Change-over to enewable energy

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It predicted their paychecks all these years, which is good enough for government work.

-- Cheers, James Arthur

Yes, it is.

Your own linked expert said the opposite.

During the recent storms (Irene and Lee), I was amused to note that the whethermen[sic]'s rainfall and energy predictions were off by factors of 2-5. That is, current methods can't accurately /measure/ the moisture or energy content of clouds, or predict macroscopic behavior--even when right under their noses, much less predict formation, reflectance, opacity, etc.

I try to trim the trolling, and stick with the interesting, substantive parts exploring the merits of the various AGW arguments. Plus a little bit of fun, of course. YMMV

-- Cheers, James Arthur

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Not in this context. Climate modelling involves getting the broad features roughly right. As John von Neumann pointed out a long time ago, climate modelling is different from weather modelling. Since it doesn't aim for cell-by-cell veracity it is consequently immune from the butterfly effect.

Some of the range of models tested didn't predict the right amount of cloud, most did. How is this "the opposite" of what I said?

That's the distinction between weather modelling and climate modelling, which seems to have been obvious enough to John von Neumann.

discusses the point in a lot more detail and depth.

Climate modelling isn't aimed at getting precise prediction of specific weather patterns on a moment-to-moment basis. It's aimed at getting the right averages over months and years, which turns out to be a more tractable problem.

But you idea of "interesting" doesn't stretch far enough to capture the difference between weather models and climate models. John Larkin has the same problem, and can't be persuaded that the fact that weather is chaotic - as are the orbits of the planets - isn't evidence that you can't you make useful long-term predictions, and your text- chopping is decidedly selective.

-- Bill Sloman, Nijmegen

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Ignorance may not be bliss, but it does provide the basis for some remarkably silly snide comments. Presumably when James Arthur was first let lose with non-linear multi-parameter curve-fitting program, he tried to fit more parameters at once than the data could define - it's the sort of mistake the naive have been known to make if they don't read their text-books. He's got to have a totally unrealistic idea of academic research standards to think that kind of obvious idiocy could be parlayed into a research career.

My own multi-parameter curve-fitting program exploited the fitting process to generate confidence limits on the parameters being fitted - mildly optimistic confidence limits, as it turned out, because the citical part of the noise spectrum turned out to be 1/f noise rather pure random noise - but it did make it obvious when I was trying to extract more information than the data could support.

-- Bill Sloman, Nijmnegen

o "Right amount"?

"...one of my runs ended up with no clouds, other people had all the water precipitate as ice at the poles, etc.)."

Yep, they've got it nailed all right.

o Models were gauged by hindsight, not successful predictions. o "...most did"? Where'd you find that?

He said they try a bunch of crappy parameters, then cherry-pick the results they like. That gives them a model, but doesn't guarantee any correspondence with physical reality.

Clouds and other factors are poorly understood, and the modeler's only way around is fiddling, then trying.

"Once you get a set of parameters that gives a fair approximation to the known past climate, you can double the carbon dioxide in the atmosphere and run it again."

That's adaptive curve-fitting. It doesn't prove causation.

You claimed they predict clouds. Your source says he can't, and I showed they can't even measure them, much less predict.

-- Cheers, James Arthur

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In the bit of the quote that you first posted, then snipped when you reposted it above.

If the model behaves like physical reality - which is what they were looking for - that's a useful correspondence.

They are pretty well understood, but a physically realistic model is not only computationally impractical but also unstable - the butterfly effect - and what's needed is a simpler model that captures the crucial behaviour.

Causation depends on other evidence and other logic. We know - without a shadow of doubt - that more greenhouse gas means that the surface of the earth is warmer. The tricky bit is working out how much warmer. The ice core data and the ocean sediment data tells us a fair bit about how much cooler with less CO2 in the atmosphere, but we haven't had warmer for some 20 million years and the evidence from back then isn't as good.

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They predict clouds - in the sense of areas of the atmosphere that are loaded with small water droplets or ice crystals - as a function of gross geography. For climate modelling they don't have to predict exactly where or exactly when.

Having weather radar that could dissect the fine structure of a thunderstorm is useful - for weather modellers - and some researchers have that kind of gear to play with. It's a bit too fine-grained to be useful to climate modellers at the moment.

IEEE Spectrum had a article on a "computer for the clouds"

which addressed to problem of running a model that was fine-grained enough - 1 km per side cells - to cope with individual clouds rather than treating "some cloud" as a property of a cell that is 100km by

-- Bill Sloman, Nijmegen

It is sad that you do not expect conclusions to be objective.

Dan

I am not political at all. I want a happy, peaceful, prosperous world. Leftist politics doesn't produce that.

I told you, here, years ago, that Europe was working on making a demographic and economic crisis, and you didn't believe me. It's just happening faster than I thought it would.

Liberal lefists, the coastal latte-drinking NYT-reading types, are the ones who think the average citizen is an idiot. Read the Times or the SF Chronicle for lots of examples. I think the US population, especially the common folk who live in flyover territory, have a pretty good longterm collective wisdom, and they are worried about having too much government. They are right.

John

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Then you mistook what he said.

He said they ran a spread of models with various parameters, then selected the model runs that correlated with PAST data. Producing correlation with past events was the parameter-selection criterion.

That's adaptive curve-fitting.

They did not make predictions, then compare those to subsequent events.

It's still curve-fitting until they successfully predict things before they happen. Everything else is retrospective.

Which is a critical weakness of today's models. Critical.

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We don't need to go into the depth and detail. Your expert has already restated what I deduced years ago: so far, clouds (and other factors) defy analysis. Currently, instead, they're approximated by twiddling coefficients, then cut-and-try.

The exact location--and possibly timing--is of course extremely critical, since the effects and insolation are dramatically different at different latitudes.

-- Cheers, James Arthur

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In fact adaptive curve fitting involves adjusting the value of a particular set of parameters to fit a particular set of data (which can be quite large).

The spread of models with various parameters are a variety of different models, rather than a single model being adjusted to fit historical data.

You've failed to understand what's going on, and on the basis of your imperfect understanding have written off a large chunk of academic research on the basis that it's something simpler - and totally idnadequate - which you do think you understand. It's distinctly comical.

The usual technique to to split up the test data, and fit the model - or models - to some of the data, then test the fit between the models and the rest of the data. This is elementary stuff, but you don't seem to know about it.

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Not if you do it right - and you clearly haven;t any idea how one would do it right.

Every other physical model that we work with is an over-simplified version of reality, which doesn't make the models useless. One does have to understand their limitations, but the absence of computationally simple and theoretically rigorous model for clouds isn't - in fact - a critical weakness, any more than the absence of a computationally simple and theoretically rigorous model for integrated circuits isn't a critical weakness of Spice.

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The twiddling goes rather deeper than just adjusting coefficients, and clouds don't "defy analysis". They defy the kind of detailed analysis that you'd like - it's not impossible but it is totally impractical in the anthropogenci global warming context. They don't defy analysis based on intelligent simplication - which is what the Princeton paper appears to be talking about, but you lack the background to appreciate this approach.

That's gross geography and that's exactly the kind of crude stuff they can - and do - model.

-- Bill Sloman, Nijmegen

It's a good deal sadder that you can't realise quite how stupid this observation is.

-- Bill Sloman, Nijmegen

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Dream on.

And rightist politics would? The invasion of Irak made the world more peaceful and prosperous?

The demographic crisis was that Muslim immigrants were going to outbreed the local population - which might happen if the next three generations shared their parents ideas about optimum family sizes. No other immigrant group has behaved that way, but you found it necessary to warn us that you though that Muslims were different from - say - Jews or Protestants.

You'll need to remind me why you were predicting an economic crisis for Europe. The bursting of the US property market bubble and the sub- prime mortgage business that blew it up in the first place rather devalued American opinions on other peoples' economic crises.

Not so much right, as little too far to the right. The American media has been lying about socialism for more than a century now - to the point where most Americans think that socialism and communism are interchangable - and it seems that you can fool enough of the people enough of the time.

The average citizen isn't an idiot - any more than you are - but can be misinformed - as you all too frequently are - if right-wing interests control enough of the newspapers and the television stations.

-- Bill Sloman, Nijmegen

You keep thinking Left and Right, like they were sports teams.

The invasion of Irak made the world more

We don't know yet. If the Arab Spring goes right, yes.

I didn't say that. I said that low birth rates and high "social" benefits were a time bomb. The Greeks turned out to have the shortest fuse.

No

No.

John

And the same about you.

Dan

I really enjoy reading your posts. It is interesting to see how wrong your view of the U.S. media is. For instance you believe right wing interests control much of the newspapers and television stations.

Dan

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You're lost in the details. If the model doesn't accurately reflect the physical system, tweaking a bunch of unrelated coefficients doesn't rehabilitate it. You can artificially make it reproduce arbitrary historical data, and pretend you've modeled reality, while conferring zero actual power of prediction.

The same methodology, applied, could extract the pertinent parameters w.r.t. to fires, fire intensity, and historical data regarding red trucks. A model would quickly emerge showing strong correlation, with coefficients capable of roughly predicting the size of the fire based on the number and size of the trucks, plus other data.

But, model or no, it's wrong--red trucks don't cause fires.

-- Cheers, James Arthur

Hi,

Solar panel prices are extremely low right now due to oversupply and lower demand, $1.34/watt at this website:

cheers, Jamie

And how much of that cost is covered by money extracted from the working stiffs in the form of taxes for subsidies?

Thanks, Rich

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You don't understand the details. No model accurately represents a phyiscal system - they are all more or less useful simplications.

That is the sort of mistake a beginner can make, if they don't undestand what they are doing. The art lies in getting a useful approximation to reality.

I imagine it could. Nobody in their right mind would take it seriously, or waste time concoting such a model, but it does make a comical straw man.

Perfectly correct, and perfectly irrelevant.

As I said, you are effectively claiming that a large chunk of academic research can be written off on the basis that you think that they are making the kind of mistake that you presumably made when you were a wet-behind-the-ears newby in modelling business.

It's definitely comical, and entirely pathetic.

-- Bill Sloman, Nijmegen