept the claims of statistical significance of the two gases identified as showing the greatest effect, namely methane and the CFCs, methane has stopped increasing and CFC is in decline. Also, ozone decreased during the period, but the absorption line deepened. Something doesn’t make sense here?

I always like to read articles by the same author published both before and after the one in question. Here in the Journal of Climate Harries summarized his previous finding in a somewhat more precise form:

A recent comparison between data taken by two different satellite instruments, the Interferometric Monitor of Greenhouse Gases (IMG) that flew in 1997 and the Infrared Interferometer Spectrometer (IRIS) that flew in 1970, showed evidence of a change in the clear-sky greenhouse radiative forcing due to the increase in greenhouse gas concentrations between those years.

The phrase “evidence of a change in the clear-sky greenhouse radiative forcing” is a much weaker claim than the previous “experimental evidence for a significant increase in the Earth’s greenhouse effect”. After all, they did not perform an experiment in the usually understood sense, nor did they directly measure the Earth’s greenhouse effect, which relates to radiation across the whole infrared spectrum, from the surface to top of atmosphere.

Another paper in 2004 reveals more uncertainties, particularly in the earlier instrumentation:

The results suggest that while the sampling pattern of the IRIS instrument is sufficiently well distributed and dense to generate monthly regional mean brightness temperatures that are within 1.5 K of the true all-sky values, the IMG sampling is too sparse and yields results that differ from the true case by up to 6.0 K. Under cloud-free conditions the agreement with the true field for both instruments improves to within a few tenths of a kelvin. Comparisons with the observed IMG–IRIS difference spectra show that these uncertainties due to sampling presently limit the conclusions that can be drawn about climatically significant feedback processes.

In addition, it seems that in this paper comparing three satellites spectra, an increase in methane was found even between observations when methane was not increasing. They also highlight an inaccuracy in the MODTRAN spectroscopic model. This suggests the only really significant result of Harries et al. 2001 at all, the deepened methane line, could have been an artifact.

Conclusions

I first became interested in this paper from reading the IPCC AR4 report where Harries et al. 2001 is cited as prima facie evidence for greenhouse caused warming. If that were then case, would it not be sensible for another group to have followed up the Harries et al. 2001 study just to verify their claims? I suspect the uncertainty is still underestimated, as the result is achieved by the subtraction of two series of large numbers of variable scaling.

A simple progression through the literature reveals challenges to their claims (Raschke), and dilution the original bold claims. While initial enthusiasm is perhaps understandable, which is why bold claims should be viewed with skepticism, the IPCC report six years later sticks with the original claims, and ignores the subsequent challenges and clarifications. This reveals their bias for their preferred ideology — global warming due to increases in greenhouse gases — and lack of concern with quality of evidence issues. A little background reading reveals that the results of Harries et al. 2001 are an example of weak evidence accompanied by strong interpretive bias.

References

Harries, J.E., H.E. Brindley, P.J. Sagoo, and R.J. Bantges, 2001: Increases in greenhouse forcing inferred from the outgoing longwave radiation spectra of the Earth in 1970 and 1997. Nature, 410, 355–357.

Is the additional greenhouse effect already evident in the current climate?, Journal Fresenius’ Journal of Analytical Chemistry, Volume 371, Number 6 / November, 2001, Pages 791-797

H. E. Brindley and J. E. Harries, Journal of Climate, Article: pp. 3820–3833
Observations of the Infrared Outgoing Spectrum of the Earth from Space: The Effects of Temporal and Spatial Sampling

Bias Examples

Continuing a series on Evidence Based Practise (EBP) below are examples from sea level research of the biases mentioned previously from an interview with Dr. Nils-Axel Mörner. From wikipedia:

Nils-Axel Mörner is the former head of the Paleogeophysics and Geodynamics department at Stockholm University, having retired in 2005. He was president of the INQUA Commission on Neotectonics (1981-1989) and president of the INQUA (International Union for Quaternary Research) Commission on Sea Level Changes and Coastal Evolution (1999-2003).[1] He headed the INTAS (International Association for the promotion of cooperation with scientists from the New Independent States of the former Soviet Union) Project on Geomagnetism and Climate (1997-2003). He is a critic of the IPCC and the notion that the global sea level is rising.

Firstly, he establishes his evidence-based approach to determining sea level rises:

So, we have this 1 mm per year up to 1930, by observation, and we have it by rotation recording. So we go with those two. They go up and down, but there’s no trend in it; it was up until 1930, and then down again. There’s no trend, absolutely no trend.

He then recounts an instance of sample bias or ‘cherry picking':

Another way of looking at what is going on is the tide gauge. Tide gauging is very complicated, because it gives different answers for wherever you are in the world. But we have to rely on geology when we interpret it. So, for example, those people in the IPCC [Intergovernmental Panel on Climate Change], choose Hong Kong, which has six tide gauges, and they choose the record of one, which gives 2.3 mm per year rise of sea level. Every geologist knows that that is a subsiding area. It’s the compaction of sediment; it is the only record which you shouldn’t use. And if that figure is correct, then Holland would not be subsiding, it would be uplifting.

He then relates a violation of the ‘uncertainty principle‘ ensuring no uncertainty about the results of a study:

Then, in 2003, the same data set, which in their [IPCC’s] publications, in their website, was a straight line, suddenly it changed, and showed a very strong line of uplift, 2.3 mm per year, the same as from the tide gauge. And that didn’t look so nice. It looked as though they had recorded something; but they hadn’t recorded anything. It was the original one which they had suddenly twisted up, because they entered a correction factor, which they took from the tide gauge. So it was not a measured thing, but a figure introduced from outside. I accused them of this at the Academy of Sciences in Moscow. I said you have introduced factors from outside; it’s not a measurement. It looks like it is measured from the satellite, but you don’t say what really happened. And they answered, that we had to do it, because otherwise we would not have gotten any trend!

He then invokes funding bias, where financial interests bias the interpretation of trial results.

Then we know that there was a Japanese pineapple industry which subtracted too much fresh water from the inland, and those islands have very little fresh water available from precipitation, rain. So, if you take out too much, you destroy the water magazine, and you bring sea water into the magazine, which is not nice. So they took out too much fresh water and in came salt water. And of course the local people were upset. But then it was much easier to say, “No, no! It’s the global sea level rising! It has nothing to do with our subtraction of fresh water.” So there you have it. This is a local industry which doesn’t pay.

Then we have accusations of fraud, deliberate falsification of evidence:

A famous tree in the Maldives shows no evidence of having been swept away by rising sea levels, as would be predicted by the global warming swindlers. A group of Australian global-warming advocates came along and pulled the tree down, destroy-ing the evidence that their “theory” was false.

Finally we have publication bias, the selective publication of the findings of trials with certain results:

Instead of doing this, they give an endless amount of money to the side which agrees with the IPCC. The European Community, which has gone far in this thing: If you want a grant for a research project in climatology, it is written into the document that there must be a focus on global warming. All the rest of us, we can never get a coin there, because we are not fulfilling the basic obligations. … but it is exceptionally hard to get these papers published also. The publishers compare it to IPCC’s modeling, and say, “Oh, this isn’t the IPCC.” Well, luckily it’s not! But you cannot say that.

This interview has examples of all the forms of research bias mentioned previously. I can’t vouch for the accuracy of these claims as I have not researched them myself. It is presented to show that the concerns with bias in global warming research are almost identical to the issues of concern in the clinical studies medicine. There is a view that these concerns gave rise, after a series of scandals such as the Thalidomide tragedy, to the EBP movement.

From the point of view good scientific practice, and the diminishing evidence of global warming, the IPCC is looking more like a 60’s drug company: an organization with a product to sell, involved in unscrupulous marketing of its product in the absence of evidence of both safety and efficacy.

Bias in Research

Following the line of interest in the previous post on Evidence-based Practise, I came across a review of research into bias in clinical medical research by Lise Lotte Gluud summarizing the findings of methodological studies on the influence of bias in clinical trials. There are many learnings here that could be applied to climate and environmental sciences in general.

It is recognized that uncontrolled observations can provide reliable evidence if the effects are dramatic. However, great care must be exercised when the effects are moderate or small, as such effects as errors, bias, spurious correlations, limit the value of uncontrolled observations. Computer models are essential where direct experiments are impossible. The main problem of experiments with models lies in extrapolation to situations without experimental testing (i.e. predictions), as these may lead to the wrong conclusions.

Thus the main concern of evidence-based practise is detecting and controlling research bias. One definition of bias is the unknown or unacknowledged error created during the design, measurement, sampling, procedure, or choice of problem studied.
Bias is so pervasive because we want to confirm our beliefs, even though science should be organized around proving itself wrong. The key difference between evidence-based and other research is the explicit attempt to eliminate sources of bias.

Selection Bias

Selection bias occurs when confounding factors are unevenly distributed between the experimental group and the control group. Selection bias is often called ‘cherry picking’, where only those data points with favorable outcomes are included in the experimental group. The medical field uses randomization to reduce such bias by creating control groups that are similar with regard to known confounding variables. For example, cores from trees selected for a dendrochronological study could include cores from a random sample of trees and subjected to parallel analysis. Climate analysis from a selected set of climate stations could include analysis of a random sample of stations.

Evaluation of models should be performed blind, where for example, the fit of climate models could be compared without the operators knowing which are the ‘real’ data, or what results were achieved by other models. Certain statistical methods such as logistic regression has been found to increase bias due to misclassification and measurement errors in confounding variables. So care should be taken in selecting methods that minimise inbuilt biases.

Randomization

Medical science has regognized that the large randomized trial is one of our most reliable sources of evidence for assessment of intervention effects. As trials are not possible in the study of large systems such as climate, alternatives for capturing possible bias must be sought.

Adequate randomization requires that the results be uncertain (the ‘uncertainty principle’). If the result of a study is predetermined due to the study design or methodology, then bias compromises the results. Adequate randomization may be achieved by ‘monte carlo’ simulation, by the generation of random sequences and giving the random sequences and equal chance of producing the result.

Funding Bias

The effect of competing interests is debated in medical research. It has been found that industry funding has been associated with higher quality than trials without external funding. On the other hand, financial interests may bias the interpretation of trial results.

The reason for the association between funding and pro-industry conclusions include violation of the uncertainty principle, publication bias, and biased interpretation of trial results. The uncertainty principle means that there is demonstrated uncertainty about the results of the study. Violation of the uncertainty principle may be related to ‘cherry picking’ or flawed methodologies.

In 1997, approximately 16 percent of 1,396 highly ranked scientific journals had policies on conflicts of interest (78). Less than 1 percent of the articles published in these journals contained disclosures of personal financial interests. The importance of disclosure of financial interests is increasingly being recognized, as demonstrated by the following examples of publication bias and neglect of harm.

Publication Bias

Publication bias is the selective publication of the findings of trials with certain results, and may lead to exaggeration of effects. Medical studies have found that studies with statistically significant results were more likely to be published than studies with nonsignificant results, and they had significantly shorter times to publication.

Selective or delayed publication of the findings of studies with unwanted results seems to be a widespread but undocumented problem. For example, “The Scientific Consensus on Climate Change” by Nancy Oreskes found of 913 papers published between 1993 and 2003 with the words “global climate change” in their abstracts that “Not one of the papers refuted the claim that human activities are affecting Earth’s climate”. Although this was widly regarded as evidence of a consensus on global warming, a contribution from selection and publication bias is also highly likely.

Conclusions

In theory, evidence should be believed only if it is produced from well designed studies. Reviews of the medical literature suggest that most studies have variable randomization, small sample sizes and unclear control of bias. As the limitations of studies are frequently not addressed within the study, a systematic review of the evidence is necessary to identify limitations, such as bias or inadequate statistical power. Research on sources of bias is important to empirical fields. All methodological studies could benefit from the influence of better statistical designs.

Global Warming

Global warming is one of the most serious threats facing our global community today. It has been said that global warming may prove to be the first great example in the modern Western world, when science was betrayed by scientists themselves. The makers of the documentary The Great Global Warming Swindle have made many science documentaries before. When they started to make this one, as many others before them have found, the case for man made global warming is weak, and the evidence contradictory.

Warming

The melting of the Arctic ice has inspired both art and science. “Polar Thaw,” is a 30-print exhibit of photographs from locations of Arctic and Antarctic climate warming, available for museums, science centers and funded public venues. The Arctic Climate Impact Assessment (ACIA) report by an international team of 300 researchers for the Arctic Council, predicting the Arctic will lose 50% to 60% of its ice distribution. Polar Bears are the first creature brought under protection for global warming linked habitat loss. But Arctic Ice has recently returned to previous levels, and the Polar Bears were never threatened.

Computer model predictions of strong surface warming in the Arctic have convinced most atmospheric and polar scientists that the main reason for Arctic warming and melting of sea ice is the enhanced greenhouse effect of increased CO2. But their capacity to represent the causes of global warming is limited. Just recently in Nature, a study of the “Vertical structure of recent Arctic warming” demonstrated that much of the present warming appears to be linked to processes other than the modelled processes, such as atmospheric energy transports.

In general global temperatures have risen since the 19th century industrial revolution. According to NOAA, the global warming rate in the last 25 years has risen to +1.3 degrees per Century. But recent satellite measurements show temperature anomolies of -0.18, the same level as 30 years ago when satellite measurements began. This tends to disconfirm the predictions of temperature increases made by international panels of climate scientists (IPCC).

Climate

The phrase ‘climate change’ is growing in preferred use to ‘global warming’ because it helps convey that there are effects of global warming in addition to rising temperatures. There is a tendency in the press to blame all of societies ills, such as African land use problems, on climate change. Although factors other than climate (such as earthquakes, food shortages, deforestation, disease and war) are much more intense and severe of some of the climate events, scientists still predict such problems will increase if emissions of heat-trapping gases are not brought under control, believing very rapid climate change could be disastrous, even for wealthy countries. This view ignores that if climate changes, we could adapt by changing agriculture and other human activities.

Hurricanes

Many have claimed that super powerful hurricanes, fueled by warmer ocean temperatures are the “smoking gun” of global warming. Al Gore claimed global warming is forcing ocean temperatures to rise, which is causing storms, including cyclones and hurricanes, to intensify. However, new research suggests that the number of hurricanes each summer could decrease by about 18 percent. Why were so many so confident that global warming increased the threat from hurricanes? William Gray, meteorology professor emeritus at Colorado State University and renowned hurricane expert, says that the popular notion of global warming is a big scam.

Czech President Vaclav Klaus makes the case that policies being proposed to address global warming are not justified by current science and are, in fact, a dangerous threat to freedom and prosperity around the world. The supposed threat of human civilization against a fragile Earth has become an article of faith, especially in the realm of global warming activism. Today, the global warming debate raging in both the United States and Europe has become extremely contentious, with those would dare to question the quality of the evidence being labeled “deniers”, and “devilish” and compared to human monsters like Josef Fritzl.

The global warming conflict is one of the most serious threats facing our global community today.

Evidence Based Practise

Writing on Prof. Garnauts Heinz Arndt Lecture, Peter Gallagher pens a sensible comment on the lack of attempt to strike a balanced risk assessment. Unlike the 1996 inaugural speech of Adrian Smith as President of the Royal Statistical Society, who held out evidence-based practices as an exemplar for all public policy, Prof Garnaut dismissed the conflicting scientific evidence for global warming.

Evidence-Based Practice uses techniques from science, engineering, and statistics, such as meta-analysis of literature, risk-benefit analysis, and independent tests. EBP aims for clear understand of the relative quality of evidence used in decisions.

Generally, there are three distinct, but interdependent, areas of EBP. The first is the application of the most well-evidenced studies. This requires a basis for judging best research by some objective critieria. Thus second area is the systematic review of literature to evaluate the best studies. Finally, EBP is a “movement” where advocates work to popularize the method and usefulness, both by highlighting instances of good and bad evidence-based practise.

Evidence-based medicine has demoted statements of the “medical expert” to the least valid form of evidence. Thus, statements by the worlds leading organizations would rank poorly as a basis for public policy unless they are based on an evidence-based approach.

Systems to stratify evidence by quality have been developed, such as this one by the U.S. Preventive Services Task Force for ranking evidence about the effectiveness of treatments or screening:

Level I: Evidence obtained from at least one properly designed randomized controlled trial.
Level II-1: Evidence obtained from well-designed controlled trials without randomization.
Level II-2: Evidence obtained from well-designed cohort or case-control analytic studies, preferably from more than one center or research group.
Level II-3: Evidence obtained from multiple time series with or without the intervention. Dramatic results in uncontrolled trials might also be regarded as this type of evidence.
Level III: Opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees.

A more general approach from the Oxford Centre for Evidence-based Medicine might be more adaptable to earth sciences in general:

Level I: Well designed, randomised controlled trial, a decision rule validated in different conditions.
Level II: Well designed, comprehensive and independently tested studies; or extrapolations from level I studies.
Level III: Hypothesis tested theories or models with observations, or extrapolations from level II studies.
Level IV: Computer simulations, observational, based on physical principles, bench research or first principles.
Level V: Expert opinion without explicit, independent critical appraisal.

The difficulty with climate science and economics is the virtual impossibility of level I randomised controlled trials. This serves as a reminder the quality of evidence is generally never above level III. Human ingenuity may develop ways to improve the conduct of natural experiments, and the classification scheme serves to motivate better generation of evidence.

Based on the scheme above, Garnaut’s statement that the recommendations of the IPCC:

“Is not contested by the large majority of specialists, and by the leaders of the relevant learned academies in the countries” (page 6)

would put the evidence on level V, even though individual research examined by the report could occupy higher levels.

Consider other cases of sources of evidence, Global Climate Models (GCMs) and Paleoecological reconstructions.

GCMs would generally sit at level IV, one level higher than expert opinion, and so present low quality evidence. As an illustration that this evidence is indeed low quality, consider the Climate Impact Assessment (ACIA) report by an international team of 300 researchers for the Arctic Council, predicting the Arctic will lose 50% to 60% of its ice distribution. However, Arctic ice extent has since returned to long term averages, justifying its classification as level IV poor evidence of global warming.

Palaeoecology includes reconstructing past climates from tree-rings and other proxies of climate. The origin of the famous hockey stick graph claiming temperatures are the highest experienced in 600 (and then 1000) years, and this could only be attributed to human emission. This view on historic temperatures, particularly in the Medieval Warm Period, has been reversed by a number of more rigorous studies. At best, one could say that some of these studies sit at level III, and some at level IV.

When judged against these standards, one may well ask just where is the reliable evidence of global warming? What can be confidently attributed to human factors, and represents a serious threat? At the very least, the quality sources of evidence and their confidence would be clearly identified in an EBP.

Categories of recommendations

Recommendations for action on global warming, as Prof. Garnaut is doing, should be based on balance of risk versus benefit and the level of evidence on which this information is based. These levels, drawing on the U.S. Preventive Services Task Force are:

Level A: Good scientific evidence suggests that the benefits of the policy substantially outweighs the potential risks. Clinicians should discuss the service with eligible patients.
Level B: At least fair scientific evidence suggests that the benefits of the clinical service outweighs the potential risks. Clinicians should discuss the service with eligible patients.
Level C: At least fair scientific evidence suggests that there are benefits provided by the clinical service, but the balance between benefits and risks are too close for making general recommendations. Clinicians need not offer it unless there are individual considerations.
Level D: At least fair scientific evidence suggests that the risks of the clinical service outweighs potential benefits. Clinicians should not routinely offer the service to asymptomatic patients.
Level E: Scientific evidence is lacking, of poor quality, or conflicting, such that the risk versus benefit balance cannot be assessed. Clinicians should help patients understand the uncertainty surrounding the clinical service.

A large and growing body of scientists would suggest that despite all of the research, global warming is at Level E:

“the scientific evidence is lacking, of poor quality, or conflicting, such that the risk versus benefit balance cannot be assessed.”

The advice to Clinicians in this case is that they

“should help patients understand the uncertainty surrounding the clinical service”.

Ross Garnaut suggests that we should take up Pascal’s Wager out of fear of the possible consequences of global warming. A parallel can be drawn as in environmental science, as in medical science, where the treatment has attendant risks (costs). Garnaut wants us to take a bitter pill, costing at least $45 billion at this time. And while Garnaut acknowledges that

“The scientific assessments are highly uncertain, and their impacts on human activity and welfare even more so.” (page 4)

It does not follow that we are forced to take it:

“We have no alternative to making decisions on complex issues of valuation under great uncertainty.” (page 4)

While it is defensible to argue for taking the pill on the basis that public opinion wants and demands the treatment, evidence-based practise suggests that Garnaut should pay far more attention to understanding the uncertainties surrounding global warming and explaining these uncertainties to the public.

Adapted from wikipedia

Global Warming Statistics: OET (ordinary eyeball test).

The ordinary eyeball test is a reliable and widely used form of data analysis, particularly in climate science. The basic approach is to plot data of a graph, use a highly complex and incompletely documented method to make it almost impossible to replicate, then visually present the desired results with a thick red line.

Experience has shown that the OET produces reliable results in almost every situation. Moreover, these results are very convincing. So convincing was the OET known as the Hockey Stick that it was used in press releases of Third Assessment Report by the United Nations’ Intergovernmental Panel on Climate Change (IPCC) in 2001, featured in the award winning movie “An Inconvenient Truth”, and is still widely used throughout government and science. It has rendered yeoman service in garnering acceptance for the notion that temperatures are the highest they have been for a million years.

Figure: Example of the Ordinary Eyeball Test (OET) from Rahmstorf et al. 2007.

One of the most recent examples of the OET is in the publication by seven IPCC lead authors (the Rahmstorf7) of Rahmstorf et al. 2007 in Science. Here an enhancement of the OET called the ‘slide and eyeball method‘ was used as the main scientific support for the notion of a present ‘runaway warming’ using a classic OET method to demonstrate that “the climate system is responding faster than our current generation of models suggest”. So convincing was this OET that citing this piece of evidence alone, the Australian Garnaut commission determined that “Developments in mainstream scientific opinion … suggest that the world is moving towards high risks of dangerous climate change more rapidly than has generally been understood”. Recent economic modeling shows that implementing a 90 per cent reduction in carbon emissions by 2050 would alone require closing 3 out of 4 coal fired power stations, and building new clean power stations at a cost of $50 billion dollars.

Unfortunately the OET is vulnerable to attacks from the numerate, particularly the claim that uncertainty has not been properly accounted for. Some of the curve has been taken off the Hockey Stick with subsequent studies, but this has not prevented it from remaining in widespread use. The OET is usually acceptable to reviewers in Nature and Science. Some concerns have been raised in a submission to the Garnaut commission pointing out that a more arcane part of the methodology stems from the same person who developed Hockey Stick (Michael Mann) and that it advocates an even more extreme position than the already quite extreme global warming consensus of IPCC. In responding to questions about the uncertainty in the OET of the Rahmstorf7 at RealClimate.org, Rahmstorf seemed confused about the operation of the methodology itself, and suggested concerns be taken to peer review. It never pays to look too closely at an OET.

There are a few of the opinion that even papers that have passed Science and Nature’s peer-review processes, and scientific reports such as the IPCC approved by more than 100 governments, could benefit from review of the methodology by at least one expert statistician. But then the statistical deficiencies would be brought to wide public notice and much of the effectiveness of the OET would be lost.

Thanks to Peter Gallagher for the OET.

Statistics of Global Warming: Sentiment Models

Abstract

These empirical results suggest that overly pessimistic predictions of global warming precede large falls in global temperature. Thus, the level of alarmist sentiment has the potential to be a useful predictor of global temperatures. The rational null expectations hypothesis is tested against the alternative hypothesis that extremes of sentiment signal turning points in global temperature.

Introduction

Sentiment models are based on the idea that extreme sentiment levels signal turning points. These points occur at rare times, when irrational emotional responses lead to temporary extremes that are unsustainable. If you are indeed near the peak of an extreme, it is more likely that levels will fall away, thus contradicting the extremes up to and at the peak. Being aware of sentiment models can help you identify when levels of sentiment are at unrealistic, alarmist extremes.

The figure below shows the correspondence between landmark studies in global warming in the last 10 years and sudden falls in global temperatures. The first and largest fall was after the publication in 1998 by Mann et al. of the (now discredited) Hockey Stick showing temperatures flat for the last 1000 years and suddenly spiking up in the 20th century. The start of the most recent fall in temperature coincides with the 4 May 2007 publication by Rahmstorf et al. (Science Brevia) concluding that “The climate may be responding faster than IPCC models suggest”. The onset of other major falls in the last ten years is marked by other landmark studies in climate alarmism. The publications numbered in the figure are listed below.


Slide1.png

Figure: Dates of publications indicating extremes of global warming sentiment precede sudden falls in global temperature (UAH MSU for lower troposphere).

1. April 1998 Paleoclimatology

Global-scale temperature patterns and climate forcing over the past six centuries“, by Michael E. Mann, Raymond S. Bradley & Malcolm K. Hughes. The origin of the famous hockey stick graph claiming temperatures are the highest experienced in 600 (and then 1000) years. The view has been reversed by a number of more rigorous studies.

2. January 2004 Biodiversity

Extinction Risk from Climate Change,” by Chris D. Thomas, Alison Cameron, Rhys E. Green, Michel Bakkenes, Linda J. Beaumont, Yvonne C. Collingham, Barend F. N. Erasmus, Marinez Ferreira de Siqueira, Alan Grainger, Lee Hannah, Lesley Hughes, Brian Huntley, Albert S. van Jaarsveld, Guy F. Midgley, Lera Miles, Miguel A. Ortega-Huerta, A. Townsend Peterson, Oliver L. Phillips8 & Stephen E. Williams, Nature, stating “we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15–37% of species in our sample of regions and taxa will be ‘committed to extinction’.”

2004 has been described as the year global warming got respect. A number of significant reports of alarmist sentiment appeared throughout the year (as temperatures plummeted) including the Climate Impact Assessment (ACIA) report by an international team of 300 researchers for the Arctic Council, predicting the Arctic will lose 50% to 60% of its ice distribution (ice extent has since returned to long term averages). In December “The Scientific Consensus on Climate Change” by Nancy Oreskes found of papers published between 1993 and 2003 with the words “global climate change” in their abstracts that “Not one of the papers refuted the claim that human activities are affecting Earth’s climate”.

3. May 2006 Hollywood

The movie An Inconvenient Truth by Al Gore released
(soon as an opera).

4. May 2007 Global Climate Models

“Recent Climate Observations Compared to Projections” by Stefan Rahmstorf, Anny Cazenave, John A. Church, James E. Hansen, Ralph F. Keeling, David E. Parker, and Richard C. J. Somerville expressed the view that the IPCC (the consensus view on climate change) was too conservative and that “The climate may be responding faster than our current generation of models suggest” (temperatures have plummeted once again).

Results

With a rational expectation of no bias, publications marking extremes of sentiment would be correct half of the time. The probability of the four publications would precede large falls in temperatures is 0.5×0.5×0.5×0.5=0.0625 or 6.25%. The null hypothesis is thus rejected at the 90% level but not at the 95% level. It is thus ‘very likely’ (according to IPCC terminology) that extremes of global warming sentiment mark turning points in global temperatures. Further work on development of an index of extreme global warming sentiment is in progress, and would be an important contribution to the emerging science of global warming error theory.