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Comment on Climate models at their limit? by Robert

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You don’t understand me correctly.

You are arguing that by not taking action to change something, that we control it.

Please support that argument — that by not something, you are taking control — with facts.

You may also want to examine to further fallacies in your argument:

1. Your assertion that conservatism is associated with restricting the power of government. That’s historically wrong. Conservatism has always fought for a strong central government and against the liberal argument for individual rights in opposition to government power. Hated our democratically elected government and wanting to reduce its influence may or may not be philosophically correct, but in no possible way can it be considered “conservative.”

2. Your assumption that mitigating global warming can only be done by increasing the power of government. In reality, there are many things that could reduce greenhouse gas emissions by reducing the scope of government power — eliminating fossil fuel subsidies, for example, or replacing free-to-travel public highways with private toll roads.

You have allowed your hatred of government to push you into denial of reality, but both the science denial and the fear of the solutions is based in fantasy.


Comment on Climate models at their limit? by DocMartyn

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” Robert
Actually climate models can “hindcast” remarkably well.”

That’s because they are ‘fits’, not classical models. The models are more highly trained than circus seals. Any idiot can fit any line shape using reasonable guesses for 5 or more components, this is why they are criticized.

Comment on Climate models at their limit? by Alexander Biggs

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Thank you, Dave, for your comment on mine. We know exactly why a few grams of pigment make your car white and cooler. My point is that the IPCC failed to tell us exactly why carbon dioxide had such a powerful effect, betraying a certain arrogance on the part of the IPCC. Or perhaps they did not bother to investigate the IR absorption spectra of CO2. Either way, it invited scepticism of their results. See my web site.

Comment on Climate models at their limit? by k scott denison

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Sure, Dave. Add ~400 ppm of black pigment to a gallon of paint and see just how black it is.

Comment on Climate models at their limit? by John Carpenter

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WFGW, well… I’m not sure passionate is the right term for how I feel about how the money was spent, perhaps indifferent. My original point had more to do with Jim Cripwell’s statement that ‘climate models don’t serve any useful scientific purpose’… I disagree with that statement, it is false. whether the money spent on climate modeling has been wise or not is really secondary for me. It appears to be more important to Latimer as he brought it up.

Up thread Hank Z made an unsupported statement that investment in observational (empirical data collection) methods have suffered in comparison to money spent on climate modeling… I’m asking for some evidence for that because significant amounts of money has been spent on satellite observational equipment and I have never seen such data suggesting modeling gets significantly more. I could be wrong… I’m just asking a question.

Are there going to be useful ‘spin-offs’ of climate science that will realize a ROI? Dunno, I suggest you ask Judith Curry herself… she’s giving the longer term weather forecasting business a try as a spin off of her climate science knowledge coupled with modeling.

Comment on Climate models at their limit? by Robert

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What is the difference between an engineer and a scientist? Answer- nothing if someone is adequately informed on the specific topic.

It seems we have come to a direct statement of your delusions of grandeur. You’re not a scientist, but you think that doesn’t matter. I don’t see any reason I need to add commentary on that, except to say that your comments amply demonstrate that you are not “adequately informed on the specific topic.” So your sad hypothetical does not in any case apply to you, who cannot even tell the difference between predicting the future and recording the past.

Take your cue from Socrates. Learn the power of acknowledging all you don’t know.

Your “experience” at WUWT sounds similar to someone who has had a “bad experience” with someone of a different ethnic background and then generalizes to believe that anyone of that ethnic background must necessarily be inferior.

No matter how many times you play that card, it doesn’t trump reality. Pace 30 Rock, idiots are not a protected category. ;)

I picked the rough 20% figure based on looking at the last 20 years of reliable historical records and then believing that if I were developing a model to predict sea level rise I wouldn’t think it was a very good model if I couldn’t develop one that was better than simply looking at that historical record.

Exactly: you think scientist ought to be able to predict the future with the same accuracy as they observe the past. And you still don’t see why that’s nonsensical? Really?

What I wrote is that ENSO is a part of the systems performance and needs to be understood in order to model the system correctly.

Except as you point out, you know nothing about climate models so you have no idea if that’s true. You’re guessing. And you have no foundation in the subject to even make an intelligent guess. So you are left claiming that if you can’t predict the weather, you can’t predict the climate. If you were a physicist, or a climatologist, or had any background in science at all, you’d know that what you are describing is a classic mistake of thinking that short-term fluctuations determine long-term trends. But you’re not a scientist, so you don’t know that. That’s fine — I’m sure you build nice sewers. I wouldn’t want Michael Mann to build a rocket. The difference is, Mann doesn’t think that knowing how to do his job means he knows how to do yours.

Basically I’ve called your bluff. You did everything you could to try and sound like somebody able to critically evaluate climate science, but pressed on the details you totally fell apart, because you have absolutely no idea what you are talking about, and hope that phrases like “acceptable margin of error for a model is dependent on the specific attribute being modeled” and “20% figure is a notional figure” will fool people into thinking you have a clue.

Since I plowed right through that bluff to the big empty space underneath, I can see why you wouldn’t want to talk to me. I will continue to comment as I feel moved to do so, and you should feel absolutely free not to respond. You don’t have much to say in any case.

Comment on Climate models at their limit? by Berényi Péter

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<i><b>They must stop waiting for further certainty or persuasion, and simply act."</b></i> Under the circumstances that's the worst advice I can think of. In case of great uncertainty the best course of action is <b>not</b> to commit yourself to any specific action. Increase your flexibility instead, strengthen your weak points, build reserves and be ready to move vigorously as soon as a clear opening shows up. Any sane chess or go player knows that. In this specific case it means increasing institutional flexibility, that is, we should get rid of centralized bureaucratic power structures as much as possible in the unknown time span given, because they are rigid and brittle, hinder <i>any</i> reasonable action effectively. The world system should be rebuilt in a recursively modular fashion, with standard interfaces at module boundaries controlling (and facilitating) traffic according to standard protocols. The foolish practice of removing module boundaries as <i>obstacles</i> should be halted. We have to improve permeability and <i>local</i> control over interfaces at the same time instead. Internal workings of a module is no business of anyone outside, save for its interfaces to other modules. By "traffic" I mean exchange and flow of persons, information, knowledge, expertise, ideas, services, goods, capital, finances, etc. (but never coercion, intimidation or raw power) That's how a <i>free</i> system looks like. It is a system which is durable, can accommodate to anything the future, always shrouded in dense fog, might or might not bring about.

Comment on Climate models at their limit? by David L. Hagen


Comment on Climate models at their limit? by k scott denison

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Yes Dave, at 0.0004 (400 ppm) that means one is adding 0.0512 ounces of black pigment to a gallon of paint. Try it out and let me know how it goes. I find it amazing that my Home Depot can measure out that 0.0512 oz of pigment, don’t you?

Comment on Climate models at their limit? by k scott denison

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ps, does the term “surface area” mean anything to you in conjunction with your analogy. That paint layer is not very thick… seems to me the atmosphere is.

Comment on Climate models at their limit? by MattStat/MatthewRMarler

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I’ll have to let you have the last word on that.

Comment on Climate models at their limit? by Robert

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There is a glaring paradox in climate science that no one has bothered to explain: How come that a rare gas like carbon dioxide (less than 1% of atmosphere) can have such a profound effect on climate when nitrogen (70%), oxygen (20%) and water vapour have no effect? What is the difference between carbon dioxide and say, nitrogen that explains this paradox?

So you’re completely ignorant of basic atmospheric physics. What does that has to do with climate science? They don’t share your ignorance.

If you would like them to teach you, there are many resources online, there are courses at your local community college and books in the library.

Why would you think that your ignorance is a global state of affairs?

Comment on Climate models at their limit? by David L. Hagen

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Adam Adding uncertainties that were not previously included increases the overall uncertainty than previously. e.g., Singer showing that more runs were needed to quantify chaotic variation. Including systematic uncertainty that was previously ignored further increases uncertainty. Doing so improves our understanding and thus is "more accurate". If increasing the number of parameters improves the fit, then that could reduce the overall uncertainty - if the relate to physical causes and are not overfitting. The latter would give the appearance of improvement but give worse results later on. e.g., there are numerous papers indicating that the IPCC GCMs currently have too great a sensitivity to CO2 and too low a sensitivity to clouds, etc. Scientists can only "trust" model after thoroughly "kicking the tires" to find and quantify all the reasons to "distrust" the models - especially when the models are not adequately predicting the current temperature trends. For science ignored by the IPCC, see the <a href="http://www.nipccreport.org/" / rel="nofollow">NIPCC.</a> See <a href="http://rankexploits.com/musings/author/lucia/" / rel="nofollow">Lucia at The Blackboard for quantitative explanation / exploration of the statistics</a> For stats see also <a href="http://wmbriggs.com/" / rel="nofollow">William Briggs.</a> See Don Easterbrook and <a href="http://www.duke.edu/~ns2002/" / rel="nofollow">Nicola Scafetta for simple models</a> that include natural oscillations/cycles that all the IPCC's GCMs have ignored up till now. AR5 promises some improvement!? See Armstrong's <a href="http://www.forecastingprinciples.com/files/standardshort.pdf" rel="nofollow">principles of "scientific forecasting",</a> and <a href="www.forecastingprinciples.com/files/WarmAudit31.pdf" rel="nofollow">Green & Armstrong on Global Warming.</a> Ignoring these principles suggests higher bias or systematic error than otherwise possible. (Contrast medical claims with/without the FDA, or stock broker claims with/without the SEC. Where is the watchdog challenging/correcting the IPCC?) Re the lead story - "Despite the uncertainty, the weight of scientific evidence is enough to tell us what we need to know." Climate science will only be "robust" and "trustworthy" when it thoroughly addresses all of these issues and the FULL range of uncertainty - rather than pressuring politicians to "mitigate" when the underlying predictions are weak to say the least, and then trying to hide that weakness.

Comment on Climate models at their limit? by DocMartyn

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” Jim D
A lot of skeptics are not aware that GCMs can simulate daily and seasonal cycles globally really well already.”

When you use the words ‘really well’, you mean them in the manner of usage amongst climate scientists, and not as used by the general population. Essentially, when a climate scientist uses the term ‘really well’ it translates into the normal usage of ‘really crap’.

http://www.hydrol-earth-syst-sci-discuss.net/9/5515/2012/hessd-9-5515-2012-print.pdf

Comment on Climate models at their limit? by Latimer Alder

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It also says ‘EXCELlent references required to fill a major skills gap in our own portfolio’


Comment on Climate models at their limit? by Latimer Alder

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They’ve signed up to Craven’s ‘Vision of the Apocalypse’?

Really? Did I miss the memo?

Comment on Climate models at their limit? by Chief Hydrologist

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‘AOS models are members of the broader class of deterministic chaotic dynamical systems, which provides several expectations about their properties (Fig. 1). In the context of weather prediction, the generic property of sensitive dependence is well understood (4, 5). For a particular model, small differences in initial state (indistinguishable within the sampling uncertainty for atmospheric measurements) amplify with time at an exponential rate until saturating at a magnitude comparable to the range of intrinsic variability. Model differences are another source of sensitive dependence. Thus, a deterministic weather forecast cannot be accurate after a period of a few weeks, and the time interval for skillful modern forecasts is only somewhat shorter than the estimate for this theoretical limit. In the context of equilibrium climate dynamics, there is another generic property that is also relevant for AOS, namely structural instability (6). Small changes in model formulation, either its equation set or parameter values, induce significant differences in the long-time distribution functions for the dependent variables (i.e., the phase-space attractor). The character of the changes can be either metrical (e.g., different means or variances) or topological (different attractor shapes). Structural instability is the norm for broad classes of chaotic dynamical systems that can be so assessed (e.g., see ref. 7).’ James McWilliams

http://s1114.photobucket.com/albums/k538/Chief_Hydrologist/?action=view&current=sensitivedependence.gif

TT – the usual advice for such as you is that it is better not to speak and be thought an idiot than to speak and remove all doubt.

Comment on No consensus on consensus: Part II by Pekka Pirilä

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Now I don't understand at all, what you mean as I write <i>the same revenue for the government</i> and you refer to <i>bring zero net revenue for the government</i>. Where do you see the difference that I don't see?

Comment on Climate models at their limit? by Chief Hydrologist

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‘In principle, changes in climate on a wide range of timescales can also arise from variations within the climate system due to, for example, interactions between the oceans and the atmosphere; in this document, this is referred to as “internal climate variability”. Such internal variability can occur because the climate is an example of a chaotic system: one that can exhibit complex unpredictable internal variations even in
the absence of the climate forcings discussed in the previous paragraph.’ Royal Society

You are really very tedious and ignorant TT. If you were a serious person and not an AGW space cadet I might want to treat you as a fully functioning human being. As it is there are too many roos loose in your top paddock to take anything you say seriously.

Comment on No consensus on consensus: Part II by Sullivan

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Pekka

With say petrol tax, the government can spend the money on its own activities and programs, eg defence, schools, roads. With a revenue-neutral tax, it doesn’t, it just passes the money back to some citizens.

And in this case (a tax on natural resources), it does so in a way that has the same effect as you would have if the natural resource (carbon in this case) was owned by citizens who charged for its use. And if the idea is to give each citizen an equal share in the natural resource, then each citizen/shareholder would get an equal payout.

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