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Climate Hustle

Separating signal and noise in climate warming

Posted on 5 December 2011 by John Hartz

The following is a reprint of a news release posted by Lawrence Livermore National Laboratory on Nov 16, 2011.


A National Oceanic and Atmospheric Administration (NOAA) weather satellite. Image courtesy of NASA.

In order to separate human-caused global warming from the "noise" of purely natural climate fluctuations, temperature records must be at least 17 years long, according to climate scientists.

To address criticism of the reliability of thermometer records of surface warming, Lawrence Livermore National Laboratory scientists analyzed satellite measurements of the temperature of the lower troposphere (the region of the atmosphere from the surface to roughly five miles above) and saw a clear signal of human-induced warming of the planet.

Satellite measurements of atmospheric temperature are made with microwave radiometers, and are completely independent of surface thermometer measurements. The satellite data indicate that the lower troposphere has warmed by roughly 0.9 degrees Fahrenheit since the beginning of satellite temperature records in 1979. This increase is entirely consistent with the warming of Earth's surface estimated from thermometer records.

Recently, a number of global warming critics have focused attention on the behavior of Earth's temperature since 1998. They have argued that there has been little or no warming over the last 10 to 12 years, and that computer models of the climate system are not capable of simulating such short "hiatus periods" when models are run with human-caused changes in greenhouse gases.

"Looking at a single, noisy 10-year period is cherry picking, and does not provide reliable information about the presence or absence of human effects on climate," said Benjamin Santer, a climate scientist and lead author on an article in the Nov. 17 online edition of the Journal of Geophysical Research (Atmospheres).

Many scientific studies have identified a human "fingerprint" in observations of surface and lower tropospheric temperature changes. These detection and attribution studies look at long, multi-decade observational temperature records. Shorter periods generally have small signal to noise ratios, making it difficult to identify an anthropogenic signal with high statistical confidence, Santer said.

"In fingerprinting, we analyze longer, multi-decadal temperature records, and we beat down the large year-to-year temperature variability caused by purely natural phenomena (like El Ninos and La Ninas). This makes it easier to identify a slowly-emerging signal arising from gradual, human-caused changes in atmospheric levels of greenhouse gases," Santer said.

The LLNL-led research shows that climate models can and do simulate short, 10- to 12-year "hiatus periods" with minimal warming, even when the models are run with historical increases in greenhouse gases and sulfate aerosol particles. They find that tropospheric temperature records must be at least 17 years long to discriminate between internal climate noise and the signal of human-caused changes in the chemical composition of the atmosphere.

"One individual short-term trend doesn't tell you much about long-term climate change," Santer said. "A single decade of observational temperature data is inadequate for identifying a slowly evolving human-caused warming signal. In both the satellite observations and in computer models, short, 10-year tropospheric temperature trends are strongly influenced by the large noise of year-to-year climate variability."

The research team is made up of Santer and Livermore colleagues Charles Doutriaux, Peter Caldwell, Peter Gleckler, Detelina Ivanova, and Karl Taylor, and includes collaborators from Remote Sensing Systems, the National Center for Atmospheric Research, the University of Colorado, the Canadian Centre for Climate Modeling and Analysis, the National Oceanic and Atmospheric Administration, the U.K. Meteorology Office Hadley Centre, and Lawrence Berkeley National Laboratory.

Additional information:

Founded in 1952, Lawrence Livermore National Laboratory provides solutions to our nation's most important national security challenges through innovative science, engineering and technology. Lawrence Livermore National Laboratory is managed by Lawrence Livermore National Security, LLC for the U.S. Department of Energy's National Nuclear Security Administration.

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Comments 1 to 40:

  1. All of Science is about signal to noise ratio. The trouble with pseudo scientists and ignorant crackpots is that they cannot differentiate between the two or conveniently ignore the difference.
    Nearly all of Science is counterintuitive and unless you have studied up to at least a first degree level your 'common sense' will inevitably fail at interpreting what is really going on.
    Charlatans and con-men have known this for a long time. Otherwise how do you explain the success of many scams on supposedly intelligent victims.
    What is at stake now is the future habitability of our whole planet. We cannot pick up the pieces after the scam artists have won. Bert
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  2. Even if the climate was not changing and in danger of trashing human society, there are many other reasons to break our dependence on fossil fuels
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  3. Consistent temperature records are necessary for predicting future temperatures in a world with doubled or more CO2. The longer the record, the better. My question is, "How do you weight the results of different climate models?" "What changes are likely to happen as the speed of change exceeds past experience?" I know this is a current topic of much discussion for the upcoming IPCC report. Which proxies are they likely to use for supporting their findings? Will projected CO2 level alone be used or projected CO2 plus projected CO2 equivalents?
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  4. Climate models dont actually use past records for prediction. The value of proxies is for validation that you have the physics right. The models predict future temperature by looking at all forcings (all GHG, aerosols, solar etc) with scenarios used to look at different possible sets of emissions.

    For model validation, you can estimate past forcings, (eg proxies or measurements for solar, GHGS, aerosols) put them into the models, and compare output temperatures with proxies for temperatures. If the hindcast isnt within the range of uncertainties, then the physics in the model is wrong.
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  5. I am deeply worried, having looked at the mathematical background to the current climate models, by the insistence that there is no dynamic linkage between weather and climate. This is known to be false, from the science of non-linear systems, or dynamics. There is a belief that by the application of ‘smoothing functions’, these variations in systematic boundary conditions may be ignored. I would point out that in the field of oscillator theory, this was proven to be false in 1988, in the landmark PhD thesis of David M. Harrison at Leeds University. David conclusively proved that the lack of correlation between real noise performance, and the then ‘theoretical models’ was the introduction of smoothing functions to allow the generation of closed integral solutions. This investigation was sparked by my observation that the value of close to carrier noise terms in electronic oscillators was often 10 – 100 times worse than the open loop noise. This had led, by modellers, to the introduction of coefficients for these noise terms that could not be related to the physics of operation. David implemented a full, non-linear solution, and showed clearly how the noise terms were multiplicative, leading to a dramatic increase in noise amplitudes at low frequencies. Such as model applies to any dynamic system, and can lead to a system with more than one, potential stable amplitude, and the system jumping from one state to another in a very short timescale.
    In the case of climate, the noise variables are of very high energy, unlike the noise perturbations in an electronic oscillator. This is a true dynamic model, unlike the crude Laplacian ‘steady state’ model favoured by climate modellers. Laplace, because he was incapable of solving problems in dynamics, reduced all to statics, a system of closed integral curves which allowed the formulation of integrals schoolboys could handle. In this he followed Lagrange. I do not doubt that climate change is occurring, and that man has made some contribution, but I doubt our ability to accurately predict the outcome on the basis of the reasoning of some not very good French mathematicians of the 18th century. No Langrangian or, Laplacian model can be relied on for development as a time series solution, and crude attempts to introduce coupling terms will lead the analyst astray. It is now accepted that linear approximation reduces the potential behaviours in a physical system, and in the case of a simple non-linear system – an oscillator, led us up the garden path for decades. In the case of a system as complex and multivariate as climate, we should not be surprised if it springs a few surprises on us. We seem prepared to hang all on a few decades of data, and a very limited understanding of the dynamic behaviours involved. We cannot avoid jumps in a non-linear system by pretending they cannot occur – and the potential jumps could be in any direction!
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    Moderator Response: Your personal skepticism of the ability of climate models to predict must take a back seat to the empirical evidence that climate models do predict easily well enough to feed decisions to act; in the Search field at the top left of this page, type "models are unreliable" without the quote marks. Also search for "chaos."
  6. 5, mervhob,

    Your opinion is, unfortunately, founded on a large number of false assertions/assumptions. In fact, I'm not sure there is any foundation at all beneath your conclusions.

    Rather than address them point by point (which would be tedious), I would suggest that since the subject is of such interest to you, your best course would be to educate yourself on how climate models actually are designed and operate.

    There are a great number of resources available on the Internet, including a number of in-depth books on how to design and implement climate models, and several climate models that you can actually download and run yourself, as well as reading the actual source code (which I myself have done, although not to any great extent).

    But, as I've already said... most of your foundation statements are false. You do not appear to have an actual grasp of how climate models operate. Instead, you appear to be basing your opinion on the fanciful descriptions of such models that you might find in ignorant venues such as WUWT and others, or on false premises and assumptions inferred purely from your own experience and education in EE or signal theory.

    This site is a decent place to start to better understand the models at a very high level, but really, to learn what you need to know to be able to speak knowledgeably on the subject, you'll need to go much more deeply into it than this site offers.

    Google and time are your friends in this. Hasty assumptions and misinformation delivered by sites that specialize in misinformation are not.
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  7. mervhob, you might also like to look at:
    FAQ on climate models and Part 2 from the modellers themselves.
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  8. It is a very poor mathematician that does not accept the limitations of the tools he uses, and their inapplicabilty to certain types of problems. I do not doubt your ability to model a simple outcome - a rise in temperature. What I question is the ability of such a model to quantify the the effects of such a temperature rise, except in equally simplistic terms.
    The empirical evidence has already started to diverge from the model - the model did not predict the dramatic increase in the rainfall around the Tropic of Cancer, and neither did it predict the very dry conditions in much of the Northern hemisphere in winter. I find the idea that a non-linear model can be 'linearised' and still represent long term behavior baroque - the methods of Lagrange and Laplace only work for small perturbations - hence the good correlation to temperature in the short term. But please don't consider such a model dynamic - it is not.
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  9. 8, mervhob,

    It is a very poor carpenter who looks at a cement and steel skyscraper, and says that it cannot exist because he is a carpenter and he knows one could never fabricate such a structure using wood.

    Your presumption that models "linearize" things is flat out wrong.

    Again, you are speaking from a position of complete ignorance. Educate yourself properly about how the models are constructed before casting arrogant aspersions and speaking condescendingly about things that you misunderstand.
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  10. Climate models have no skill at decadal or shorter predictions. No such claim is made and that limitation is readily accepted - the subject of many papers. Again it seems that you are making a raft of assumptions without actually studying how climate modelling is done first.
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  11. scaddenp

    Thanks for the links, but they don't answer any questions. There is an almost deadly silence on the mathematical background to climate modelling - I was shocked by the statement that smoothing functions were in common use, with seemingly little understanding of their effect on dynamics. This is hardly surprising as most graduates leave university with the delusion that they can solve any problem using linear algebra. Newton would not agree, and we have had to return to many of the tricks of the fluxional calculus, in order to solve non-linear problems.
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  12. Sphaerica,

    So the use of smoothing functions doesn't linearize the system? That assumption would not be accepted by a professional mathematician. It has been a tool of classical analysis for the last 200 years. However, it proved to be of little value in dynamics. I suggest you improve your own education, in particular take a look at the statements of mathematicians in the early 19th century, where it was widely stated that the French school had abandoned dynamics and replaced it with statics - the mathematics of the known solution. This is the mathematics commonly taught today. However, if you were fortunate enough to have a mathematical education in Russia, you would find that they teach non-linear principles, and linear methods are always treated as an approximation, with sound advice on their limitations.
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  13. mervhob @11, you are making a number of unsupported claims. When you said you were, "... shocked by the statement that smoothing functions were in common use", I looked for that statement in the article above, and could not find it. Nor could I find it in either of the two FAQs linked by scaddenp. Further, you have provided no examples any models replacing a dynamic chaotic function with a smoothed approximation. Absent sources or examples to back up your claims, it is difficult to take them seriously.

    Please note that providing technical discussion on this point, while welcome, may be of topic for this post. I suggest you shift the discussion to this more relevant thread. You can always link back to that discussion in support of points directly relevant to this topic.
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  14. mervhob:

    If you really want to know about the state-of-the art in climate modeling you could start by immersing yourself in the materials about the MIT Integrated Global System Model posted here.

    From the tenor of your posts, I suspect that you may just be trying to stir up a hornet's nest on this comment thread by slinging a lot of hash about climate models.
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  15. mervhob

    I do not know what are you smoking. Highly non-linear, but as you may experience everyday it does not jump around between steady states at the global scale. There are no hidden states in the system. Similar to RANS a time-averaging that allows you to ignore local chaotic behavior of turbulence but still lets you make macroscopic predictions of flow behavior. You can add any physics you want, radiation, complex non-linear kinetics etc.. etc.. still tractable under specific assumptions. If you are the genius that uncovered the mathematical scandal please put up or shut up....
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  16. mervhob - what makes you believe that climate modellers are not competent mathematicians? So far you are pontificating about something you clearly know very little about. Have you read any papers on the mathematical foundations in climate modelling at all? Note also that there are 20 different modelling groups from around the world participating in CMIP5 so lets forget the "my countries education is superior to yours" bit.
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  17. 12, mervhob,
    So the use of smoothing functions doesn't linearize the system?
    Strawman. I never said any such thing. No one has. Tom Curtis already said it at 13, but since the comment was directed at me, please let me reiterate. Please provide a citation for where (anywhere) that someone in a position to know such things says that smoothing functions are in common use in climate models.

    You are fabricating arguments and lecturing everyone about the mathematics of linear systems when it is not an issue, because climate models are not implemented as linear systems, and the mathematics background of climate modelers is very, very good.

    Again, instead of lecturing someone you don't know on the mathematics that you presume they (I) don't know, please do as you have been instructed. Your understanding of how climate models are designed and implemented is pathetically bad. Your Russian education in mathematics may be good (but not as good as my American education, I'll wager), however it is irrelevant when the topic at hand is not mathematics (of any sort) but instead complex, state-of-the-art climate modeling techniques.

    Please educate yourself before continuing this discussion. The following statements that you have made are categorically false, and until you have learned enough to understand this, the conversation amounts to you blustering and refusing to listen:
    • There is a belief that by the application of ‘smoothing functions’, these variations in systematic boundary conditions may be ignored
    • the crude Laplacian ‘steady state’ model favoured by climate modellers
    • It is now accepted that linear approximation reduces the potential behaviours in a physical system
    • We seem prepared to hang all on a few decades of data, and a very limited understanding of the dynamic behaviours involved
    • There is an almost deadly silence on the mathematical background to climate modelling
    • smoothing functions were in common use, with seemingly little understanding of their effect on dynamics
    When you have learned enough about how climate models work to understand that all of these assertions are false, and that the rest of your statements about mathematics, dynamics, Laplace, Lagrange and linear systems simply do not apply to the topic of modern climate models, then a meaningful discussion can proceed from that point.

    If you seriously consider yourself qualified to understand, then the best place to start is here, the GISS GCM ModelE. You can view the documentation, download the source code, and compile and run it yourself.

    There are myriad other sources of information on the web, including, as you have already been told, books on climate modeling, web pages on climate modeling, source code, models you can run online, models you can download, and more. There is no excuse to speak without understanding.

    Climate models are not linear systems.



    Then we'll talk.
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  18. 5,8,12 mervhob

    Since you make completely false and outrageous claims about what mathematicians know and claim to know and claim to know, I am free to do the same to you.

    You clearly have never heard of functional analysis: Fredholm operators, Hilbert spaces, Soboleve spaces.
    It was created by extremely intelligent mathematicians in the early half of the 20-th century to extract results about the properties of non-linear differential equations to deal with the fact that they could not figure out a way to solve these equations exactly. These mathematicians know more than anyone else the difficulties and limitations of their work. And computer programmers know better than any non-programmers the difficulties and limitations of their work.

    There is a niche of mathematics called differential algebra which is devoted entirely to finding exact solutions. Exact solutions can be defined as finite compositions of certain well-known functions and quadratures (integrals) of such compositions.
    I personally know many mathematicians who work night and day in this area, searching for new exact solutions. Check out the weekly Kolchin Seminar in Differential Algebra at Hunter College in New York City.

    You DO know that any partial differential equation (PDE) has a multivariable Taylor series solution that can be computed iteratively from the PDE itself by repeated differentiation, right?

    If Laplace and Lagrange are "bad" mathematicians, as you claim, then by the same standards WUWT posters and Monckton and Alex Jones don't even deserve recognition as human. Laplace - inventor of the Laplace transform.
    Lagrange was the discoverer of the Lagrange Interpolation Formula. And Lagrange who achieved the single greatest triumph over the nonlinearity of math still to this day: the Lagrange Inversion Formula for inverting ANY given analytic function, z=g(w), to find w=f(z), and expressing the coefficients of the powers of z in the power series expansion of H(f(z)) for an ARBITRARY function H(t).

    I'm sure you know all about these achievements, since you claim to be such an expert.
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  19. When will you deniers get it through your heads that words - prose - like the kind you and I are typing into these textboxes right now - are MODELS of the real physical world? Hence, you already ARE modeling the world.

    The difference between all the words by all the deniers
    - or even lectures by non-deniers meant to educate the public, but which must necessarily resort to imperfect metaphors or analogies for clarity and brevity -
    versus mathematical models, is that
    only mathematical and logistical models can model

    1) the magnitude of things -
    only math can tell you when one thing is bigger than another, or that there is more of something than another, or that something occurs more frequently than another,
    or that one form of energy gets much more government subsidies than another

    2) logical consistency of cause and effect:
    i.e. if (as deniers always do) you blame some poor person in India for failing to do enough to get THEIR government to pass stronger restrictions on CO2 emissions,
    then you must blame (as deniers never do) blame some comfortable person in America or Australia for failing to do enough to get THEIR governments to act, etc

    3) test hypothetical what-if scenarios
    and assert if-then statements

    4) no human can memorize all the boundary and initial conditions (i.e. data) that goes into these models.
    Only computers can.

    5) the difference between math models and computer models is: one can test only one "what-if" scenario in a computer model at a time, or, more accurately, one can test only a finite number of them. A math theorem proves assertions that can knock out an UNCOUNTABLY INFINITE number of scenarios, say, if a given forcing function f:R->R, f(t), t=time, is unknown, we can still derive important statements from a math theorem.

    e.g. if x = some physical variable, x'+x=f(t), we know then that x(t)=integral of exp(t)*f(t) times constants

    mervhob: here's a quiz: what is the cardinality of continuous functions, f:R->R, from reals to reals?

    So, saying math and computer models are wrong is like saying language is wrong and should not be used or trusted for making predictions or assertions of any kind.
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  20. 5 mervhob

    "I am deeply worried"

    Also, you're concern trolling.
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  21. Mervhob is trying really hard to sound very educated but he fails to produce any substantiation on any single one tof the terrible accusations he throws around. Could we have some pointers and links to some real substance showing how bad the situations is?

    As for calling Laplace and Lagrange "not so good mathematicians", once again, let us see links to mervhob's own work, so we all can be in awe before the revolutionary mathematical understanding that it surely is already spreading throughout the world. No doubt that one who calls Lagrange and Laplace in such derogatory terms has an intellect the like of which is witnessed every other century or so. I can't wait to see its products.
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  22. Sphaerica et al

    Russian mathematician’s re- initiated the interest in non-linear systems, after their abandonment at the end of the 18th century - I know of only a few American mathematicians that have contributed anything of importance. David's PhD used the asymptotic method of Boguilobov and Mitropolsky - I suggest you access it. The models currently displayed are based on energy balance, forcings and feedbacks. This is a classical 'steady state' scenario - as Poincare pointed out in 1899, the only reliable integrals we can form are those based on energy, 'vis viva'. Only then can we assume the existence of closed integral curves, and a solution. By definition, as energy is a scalar, there is no vectoral information, only increasing or, decreasing total energy.
    This we can relate to a single variable – temperature, with reasonable accuracy. However, using the same approach in a multivariate dynamic model we have to assume that single, linear ‘steady state’ exists as the bedrock around which the system is perturbed. This is the method of small perturbations as developed by Lagrange and Laplace, the replacement of a dynamic system with no closed integral curves by one where all integral curves are closed by definition. However, if there are non-linear states within the model, which can be accessed by a sufficiently large noise term, the use of ‘smoothing functions’ and integration destroys such behaviours in the model. Very simply, as we found with oscillator models, all non-linear behaviour is suppressed. It is argued that no such possibility exists with climate – with your current models how would you know? Let us say that the increase in freshwater melt from the Arctic ice so dilutes the water of the Northern Atlantic that the Atlantic conveyer turns off. The Atlantic Conveyor has been weakening since the 1980s. Such a change tips the system into a new state space very quickly, with very unpleasant effects for Northern Europe. I would argue that I can apply your assumptions, providing I have sufficient representative data over a long enough period of time to feel safe. Or, sufficient data from comparable dynamic systems. In the case of oscillators, measurement of the noise of a 100Mhz quartz oscillator over 10 sec gives me adequate data – 1 billion cycles worth. But even this proved in some cases a fool’s paradise, as oscillators demonstrating phase hits due to non-linearity merely showed a slightly raised integrated noise level, but had a devastating effect on digital signal links. You could treat the temporary loss of the Atlantic conveyer as the equivalent of a ‘phase hit’ – in overall energy terms it would be.
    This blog purports to deal with signal/noise effects – I looked at the paper by Santer et al, the noise signatures are very interesting – clear evidence of both 1/f noise and periodic terms, a very interesting dynamical system. However, the linear processing applied, low pass, high pass and band pass filtering is fairly simplistic – I would be tempted to apply a Bayesian filter to the same data, to see if the possibility of sustained trends developing, as you might with radar return data. (-Snip-) No, Laplace did not develop the Laplace transform method – Oliver Heaviside did – Carson transformed Heaviside’s method to one of definite integrals in the 1920’s. David Hilbert’s (-Snip-) foundered on the rock of Godel’s incompleteness theorem in the 1930’s. It is a myth that a non-linear system can be linearised by approximation, if the system is non-linear, it remains non-linear down to its smallest amplitude – Y. H. Ku states, in a paper on his acceleration plane method, ‘Nature is non-linear – even the pendulum of Galileo is controlled by a second order, non-linear equation.’ Those who doubt the sagacity of that remark can examine the performance of the Littlemore clock on the web.
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    [DB] "The Atlantic Conveyor has been weakening since the 1980s. Such a change tips the system into a new state space very quickly, with very unpleasant effects for Northern Europe."

    Based on what?  Source citation needed.

    Inflammatory snipped.

  23. 22, mervhob,

    Do you know anything about computer programming and modeling, or is your only frame of reference mathematics? Computer modeling is inherently non-linear (computers are, after all, based on the concepts of iteration, decision making and branching -- complex iteration), even when some linear techniques are (necessarily) used in base calculations. Really, comparing mathematics to computer algorithms is wildly inappropriate.

    And, once again, you go on and on about what you know, without recognizing what you don't know, or more importantly that, true or not, nothing that you say is applicable to the problem at hand. None of what you say applies to climate models, because they do not work the way you claim they work.

    You have been corrected repeatedly, and yet you repeat the categorically false statement statement that "...all non-linear behaviour is suppressed. It is argued that no such possibility exists with climate..."

    This is false. It is flat out, categorically false. Please stop repeating falsehoods unless you are able to support the assertion with a clear and unambiguous citation... something you have been asked repeatedly to do and yet the requests are repeatedly ignored.

    I would suggest that if from this point on you fail to support your assertions, your comments amount to trolling and should be moderated.

    You must accept that as evidenced by your statements your own understanding of climate modeling is pitiful.

    You need to educate yourself and stop pontificating as if everyone else is stupid and you are a genius. You have been directed to multiple sources of information. Please take advantage of them, and put your energy into improving your knowledge base rather than arguing from ignorance.
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  24. mervhob:

    You are entitled to your opinion regarding climate models. You are not entitled to have your opinion taken seriously if you are not going to substantiate it.

    Your posts on this thread thus far have consisted of a great many unsupported assertions and no small amount of contempt for the researchers working on climate models (including their continual improvement).

    Without your providing calculations or citations to support your claims, on what basis should interested laymen such as myself consider any of your criticisms valid?
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  25. Look this site is about discussing the science of climate change. Mervhob should either put up (reference published science to support his/her assertions) or be shut up.
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  26. I see that mervhob continues to talk about something else than the subject of this thread and continues to throw unspported assertions.

    Considering the mathematical background he/she suggests having, it would be interesting to have an opinion on the subject of the thread. As for the rest, I am once again pleasantly surprised to see how tolerant SkS moderators are.

    A very quick search on "The Atlantic Conveyor has been weakening since the 1980s" returned these:
    By none other than the denier's favorite ocean guy, Josh Willis. Quote "Combining satellite and float measurements, he found no change in the strength of the circulation overturning from 2002 to 2009. Looking further back with satellite altimeter data alone before the float data were available, Willis found evidence that the circulation had sped up about 20 percent from 1993 to 2009." Not sure if this speeding up has been confirmed by other papers, as I said, this was a quick, straight Google search.

    There is also Zhang et al for longer term behavior:

    Meinen et al (2006) and Schott et al (2006) also failed to confirm the results of Bryden et al (2005). Doesn't mean that the slowing could not happen in the future but so far the evidence is not in the litterature. I am not sure what models forecast about that specific feature. I am sure that mervhob's statement was pulled out of you-know-where.

    I would like now to encourage all to discontinue the OT discussion (I know, I just added to it), as the subject of this thread is actually quite interesting, and should be even more so for someone with math background.
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  27. On the subject of variability and short term "trends" (an abuse of the word, since short term with trend really makes an oxymoron):

    Foster and Rahmstorf refine the statistical methodology to separate short term fluctuations from long term trends.
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  28. 26, Philippe,



    Comments on models (but only if supported by references) should be made on this thread:
    How reliable are climate models?
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    [DB] "Comments on models (but only if supported by references) should be made on this thread: How reliable are climate models?"

    Make it so.

  29. Philippe#27: "short term "trends""

    Foster and Rahmstorf 2011 (pdf here) make the case for separating the signal from the noise in a stunningly clear presentation.

    -- Foster and Rahmstorf 2011, Figure 8

    More to your comment, the warming rates F and R show stabilize when the start year for calculating the trend gets back to 1990 or so (their Figure 6). That says very clearly:
    -- The warming signal is present - and has low uncertainty - with 20 or more years of data.
    -- Any 'change in trend' (or 'hiatus' for that matter) based solely on a short time period (like a decade) is a statement with low certainty, as it is based on a time interval too short to eliminate the noise.
    -- There is thus no basis for saying that warming has stopped, slowed or changed course.

    All five data sets show statistically significant warming even for the time span from 2000 to the present.
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  30. I know this isn't entirely relevant to this thread and I apologise for this, but it was the best I could find for an answer to my question .
    Over at WUWT there is a thread in which someone has made the following comment:
    "....don’t go on about aerosols in China having a cooling effect, their coal plants are as clean as our and we’ve cleaned up more smog problems in North America and Europe inthe last 50 years than China can possibly compensate for….so….where’s the warming?"
    To my (probably not that well educated) mind the guy made a valid point that I had not thought of before. If China's current pollution is a major contributor to the dampening of the rise in global temperatures over the past few years, then why did pollution from the West not have the same effect. As far as I am aware, it is only in very recent times that North America and Europe have reduced their levels of pollution. I'm thinking of LA in particular here, as I know that it was not too long ago that the place was always covered in smog and that is no longer the case - but I am aware that this is just one example in one location and not necessarily entirely representative of all North America and Europe. Can anyone give me some facts or good links that address this point. Many thanks.
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  31. Hi, back again, but with just an observation this time and I think it is relevant as "fingerprints" are mentioned in the above article. Being someone who is not necessarily stupid but not that scientifically literate either, the "fingerprints" are the most convincing I have heard to persuade me that AGW is caused by CO2/human activity. Yet I am only familiar with these "fingerprints" as a result of looking at sites such as skeptical science. Why isn't it something that is regularly discussed and presented by scientists through the media and explained again and again. When I watch coverage of climate issues on the news here in the UK, I here about polar bears, arctic melt, freak weather, but to my mind the various fingerprints that point to CO2 as the main cause of climate change seems fundamental; yet it is to a large degree ignored and rarely discussed (at least in my experience). I am sure that if more exposure is given to the issue it could go a long way to convincing the many people who are uncertain or skeptical of the science due to ignorance and lack of this basic knowledge. Just a thought.
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  32. peacetracker:

    I have posted a link to your comment regarding fingerprints @31 on this thread and suggest any follow up go there where it is topical.

    I've just been called to dinner so I can't say more now, though I should like to once I have the opportunity tonight.
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  33. Peacetracker - We've posted a couple of recent-ish articles on aerosols (man-made pollution particles) See SkS posts: Why Wasn't The Hottest Decade Hotter? and Michaels Mischief #1: Continued Warming and Aerosols

    First up, East Asia and specifically China, saw a massive increase in coal burning in the last decade due to their similarly massive expansion in industrialization (coal-burning electricity plants to power manufacturing). Almost every developed country has shifted manufacturing of some shape or form to China because it is cheaper.

    Secondly, the Clean Air acts of the 1970's saw a dramatic reduction in sulfate pollution (the main light reflecting particles in aerosols) in both Europe and North America (sulfates not only reflect light, but cause acid rain and smog). The rapid industrialization after World War 2, is thought to have increased sulfate pollution to such an extent that it cooled global temperatures mid-century. This is known as Global Dimming. After the polluters were made to reduce sulfate pollution, global temperatures began climbing again (Global Brightening).

    See SkS post: Why did climate cool in the mid-20th Century?

    There is much legitimate debate on the "hiatus" or slowdown in warming over the last decade. In fact, some don't consider that there has been a slowdown at all (Foster & Rahmstorf [2011]). We'll just have to see how that plays out in the scientific literature, but it doesn't affect the rapidly expanding mountain of scientific evidence that indicates global warming is real, 'we dunnit,' and it's a potentially devastating problem that grows steadily worse the longer humanity ignores it.
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  34. peacetracker @30, in the mid to late 1990's China began to rapidly expand its use of coal without enforcing any clean air regulations. Since then it has begun enforcing such regulations, but not consistently. The result is that China emits much more S04 than does the US or Europe. This issue is discussed in detail at this page. It shows this image of aerosol optical depth from Jan 2000 to Dec 2006, which gives a fair comparison:

    Here also is an equivalent image for Jan 2005 to Jan 2010 for a more recent comparison:

    As is clear from these images, the person on WUWT simply made up the facts that best suited their argument, or at best greatly exaggerated the situation. (Some Chinese power plants are as clean as anything in the West, but most are not.)
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  35. 30, peacetracker,

    Regardless of cleanliness of their coal plants, what about sheer number of plants (and therefore the largest single factor in emissions)?

    From Tracking New Coal-Fired Power Plants from National Energy Technology Laboratory, Office of Strategic Energy Analysis & Planning:

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  36. While we are on the China Train, take the time to peruse this link from Shaping Tomorrow's World for some photographic documentation of the cleanliness of China's power plants and air that it's workers, citizens and children must breath.
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  37. 36, Dan,

    Wow. Scary pictures. Mordor never looked so good.
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  38. @peacetracker #31:

    I totally agree with you. "fingerprints" are the most convincing proof that manmade climate change is real and is happening now.

    It would behoove SkS to ratchet-up its coverage of the climate changes that scientists and people througouht the world are documenting and witnessing.
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  39. Thanks to everyone for your help. You have provided me with some very useful information. Cheers
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  40. 39, peacetracker,

    A quick note... you can find sources on the Internet which will show you that the USA has a lot more coal plants than China. This is true, because USA plants are much, much smaller in GW output, and what matters isn't how many plants you have, but how much coal you are burning.
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