Theories for the pause include that deep oceans have taken up more heat with the result that the surface is cooler than expected, that industrial pollution in Asia or clouds are blocking the sun, or that greenhouse gases trap less heat than previously believed.
The change may be a result of an observed decline in heat-trapping water vapor in the high atmosphere, for unknown reasons. It could be a combination of factors or some as yet unknown natural variations, scientists say.
…
“The climate system is not quite so simple as people thought,” said Bjorn Lomborg, a Danish statistician and author of “The Skeptical Environmentalist” who estimates that moderate warming will be beneficial for crop growth and human health.
…
“My own confidence in the data has gone down in the past five years,” said Richard Tol, an expert in climate change and professor of economics at the University of Sussex in England.
Full article here: http://www.reuters.com/article/2013/04/16/us-climate-slowdown-idUSBRE93F0AJ20130416
See also: Fireworks in the EU Parliament over “the pause” in global warming
==========================================================
This article is a bit of a turnabout for Alister Doyle, who has run a series of mostly unquestioning articles promoting AGW in the past. Now if only Seth Borenstein at AP can begin to start questioning, we could see real journalism on display.
h/t to Joe D’Aleo
Related articles
- Is the media waking up on global warming? ‘Tic, tic, tic. The sleeping MSM is stirring. Headlines no one could imagine seeing a few years ago are popping up on a regular basis. The backdown is beginning’ (climatedepot.com)
- Nature mag forced to admit warming has stopped: New Climate Deniers say ‘the ocean ate my global warming’ (junkscience.com)
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From Columbia University. It would seem obvious that heat rises and that the Sun heats the ocean, not the air.
Conduction: When air is contact with the ocean is at a different temperature than that the sea surface; heat transfer by conduction takes place. On average the ocean is about 1 or 2 degrees warmer than the atmosphere so on average ocean heat is transferred from ocean to atmosphere by conduction. The heated air is more buoyant than the air above it, so it convects the ocean heat upward into the atmosphere. If the ocean were colder than the atmosphere (which of course happens) the air in contact with the ocean cools, becoming denser and hence more stable, more stratified. As such the conduction process does a poor job of carrying the atmosphere heat into the cool ocean. This occurs over the subtropical upwelling regions of the ocean. The transfer of heat between ocean and atmosphere by conduction is more efficient when the ocean is warmer than the air it is in contact with. On global average the oceanic heat loss by conduction is only 24 watts per square meter.
Terry Oldberg:
I said to you
Your reply is at at April 17, 2013 at 12:12 pm but you seem to have overlooked my request.
Please provide me with a clear, simple and succinct statement of your “equivocation fallacy”.
Indeed, your reply to me causes me to make an additional request.
It begins saying.
richardscourtney:
In response to your latest message to me, I offer the following reply. My reply is a lightly edited version of comments I submitted earlier to an advisory committee to the government of the United States. My comments are on a draft of the Federal Advisory Committee Climate Assessment Report (FACCAR) that has been offered up by this committee for public comment. My comments on this documsnt start immediately below.
Summary and Introduction
No statistical population underlies the models by which climatologists project the amount, if any, of global warming from greenhouse gas emissions that the people of the United States will have to endure in the future. For the people of the United States, the absence of a statistical population has dire consequences. They include:
• The inability of the models to provide policy makers with information about the
outcomes from their policy decisions,
• The insusceptibility of the models to being statistically validated and,
• The inability of the government to control the climate through regulation of
greenhouse gas emissions.
Notwithstanding its inability to control the climate, our government continues to enact legislation and spend money in attempts at controlling the climate. Evidently the government continues to labor under one or more misapprehensions. To relieve the government of these misapprehensions is a task that the authors of the FACCAR should do.
Currently, the FACCAR reveals neither the absence of a statistical population nor the consequences from this absence. Rather than describe global warming climatology warts and all, the FACCAR obscures its unsavory features through repeated applications of a deceptive argument. Philosophers call this argument the equivocation fallacy ( Wikipedia: “Equivocation.” ) .
In the course of the following remarks, I show how the Advisory Committee can, if it wishes, expose and eliminate instances of this fallacy in the version of the FACCAR that eventually is published. Elimination of all instances of the fallacy would reveal to public view that the publicly supported investigation of the global warming phenomenon has failed. Retention of the fallacy would conceal this failure from public view.
The Equivocation Fallacy
Currently the failure of global warming research is concealed by multiple instances of the equivocation fallacy (EF). An example of an EF follows (Jumonville, 2003 ):
Major premise: A plane is a carpenter’s tool.
Minor premise: A Boeing 737 is a plane.
Conclusion: A Boeing 737 is a carpenter’s tool.
Like the argument which is called a “syllogism,” (Wikipedia: “Syllogism.” ) the example has a major premise, a minor premise and a conclusion. Like a syllogism, the example has three terms; they are “plane,” “carpenter’s tool” and “Boeing 737.” Thus, it would be easy for one to mistake the example of an EF for a syllogism. However, there is a significant difference between the example and a syllogism: the conclusion of a syllogism is true but the conclusion of the example, that “a Boeing 737 is a carpenter’s tool,” is false. What is it about the example that makes its conclusion false when the conclusion of a syllogism is true?
A pathological feature of the example can be exposed by replacement of the first instance of “plane” by “carpenter’s plane” and by replacement of the second instance of “plane” by “airplane.” The example then reads:
Major premise: A carpenter’s plane is a carpenter’s tool.
Minor premise: A Boeing 737 is an airplane.
Conclusion: A Boeing 737 is a carpenter’s tool.
While being like a syllogism in certain respects, the reworded example has four terms while a syllogism has three of them; the four terms are “carpenter’s plane,” “carpenter’s tool,” “airplane” and “Boeing 737.” Rather than being an example of a syllogism, the reworded example is a four term fallacy ( Wikipedia, “Fallacy of Four Terms” ) . That there are four terms has the consequence that the reworded example does not have the three terms that are a property of a syllogism. It is no surprise, then, that the conclusion of the example is false.
The technique that I used in exposing the fallaciousness of the example is suitable for general use. The technique is to disambiguate all of the terms in the language in which an argument is made. Prior to my rewording of the example, the term “plane” had two meanings; one was “carpenter’s plane”; the other was “airplane.” A term that has several meanings is said to be “polysemic.” Disambiguation of the language in which an argument is made eliminates the polysemic terms from this argument. It is the presence of polysemic terms that can lead a person to mistake an EF for a syllogism.
The source of the term “equivocation fallacy” is as follows. An “equivocation” is an argument in which a term changes meanings in the middle of this argument. By logical rule, a proper conclusion cannot be drawn from an equivocation ( Hall, “Proper inferences avoid equivocation.” ). To draw a conclusion from an equivocation is the “equivocation fallacy.”
Polysemic terms in climatology
In making arguments regarding the methodologies of their studies, global warming climatologists use polysemic terms. Some of these terms are words. Others are word pairs. The two words of a word pair sound alike and while they have different meanings climatologists treat the two words as though they were synonyms in making arguments.
The following terms are polysemic and are used by climatologists in making methodological arguments (Oldberg, 2011):
model
scientific
project-predict
projection-prediction
validate-evaluate
validation-evaluation
An example
A post to the blog Real Climate offers an example of an EF in the methodological argument of a global warming climatologist. Under the heading “Is Climate Modeling Science?,” the global warming climatologist Gavin Schmidt attacks an opponent’s claim that climate models are not scientific. His argument, though, draws an improper conclusion from an equivocation thus being an example of an EF.
Were climate models of the past built under the scientific method of inquiry? Schmidt argues that:
At first glance this seems like a strange question. Isn’t science precisely the quantification of
observations into a theory or model and then using that to make predictions? Yes. And are
those predictions in different cases then tested against observations again and again to
either validate those models or generate ideas for potential improvements? Yes, again. So
the fact that climate modeling was recently singled out as being somehow non-scientific
seems absurd (Schmidt, 2005).
Reduced to the form of major premise, minor premise and conclusion, Dr. Schmidt’s argument seems to be:
Major premise: All scientific models are built by a process in which the predictions of these models are validated.
Minor premise: All climate models are built by a process in which the predictions of these models are validated.
Conclusio: All climate models are scientific models.
Upon superficial examination, this argument seems to be an example of a syllogism. As the conclusion of a syllogism is true, the conclusion of Dr. Schmidt’s argument also seems to be true. However, with the help of the list of polysemic terms provided earlier, it can be seen that this argument contains the polysemic terms “model,” “scientific,” “prediction” and “validate.” Dr. Schmidt’s argument, then, draws its conclusion from an equivocation. By logical rule, this conclusion is improper.
Need for disambiguation
One can avoid reaching improper conclusions about the methodologies of climatological studies by disambiguating terms in the language of the associated arguments. In the course of the following remarks, I disambiguate these terms.
Disambiguating “model”
In the language in which global warming climatologists make methodological arguments, the word “model” is polysemic. The word means: a) a kind of algorithm that makes a predictive inference and b) a kind of algorithm that makes no predictive inference. That a “model” makes and does not make a predictive inference is of logical significance, for logic contains rules that discriminate correct from incorrect predictive inferences. Without a predictive inference, these rules are inoperative.
Thus, going forward I’ll disambiguate the language of the methodological arguments of global warming climatology through elimination of the polysemic term “model.” I’ll accomplish this task by reserving the word “model” for reference to the kind of algorithm that makes a predictive inference. For reference to the kind of algorithm that makes no predictive inference, I’ll reserve the French word modèle. As I’ll soon show, models and modèles have remarkably different characteristics. To fail to distinguish between a model and a modèle is to obscure these differences.
Disambiguating predict-project and prediction-projection
To “predict” is to do something different than to “project” yet most global warming climatologists use the two terms synonymously (Green and Armstrong, 2007). In doing so, they create the polysemic term predict-project and the polysemic term prediction-projection. I shall disambiguate the two polysemic terms by drawing a distinction between: a) predict and project and b) prediction and projection.
The idea of a “prediction” is closely related to the idea of a “predictive inference.” This relationship follows from the fact that a predictive inference is a conditional prediction. An example of one is provided by the following two statements:
Given that it is cloudy:
the probability of rain in the next 24 hours is thirty percent.
Given that it is not cloudy:
the probability of rain in the next 24 hours is ten percent.
A “prediction” is an unconditional predictive inference. It is like a predictive inference but with the exception that one of the conditions has a probability of 1 because this condition has been observed. Suppose cloudy has a probability of 1 because it has been observed. Then the prediction that is a product of the predictive inference referenced immediately above is
The probability of rain in the next 24 hours is thirty percent.
Thirty percent is the probability of rain, given that it is cloudy in the associated predictive inference.
To make a prediction, one needs a predictive inference. A predictive inference is made by a model. A predictive inference is not made by a modèle. Thus, while predictions are made by a model, a modèle is incapable of making predictions.
On the other hand, a modèle is capable of making projections while a model is incapable of making them. The “projection” of global warming climatology is a mathematical function that maps the time to the projected global average surface air temperature.
Related to the idea of a “predictive inference” is the idea of the independent events in a statistical population. Each such event is associated with a state of nature that is called a “condition” and a state of nature that is called an “outcome.” In the above example, an event has one of two possible conditions; they are “cloudy” and “not-cloudy.” Also, an event has one of two possible outcomes; they are “rain in the next 24 hours” and “no rain in the next 24 hours.” The statistical population of a model is said to “underlie” this model. A modèle has no underlying statistical population.
The statistical population of a model has properties called “relative frequencies.” The non-existent statistical population of a modèle has no such properties. A consequence is for probability theory to be inapplicable to a modèle. A further consequence is for it to be impossible for the builder of a modèle to express incomplete information.
Disambiguating validate-evaluate and validation-evaluation
Validate-evaluate and validation-evaluation are polysemic terms that were created by the IPCC. As the long time IPCC expert reviewer Vincent Gray tells the story ( Gray, 2008, pp 8-9 ), many years ago he complained to IPCC management that the IPCC assessment reports of the day were claiming the IPCC modèles to have been validated when these modèles were insusceptible to being validated. After tacitly admitting to Dr. Gray’s charge, the IPCC established a policy of changing the term “validate” to the similar sounding term “evaluate” and the term “validation” to the similar sounding term “evaluation.” Thereafter, many climatologists fell into the habit of treating the words in each word-pair as if they were synonyms. A consequence was for the two polysemic terms validate-evaluate and validation-evaluation to be created. These terms may be disambiguated through recognition of the fact that the meanings of the words in each word-pair differ.
A model is said to be “validated” when the predicted relative frequencies of the outcomes of events are compared to the observed relative frequencies in a sample that is randomly drawn from the underlying statistical population, without a significant difference being found between them. As it has no underlying statistical population, a modèle is insusceptible to being validated. However, it is susceptible to being “evaluated.” In an evaluation, projected global average surface air temperatures are compared to observed global average surface air temperatures in a selected time series.
Disambiguating “scientific”
According to Wikipedia ( Wikipedia, “Scientific theory”), “A scientific theory is a well-substantiated explanation of some aspect of the natural world, based on a body of knowledge that has been repeatedly confirmed through observation and experiment.” For a model, validation serves the purpose of confirming through observation and experiment. Does evaluation serve the same purpose for a modèle?
No it does not. In an evaluation, projected temperatures are compared to observed temperatures but a judgment is not made in which claims made by a modèle are confirmed or denied. Thus, “scientific” cannot legitimately be used as a modifier of “modèle.” On the other hand, under Wikipedia’s definition of “scientific theory,” “scientific” can legitimately be used as a modifier of “model.”
Translating Gavin Schmidt’s argument
With the help of the disambiguated terminology developed immediately above, Dr.Schmidt’s argument can be translated into a form in which it is free from the potential for drawing a conclusion from an equivocation. With its polysemic terms removed and conclusion rewritten for consistency with its premises, this argument reads:
Major premise: All scientific models are built by a process in which the predictions of these models are validated.
Minor premise: All climate modèles are built by a process in which the projections of these modèles are evaluated.
Conclusion: (none logically possible)
No conclusion is logically possible from it because the Dr. Schmidt’s argument is not of the form of a syllogism. On the other hand, it appears to be of this form prior to disambiguation of polysemic terms in the language in which it is expressed.
The conclusion that “All climate models are scientific models” is a consequence from drawing an improper conclusion from an equivocation. To draw such a conclusion is an example of an EF. Dr. Schmidt’s conclusion results from an EF.
Contrasting a model and a modèle
Disambiguation of terms in the language in which climatologists make methodological arguments reveals that there is a contrast between a model and a modèle. This contrast is illustrated in the table positioned immediately below
model modèle
makes predictive inference makes no predictive inference
makes predictions makes no predictions
underlying statistical population no underlying statistical population
makes no projections makes projections
susceptible to validation insusceptible to validation
insusceptible to evaluation susceptible to evaluation
product of scientific method not product of scientific method
conveys information to user conveys no information to user
makes climate controllable does not make climate controllable
The last two lines of the above table deserve amplification. If there were any, predictions from a climate model would convey information to a policy maker about the outcomes from his or her policy decisions prior to these outcomes happening; the availability of this information might make the climate controllable. Currently, however, we have no climate models. We do have climate modèles but they make no predictions hence conveying no information to a policy maker. Thus, after decades of effort and the expenditure of several hundred billion U.S. dollars on global warming research, the climate remains uncontrollable. Nonetheless governments, including our federal government, persist in trying to control the climate.
It is conceivable that climate models can be built. To try to build them offers the only hope for one day being able to control the climate.
The “models” of AR4
Every entity which, in IPCC Assessment Report 4 (AR4), is referenced by the polysemic term “model” is an example of a modèle. Each modèle has traits lying on the right hand side of the contrast presented immediately above. These traits are:
makes no predictive inference
makes no predictions
no underlying statistical population
makes projections
insusceptible to validation
susceptible to evaluation
not product of scientific method
conveys no information to user
does not make climate controllable
If the language of the methodological arguments that are made in the FACCAR were to be disambiguated, the authors of the FACCAR would be compelled to admit that the items in the above list are descriptive of the climate modèles that are currently being used in making policy on emissions of greenhouse gases by the federal government. If these admissions are not made, there will be continuing catastrophic waste of the capital of the people of the U.S. on: a) attempts at controlling the uncontrollable and b) foolishly framed, deceptively described global warming research. To make these admissions would require courage and integrity on the part of the Advisory Committee.
Works cited
Wikipedia: “Equivocation.” URL = http://en.wikipedia.org/wiki/Equivocation .
Wikipedia: “Syllogism.” URL = http://en.wikipedia.org/wiki/Syllogism .
Jumonville, D., 2003: “Fallacies in Argument.” URL = http://lionsden.tec.selu.edu/~djumonville/etec641/WebQuest/fallacy.htm .
Wikipedia: “ “Fallacy of Four Terms:” URL = http://en.wikipedia.org/wiki/Fallacy_of_four_terms .
Hall, James: “Proper inferences avoid equivocation ”: Lecture 13 in the series of lectures entitled “Tools of Thinking: Understanding the World Through Experience and Reason.” This series is published on DVDs by The Teaching Company.
Oldberg, T. 2011: “The Principles of Reasoning. Part III: Logic and Climatology.” URL = http://judithcurry.com/2011/02/15/the-principles-of-reasoning-part-iii-logic-and-climatology/ .
Schmidt, Gavin 2005: “Is Climate Modelling Science?” URL = http://www.realclimate.org/index.php/archives/2005/01/is-climate-modelling-science/ .
Gray, Vincent 2008: “The Intergovernmental Panel on Climate Change: Spinning the Climate.” URL = http://icecap.us/images/uploads/SPINNING_THE_CLIMATE08.pdf .
Green, Kestin and J. Scott Armstrong: “Global Warming: Forecasts by Scientists vs. Scientific Forecasts,” Energy and Environment, Vol 18, No. 7+8, 2007. URL = http://www.forecastingprinciples.com/files/WarmAudit31.pdf .
Wikipedia, “Scientific theory, URL = http://en.wikipedia.org/wiki/Scientific_theory .
I apologise to all that I failed to close quotation after “…argument was sound.” in my post at April 17, 2013 at 1:03 pm.
Richard
When private industry lobbies the government to do something, and it turns out private industry was totally wrong, it is somehow always the government’s (politicians’) fault and the government (politicians) who gets the blame. Apparently what works for private industry also works for scientists. Why would anyone ever want to be in government?
Please correct me if I’m wrong but I think what Terry Oldberg is saying is that the computer models the climatologists use to make their “projections” of the future climate, or “modeles” as he called them, are not to be confused with “models” that represent a theoretical understanding of a subject and can be used to make actual predictions.
As such Terry is saying that the modeles can’t be “falsified” because they were never making predictions in the first place (merely projections) and so there is nothing to falsify. Basically all are in agreement that the modeles are rubbish, just that Terry is saying they cannot be “falsified” using statistical analysis of actual trends since the modeles aren’t using valid statistical techniques in the first place (he says they are absent a statistical population).
So basically there is general agreement but argument over semantics, arising from using the term “falsifying”.
Graham W:
Thankyou for your attempt to help in your post at April 17, 2013 at 2:44 pm.
I am truly grateful because I suspect you may be right. However, with no disrespect to you, I want Terry to make a simple statement of what he means. Like you, I could say what I think he means, and so could anyone else. But there is only one true meaning of Terry’s words and it is his responsibility to provide it.
Please note that this is NOT an esoteric matter because it has potential for serious practical effects.
This thread is about media understanding of AGW. The climate models are the source of the predictions and projections of future climate. The models have made a wrong prediction (n.b. prediction and not projection). The media can understand that information and the implications of it.
But that information is obscured by proclamations that the models don’t make predictions and projections because of some “equivocation fallacy” which nobody – not even its inventor – can explicitly state.
Richard
richardscourtney:
You seem to believe I invented the equivocation fallacy thus being compelled by the requirement for clarity of expression to describe it. If so, your belief is false.
richardscourtney: No problem, I take your point. Good to see you posting here again, by the way!
Lawsuits brought by fossil fuel producers against climatologists and their employers will have little positive effect in the absence of a widespread public debate over AGW policy issues, a debate which challenges the validity of AGW science and theory.
We will not see that kind of useful debate emerge unless and until the voting public is asked to make significant near-term economic and lifestyle sacrifices in order to reduce their carbon footprints, both individually and collectively.
Only when the voting public is asked by America’s most influential political leaders to make significant personal and collective sacrifices in the name of carbon emission reductions will AGW alarmists be compelled to publicly defend their theories, in direct response to informed criticism.
So …. Why hasn’t America’s senior political leadership declared a War on Carbonism, and why haven’t they asked the American public to make significant near-term economic and lifestyle sacrifices in order to reduce their carbon footprints?
We kind of know the answer to that question, don’t we?
If America’s politicians asked us to make the sacrifices necessary to reduce our carbon footprints, climate change would suddenly become a contentious public issue, one which was highly visible on everyone’s day-to-day radar, and therefore an issue worthy of extended public debate.
For those who promote AGW theories as their profession, the outcome of a widespread public debate concerning the validity of those AGW theories might be either a blessing or a curse, depending on which way it went.
Would both AGW alarmists and AGW skeptics alike be willing to gamble that an extended public debate over the validity of AGW science might be either a blessing or a curse for their respective agendas, once the dust finally settled?
Beta Blocker:
It seems to me that multi-billion dollar judgements for fraud against prominent research universities would have a salutary effect on the quality of the research that is conducted by these universities.
Terry Oldberg:
I have noted your post at April 17, 2013 at 4:30 pm.
I ask you to please reply to my post at April 17, 2013 at 1:03 pm
Richard
richardscourtney:
Regarding your request of April 17, 2013 at 1:03 pm, you’ve got my response.
Terry Oldberg:
re your answer to me at April 17, 2013 at 4:43 pm .
Thankyou, that is very clear.
Either you don’t know what you are talking about or you are incapable of saying it other than in gobbledeygook. So, please stop wasting space on numerous WUWT threads and elsewhere with the meaningless gobbledegook.
And, importantly, DO NOT claim I made a false argument (as you did e.g. at April 17, 2013 at 12:12 pm) when you are incapable of stating or are unwilling to state any error in what I said except in meaningless gobbledeygook which has no meaning except to you.
Richard
richardscourtney:
Being unwilling to join you in fallacious argumentation and unable to engage you in logical argumentation, I wish you a good day.
The lack of warming for 16 years is only one of a long list of fundamental issues with the extreme AGW hypothesis.
If an idea, a theory is repeated enough, it is natural to assume there is some truth to the hypothesis. What has been ignored is there are multiple periods when planetary temperature does not correlate with atmospheric CO2.
For example, the following is Greenland Ice Sheet temperature Vs atmospheric CO2 for the last 11,000 years. The Greenland Ice sheet gradually becomes colder and experiences the Dansgaard-Oeschger warming and cooling cycles (1450 year cycle plus or minus 500 years) and atmospheric CO2 gradually increases. The Greenland Ice Sheet temperature is not disconnected from planetary temperature. There are periods in the geological record where there are ice epochs of millions of years when atmospheric CO2 was high and periods of millions of years when atmospheric CO2 has low and the planet was warm.
The observational data and basic analysis indicates that there is something fundamental that has been missed.
Greenland ice temperature, last 11,000 years determined from ice core analysis, Richard Alley’s paper.
http://www.climate4you.com/images/GISP2%20TemperatureSince10700%20BP%20with%20CO2%20from%20EPICA%20DomeC.gif
http://www.climate4you.com/
Scientists as opposed to agenda pushers, try to solve physical problems.
The AGW theory predicted – this is fundamental logical pillar of the theory, if the ‘prediction’ does not occur the theory is invalid – that the AGW warming should be the greatest in the tropics as this is the region where there is the largest amount of long wave radiation reflected off in to space. As the lower atmosphere is saturated due to the overlap of water vapour and CO2, the ‘theory’ predicted that the tropical tropospheric warming at roughly 10 km above the surface of the planet. The tropospheric warming at roughly 10 km in turn would warm the tropics by long wave radiation.
There has been no tropical warming in the 20th century and there has been no tropical tropospheric warming at roughly 10 km. The warming that has occurred in the 20th is in high latitude regions.
Interesting that that there are cycles of past warming (1450 years plus or minus 500 years) followed by cooling in high latitude regions in the paleorecord.
It is difficult to understand how group think and peer pressure can inhibit the solution of what caused the past warming and cooling cycles.
[34] Recently, it has been claimed that model‐based estimates of global‐scale TLT changes are a factor of three larger than the observed ‘residual’ TLT trend (J. R. Christy, Testimony in Hearing before the Subcommittee on Energy and Power, Committee on Energy and Commerce, House of Representatives, March 8, 2011, http://republicans.energycommerce. house.gov/Media/file/Hearings/Energy/030811/ Christy.pdf) (hereinafter Christy, online document, 2011). This residual trend was estimated after statistical removal of ENSO and volcanic signals from UAH TLT data, but not from model data. The net effect of removing ENSO and volcanic signals was to reduce the UAH TLT trend over 1979 to 2010 from 0.14 to 0.09°C/decade (Christy, online document, 2011).
http://icecap.us/images/uploads/DOUGLASPAPER.pdf
A comparison of tropical temperature trends with model predictions
We examine tropospheric temperature trends of 67 runs from 22 ‘Climate of the 20th Century’ model simulations and try to reconcile them with the best available updated observations (in the tropics during the satellite era). Model results and observed temperature trends are in disagreement in most of the tropical troposphere, being separated by more than twice the uncertainty of the model mean. In layers near 5 km, the modelled trend is 100 to 300% higher than observed, and, above 8 km, modelled and observed trends have opposite signs. These conclusions contrast strongly with those of recent publications based on essentially the same data.
http://www.johnstonanalytics.com/yahoo_site_admin/assets/docs/LindzenChoi2011.235213033.pdf
On the Observational Determination of Climate Sensitivity and Its Implications
Richard S. Lindzen1 and Yong-Sang Choi2
We estimate climate sensitivity from observations, using the deseasonalized fluctuations in sea surface temperatures (SSTs) and the concurrent fluctuations in the top-of-atmosphere (TOA) outgoing radiation from the ERBE (1985-1999) and CERES (2000- 2008) satellite instruments. Distinct periods of warming and cooling in the SSTs were used to evaluate feedbacks. An earlier study (Lindzen and Choi, 2009) was subject to significant criticisms. The present paper is an expansion of the earlier paper where the various criticisms are taken into account. … … We argue that feedbacks are largely concentrated in the tropics, and the tropical feedbacks can be adjusted to account for their impact on the globe as a whole. Indeed, we show that including all CERES data (not just from the tropics) leads to results similar to what are obtained for the tropics alone – though with more noise. We again find that the outgoing radiation resulting from SST fluctuations exceeds the zerofeedback response thus implying negative feedback. In contrast to this, the calculated TOA outgoing radiation fluxes from 11 atmospheric models forced by the observed SST are less than the zerofeedback response, consistent with the positive feedbacks that characterize these models. …. …The heart of the global warming issue is so-called greenhouse warming. This refers to the fact that the earth balances the heat received from the sun (mostly in the visible spectrum) by radiating in the infrared portion of the spectrum back to space. Gases that are relatively transparent to visible light but strongly absorbent in the infrared (greenhouse gases) interfere with the cooling of the planet, forcing it to become warmer in order to emit sufficient infrared radiation to balance the net incoming sunlight (Lindzen, 1999). By net incoming sunlight, we mean that portion of the sun’s radiation that is not reflected back to space by clouds, aerosols and the earth’s surface. CO2, a relatively minor greenhouse gas, has increased significantly since the beginning of the industrial age from about 280 ppmv to about 390 ppmv, presumably due mostly to man’s emissions. This is the focus of current concerns. However, warming from a doubling of CO2 would only be about 1C (based on simple calculations where the radiation altitude and the Planck temperature depend on wavelength in accordance with the attenuation coefficients of well mixed CO2 molecules; a doubling of any concentration in ppmv produces the same warming because of the logarithmic dependence of CO2’s absorption on the amount of CO2) (IPCC, 2007). This modest warming is much less than current climate models suggest for a doubling of CO2. Models predict warming of from 1.5C to 5C and even more for a doubling of CO2. Model predictions depend on the ‘feedback’ within models from the more important greenhouse substances, water vapor and clouds. Within all current climate models, water vapor increases with increasing temperature so as to further inhibit infrared cooling. Clouds also change so that their visible reflectivity decreases, causing increased solar absorption and warming of the earth. Cloud feedbacks are still considered to be highly uncertain (IPCC, 2007), but the fact that these feedbacks are strongly positive in most models is considered to be an indication that the result is basically correct. Methodologically, this is unsatisfactory. Ideally, one would seek an observational test of the issue. Here we suggest that it may be possible to test the issue with existing data from satellites.
The extreme AGW paradigm pushers have anchored the media with an absurdly stated temperature rise for a doubling of atmospheric CO2. A ‘projection’ from a model that is fundamental incorrect is not relevant to the discussion of climate change. The UN and the EU started with the assumption that a massive new UN and EU bureaucracy would need to be created and funded to monitor and limit CO2 emission. This is the justification for a super government, a government to govern all countries, staffed by the EU and UN. The IPCC ‘research’ and reports were to be written to justify the funding of the new bureaucracy, the massive transfer of funds from the developing world to the third world, and the funding of the ‘green’ scams.
If you are interested in the details concerning the extent of this fiasco I would highly recommend reading Christopher Booker’s ‘The Real Global Warming Disaster: Is the Obsession with ‘Climate Change’ Turning Out to be the Most Costly Scientific Blunder in History?’ I have read it twice. AGW has become a mania among the liberals. The parasites have moved in to take advantage of the mania and liberal tenancies to spend public money and think later.
William Astley:
The AGW theory does not predict. It projects. There is a difference between a prediction and a projection that is quite important.
What I cannot understand about climate science is that the wrong answer makes the reality just having a pause. In other branches of science or in engineering the wrong answer means you reject the theory as junk. Remember this is science that was right beyond question, not just probably right, and questions got you rated alongside concentration camp guards or at the very least as closet Nazis. There should be no new factors in proven beyond doubt science. All Biological and geological factors should have been either modelled accurately or have been proven beyond any question to have no effect.
As for excuses involving smoke particle action that has zero excuse value given it was known and studied pretty well by the Victorians who had even quantified the effect around Manchester.
In reply to:
Terry Oldberg says:
April 17, 2013 at 9:58 pm
William Astley:
The AGW theory does not predict. It projects. There is a difference between a prediction and a projection that is quite important.
William:
The correct mantra is the general circulation models do not predict, they make projections. The logic for that statement is that there are other variables that can affect climate. There is however a qualification in the statement the GCM do not make predictions, they make projections.
Theories do make predictions. One of the necessary components by definition of a theory, is the theory’s predictions. Think of it as the essential logic of a theory.
There are two related ‘predictions’ for the extreme AGW theory.
1) In the case of the tropical tropospheric warming at roughly 10 km, that is a fundamental pillar of the AGW theory. If there is to be substantial warming (say even 1C for a doubling of atmospheric CO2) of the planet due to the increase atmospheric CO2 there needs to be tropical tropospheric warming to drive the warm. The observations indicate that there is neither warming in the tropics and in addition there is no tropical troposphere warming. These two observations support each other.
2) As there are a limited number of climate forcing functions, the general circulation models do in fact make a prediction. As atmospheric CO2 was risen and is rising, planetary temperature cannot stop rising. The CO2 forcing mechanism cannot turn on or off.
This is an interesting line of discussion. I have been thinking of a physical explanation as to why there is no tropical tropospheric warming. I will move the essence of this discussion to Roy Spencer’s thread.
William Astley:
Thanks for the interesting response. A scientific theory is built upon the underlying statistical population. Can you describe the events in the statistical population that underlies the extreme AGW theory?
Terry Oldberg:
Your post at April 17, 2013 at 9:58 pm says
No!
The IPCC projects and predicts.
A projection is an extrapolation and a prediction is a forecast.
At April 16, 2013 at 3:40 pm I cited a clear example (with citation, quotation, link and explanation) of an IPCC prediction.
The AGW-hypothesis (n.b. it is not a theory) PREDICTS that the globe will warm in response to anthropogenic emissions of GHGs.
Your long and muddled screed at April 17, 2013 at 4:17 pm demonstrates you do not understand this. But at every opportunity you make a post saying
“The AGW theory does not predict”
IT DOES. It predicts the globe will warm in response to anthropogenic emissions of GHGs.
There is another character who keeps posting on WUWT to claim that surface tension prevents heating of water from above. You and he each fail to explain or justify your assertions when pressed. This failure is because you have each gained a notion which you have become convinced is true although it is plain wrong.
I ignore the ‘surface tension guy’ because his claims are of no consequence. But your false assertions inhibit dissemination of the fact that climate model predictions have failed. Hence, your false assertions merit refutation.
Richard
richardscourtney:
As you had made no apparent progress in understanding the equivocation fallacy and its role in climatological arguments, yesterday I attempted a friendly exit from my conversation with you. However, by your latest message you continue this conversation.
The content of your message suggests that you remain baffled by the equivocation fallacy and it pertinence to global warming research but I cannot have a productive conversation with you about errors in the methodology of this research until you come up to speed on it. It you were to attain mastery over this topic, you would then know why it is logically crucial for terms used in making methodological arguments to be defined unambiguously. Consequently, you would understand why I have gone to the trouble of disambiguating this terminology. In your current state of mind, you continually frustrate me by re-introducing ambiguity into this terminology thus reversing my work.
Henry@RMB
if you were to study the absorption spectra of water you would find that water absorbs strongly in the UV area and also a little bit in the IR.
That means that only in these wavelength areas of the incoming radiation, the radiation is – and will be – converted to heat in the water.
Hence the importance of a small change in concentration of ozone (and HxOx and NxOx) at the TOA. When it becomes more, as currently it does, it can and will back radiate a bigger portion of incoming UV. This lowers the heat coming into earth.
In turn, when less heat comes in, the differential between 0 and 90 degrees latitude changes, leading, on average, to more cloud formation at lower latitudes and less at higher latitudes. This amplifies the observed cooling effect as it reduces total insolation of earth significantly.
http://blogs.24.com/henryp/2013/02/21/henrys-pool-tables-on-global-warmingcooling/
Terry Oldberg:
At April 18, 2013 at 1:23 pm you say and ask William Astley:
Before anybody gets bogged-down in trying to answer that:
Can YOU define what YOU mean by a “statistical population”?
I, Willis Eschenbach, and others have repeatedly put this question to you but to date you have failed to provide an answer.
Your question is meaningless unless and until you provide an answer to the question I have posed to you.
For reasons of clarity and transparency, I state that I think your entire message I quote in this post is nonsense which sounds ‘sciencey’.
Perhaps you can show me to be wrong by answering another question by way of illustration.
Case (a)
It was a scientific prediction when Halley said a comet would return in a specific year, and his hypothesis of climate orbits was confirmed when the comet did return as predicted.
Case (b)
It was a scientific prediction that the IPCC said “committed warming” would occur in the first two decades of this century as a result of anthropogenic GHG emissions, and the hypothesis of AGW is disconfirmed by the failure of that “committed warming” to occur.
What was the “statistical population” in Case (a) and how does that differ – according to you – from the “statistical population” in Case (b)?
Richard
richardscourtney:
In the text of recent messages from you, I find examples of the ad hominem fallacy. In introducing these irrelevant and misleading entities into our debate is your purpose to try to win this debate while holding a weak hand by switching the issue from the equivocation fallacy in climatological arguments to flaws in my character?
I’m surprised to find that you are unclear on the definition of “statistical population” yet feel qualified to debate methodological issues of scientific investigations. You can find the URLs of Web pages providing definitions via a Web search.
Terry Oldberg:
I can only understand your post at April 18, 2013 at 2:00 pm to be saying you do not know what you mean by a “statistical population”.
I repeat
Can YOU define what YOU mean by a “statistical population”?
Please, no more evasions, no more obfuscations, and no more pretence that you have arcane knowledge which others should obtain for themselves.
Your ‘sciencey’ soundbites are meaningless noises unless and until you answer this simple question.
Richard
Terry Oldberg:
Your post at April 18, 2013 at 5:46 pm again demonstrates your appalling ignorance of logic.
It is NOT an ad hom. to insist a questioner defines the terms used in his/her question and then to state the obvious inference when provision of the definition is refused.
You are making the ridiculous assertion that the AGW-hypothesis – and climate models which emulate it – don’t make predictions and projections. That assertion is built on whatever mystical meaning you are applying to “statistical population”.
I repeat
Can YOU define what YOU mean by a “statistical population”?
Perhaps you don’t understand the question, so I will rephrase it.
What is the “statistical population” which you say is needed for the AGW predictions (e.g. as presented by the IPCC) to exist?
Your continued arm waving is demonstrating the falseness of your assertions for all to see.
Richard
PS I am not debating anything. I am successfully inducing you to expose the falseness of your unfounded and illogical proclamations which inhibit dissemination of the fact that predictions of climate models have failed.
richardscourtney:
As you may know, when a debate is conducted under the rules of logic, it is permissible for a debater to attack one or more of his opponent’s claims through refutation. In refuting a claim, one demonstrates that this claim is inconsistent with facts or with one or more logical principles. Thus, for example, it is logically permissible for you to attack my claim that the climate models of AR4 lack underlying statistical populations through identification of the populations that I claim to be missing.
It is impermissible for a debater to attack his opponent’s character, for his character is unrelated to the issue under debate. Thus when this issue is the existence of statistical populations underlying specific climate models it is impermissible for a debater to characterize his opponent as having an “appalling ignorance of logic.” For a debater to do so is to make his opponent’s alleged ignorance of logic the issue when the issue is the existence of the statistical populations.
Regarding my definition of “statistical population,” it is identical to the definition in the field of mathematical statistics. As you are capable of looking up this definition, I do not thwart you if I leave it up to you to determine what this phrase means.
@ur momisugly Terry Oldberg says:
April 19, 2013 at 8:43 am
Introducing a term that an argument is reliant on and then, when asked, not being willing to define the precise meaning with which you use it, instead referring the questioner to an alternative unspecified reference, and inviting them to interpret meaning from that, invites confusion and is not a good look.
That is not how things are done.
jc:
As the term “statistical population” is rigorously defined in mathematical statistics, clarity is not lost in referring Richard to the literature of that discipline for his definition. Under ordinary circumstances, I would respond to a request such as Richard’s as a matter of courtesy. However, in the past he has used responses to similar requests as launching pads for ad hominem arguments. To refer him to the literature serves the purpose of depriving him of a target for additional attacks.
Terry Oldberg:
I repeat:
What is the “statistical population” which you say is needed for the AGW predictions (e.g. as presented by the IPCC) to exist?
Richard
@terry Oldberg says:
April 19, 2013 at 10:26 am
A Problem
You refer him to the literature.
The literature is unspecified.
He consults what he takes to be “the literature”.
Neither he or you can confirm on information exchanged that this is what you take to be the literature.
He derives meaning from this literature which may or may not be that which you base your understanding on.
He returns to argumentation with the meaning he has derived from this process being the sole basis of his usage of it and interpretation of your usage of it.
He does not know if his understanding strictly accords with yours.
You do not know if your understanding strictly accords with his.
The term therefore remains unusable in any process requiring precision since it is based on untested assumptions by both parties.
A definitive position that is reliant on it is therefore impossible.
To have the capacity to arrive at a definitive position requires agreement on meaning of terms.
Where there is any uncertainty at all this must be explicitly addressed.
As a result of the above, uncertainty must exist.
Therefore the meaning of the term must be addressed.
Or the term rejected.
You have introduced the term.
His argumentation can proceed on the basis your meaning has not been demonstrated, and this therefore invalidates anything based on it. His argument does not require meaning to be explicit and exact.
Your argumentation cannot proceed without reliance on this term, so its meaning must be made clear, and this accepted. Your argument requires meaning to be explicit and exact.
It is beholden on you having introduced a term, and claiming it as a basis for your argumentation, to make its meaning clear.
jc:
Your description is inaccurate. That no statistical populations underlie the climate models of AR4 is not a premise to an argument but rather is a conclusion drawn logically from facts uncovered through structured research and presented in a peer reviewed article ( http://judithcurry.com/2011/02/15/the-principles-of-reasoning-part-iii-logic-and-climatology/ ). Under the norms of science, if a person does not like a conclusion from an article, his or her recourse is to submit a refutation for peer review and contingent publication. No norm requires the authors of peer reviewed and published articles to submit to badgering in internet blogs or provide free consulting for bloggers.
jc:
At April 19, 2013 at 1:22 pm you say to Terry Oldberg
He cannot.
I knew he could not because I learned that in previous attempts to understand his “equivocation fallacy”.
My purpose in this discussion is to reveal to all that he cannot “make its meaning clear”. And as you say
Yes. That is precisely what I am saying. But Terry calls that an ad hom.
Richard