GW Skeptics vs Scientific Concensus

[Brian H]

Breakable wrote:

The point is that the CRU Team etc. aggressively exclude input from those qualified in the various genuine sciences. Their mathematical hand-waving, e.g., uses PR to substitute for acknowledging the impossibility of producing the kinds of projections they claim.

Interesting paper with zero substance. Author(s) claims he has discovered (absolutely true) principles of forecasting which everyone must adhere to, but he does not provide any proof of. Why does he not use those principles to make some money in forex, stock market, horse race or football betting? Or do they only predict where you can not make any predictions?

Much more substance you can find here:
http://en.wikipedia.org/wiki/General_Circulation_Model#Accuracy_of_models_that_predict_global_warming
Wikipedia has been systematically filtered on the subject by William Connolley; it often takes just hours for any information questioning the Warmist orthodoxy to be deleted. Wikipedia is in general very unreliable on any controversial topic. The edit wars are endless.

[Breakable]

Brian H wrote:
Wikipedia has been systematically filtered on the subject by William Connolley; it often takes just hours for any information questioning the Warmist orthodoxy to be deleted. Wikipedia is in general very unreliable on any controversial topic. The edit wars are endless.

I am really interested where do you get your information from?
Original sources are probably the best, but I wonder if anyone has the time to read thousands of papers every day.
I consider myself Wikipedia to be one of the best sources for controversial information. Surely the wiki-wars are going on all the time, but It as long as there is a stakeholder it should be possible to get the truth out. Look – we even got a http://en.wikipedia.org/wiki/Focus_fusion article out!

[vansig]

The text of these principles is available for download/verification at
http://forecastingprinciples.com/index.php?option=com_content&task=view&id=7&Itemid=7

i see the content .doc files on the submenus..
Bootstrapping, Selecting, Combining, Evaluating, Expert, Extrapolation, Rule-based, Standards, Role-playing.

[Phil’s Dad]

Breakable wrote: Regarding the precautionary principle…

You’ve gone off at a rather odd tangent here since corporations will not be the decision makers in this matter.
Still, since you bring us here, ignorance is not the alternative to the precautionary principle but the root cause of it.

[Breakable]

Phil’s Dad wrote:
You’ve gone off at a rather odd tangent here since corporations will not be the decision makers in this matter.
Still, since you bring us here, ignorance is not the alternative to the precautionary principle but the root cause of it.

Ignorance is thinking that something less than precautionary principle can protect the public. Does you experience suggests that lobbying and corruption cannot tilt any decision towards business interests where there is no clear cut boundary? Lets imagine a softening of Precautionary principle : “precautionary approach”. So now government can decide if economic costs are larger than public benefit. Basically inflating economic costs (which cannot be verified), can prevent any action.

[Breakable]

vansig wrote: The text of these principles is available for download/verification at
http://forecastingprinciples.com/index.php?option=com_content&task=view&id=7&Itemid=7

i see the content .doc files on the submenus..
Bootstrapping, Selecting, Combining, Evaluating, Expert, Extrapolation, Rule-based, Standards, Role-playing.

The resulting evidence-based principles can be applied in fields such as economics, 

	sociology, and 

	psychology. It applies to problems such as those in finance (How much is this company worth?), 

	marketing (Will a new product be successful?), 

	personnel (How can we identify the best job candidates?), and 

	production (What level of inventories should be kept?).

Interestingly not a single hard-science field, probably those principles are not so reliable eh?

[Brian H]

Breakable wrote:

You’ve gone off at a rather odd tangent here since corporations will not be the decision makers in this matter.
Still, since you bring us here, ignorance is not the alternative to the precautionary principle but the root cause of it.

Ignorance is thinking that something less than precautionary principle can protect the public. Does you experience suggests that lobbying and corruption cannot tilt any decision towards business interests where there is no clear cut boundary? Lets imagine a softening of Precautionary principle : “precautionary approach”. So now government can decide if economic costs are larger than public benefit. Basically inflating economic costs (which cannot be verified), can prevent any action.

Buried in the fine print of the Warmist IPCC reports is the acknowledgement that the “models” are actually “scenarios”, meant to illustrate what would happen if a particular set of unverified and untestable guesses were true. As physics professors Gerlich and Tscheushner point out, this amounts to video gaming, and has nil scientific value. Chicken Little crying, “The sky might be falling, and if it does it would be horrible, so give me all your money so I can build shelters for you!” That’s the precautionary principle. Nonsense from start to finish.

[Breakable]

Brian H wrote: Buried in the fine print of the Warmist IPCC reports is the acknowledgement that the “models” are actually “scenarios”, meant to illustrate what would happen if a particular set of unverified and untestable guesses were true. As physics professors Gerlich and Tscheushner point out, this amounts to video gaming, and has nil scientific value. Chicken Little crying, “The sky might be falling, and if it does it would be horrible, so give me all your money so I can build shelters for you!” That’s the precautionary principle. Nonsense from start to finish.

Would it surprise you to hear that some of those “scenarios” that were modeled in eighties and nineties are playing out quote well? As well as a weekly prediction of weather. So probably those unverified and untestable guesses are true in those particular scenarios and if nothing is changed those scenarios will likely remain true.
But I guess you would not be interested. So I guess I will shut the **** up, and you can placate your “coal is good” all over the forums again.

[Brian H]

Breakable wrote:
Would it surprise you to hear that some of those “scenarios” that were modeled in eighties and nineties are playing out quote well? As well as a weekly prediction of weather. So probably those unverified and untestable guesses are true in those particular scenarios and if nothing is changed those scenarios will likely remain true.
But I guess you would not be interested. So I guess I will shut the **** up, and you can placate your “coal is good” all over the forums again.

Retro-casting is useful for generating speculations and eventually hypotheses. Actual predictions require full disclosure of model variables and algorithms, plus input data set, which are then frozen (no touch, no fiddle) for the duration of the prediction. A reasonable fit fails to disprove the forecast model; a failure invalidates it completely (since the specific reason can only be guessed at — for which you need a brand new square one re-prediction and test.) Enough failures to disprove, despite best (honest) efforts, and you MAY begin to put some reliance on the model.

None of the Warmist scenario-games meet any of those criteria.

[vansig]

Breakable wrote:
Interestingly not a single hard-science field, probably those principles are not so reliable eh?

Sorry, that statement is absurd if you can select “hard-science” to mean anything “easy to predict”. Do not dismiss whole fields and attempt to use that dismissal as ‘evidence’ that a methodology may be unreliable. Instead, test the power of the method against its competitors on those hard-to-predict problems.

[vansig]

Brian H wrote:
Retro-casting is useful for generating speculations and eventually hypotheses. Actual predictions require full disclosure of model variables and algorithms, plus input data set, which are then frozen (no touch, no fiddle) for the duration of the prediction. A reasonable fit fails to disprove the forecast model; a failure invalidates it completely (since the specific reason can only be guessed at — for which you need a brand new square one re-prediction and test.) Enough failures to disprove, despite best (honest) efforts, and you MAY begin to put some reliance on the model.

None of the Warmist scenario-games meet any of those criteria.

Stunt FOIA requests do not really expose a lack of full disclosure.

Let’s lock in Hansen’s predictions made in 1988. There were three scenarios, A, B, and C.
Observations are now out of agreement with A; but B and C are still good.
— http://www.logicalscience.com/skeptic_arguments/models-dont-work.html

[Breakable]

vansig wrote:

Interestingly not a single hard-science field, probably those principles are not so reliable eh?

Sorry, that statement is absurd if you can select “hard-science” to mean anything “easy to predict”. Do not dismiss whole fields and attempt to use that dismissal as ‘evidence’ that a methodology may be unreliable. Instead, test the power of the method against its competitors on those hard-to-predict problems.

It is possible that their methodology works on the “hard-to-predict – impossible to verify” problems, but not on the “easy to predict – easy to verify” problems?
If we don’t know it does, so why use it? How do do you verify a problem in a field such as “economics, sociology, and psychology”. Probably the best performance indicators come from economics, but they can be totally changed by by market which you have no control of. I am not aware of a single experiment that can measure prediction performance in a market in an unbiased, reliable, controllable and quantifiable fashion at least for the moment.
What about a well controlled verification – why cant I calculate planet earth motion guided by gravity using Newtonian theory (even without relativity) and see how much of the “Principles of forecasting” it violates? If they claim the principles are valid in predicting GW, that means they should be valid in any other physical calculation as GW models are physical in nature and do not try to predict human behavior for now.
But they are actually avoiding those claims – all the fields they are including are not “easy-to-verify” and I don’t see either “Climatology” nor “Physics” in their list of predictable fields. The only reason they even talk about GW, I would think is because they believe its not settled yet – so free publicity (specially for gullible people). My thinking is that they don’t actually want to mess with well-defined-hard-science, because they would quickly be disproved – same as any quack medicine that tries to claim real health benefits would be quickly axed by FDA. I really don’t have the time, but maybe anyone cares to run “CARL SAGAN’S BALONEY DETECTION KIT”
http://users.tpg.com.au/users/tps-seti/baloney.html on them?

[vansig]

Okay, Here’s an economic prediction that should be verifiable.
“Increased demand for oil results in upward pressure on the Canadian dollar.”

Let’s apply the method to hard-to-predict, easy-to-verify problems. Can you name a few?

[Breakable]

vansig wrote: Okay, Here’s an economic prediction that should be verifiable.
“Increased demand for oil results in upward pressure on the Canadian dollar.”
Let’s apply the method to hard-to-predict, easy-to-verify problems. Can you name a few?

How do you define pressure in a way you can verify it later and specifically with a marked doing whatever it wants at that moment. Economy is booming, busting or stagnating for other reasons not related to oil. Imagine you make you prediction that economy will boom and next day FF comes along.

vansig wrote:
Let’s apply the method to hard-to-predict, easy-to-verify problems. Can you name a few?

I guess if you could predict a price change in currency pair on Forex with a high accuracy, there was no need to write any books.

[vansig]

In a different thread, there is a raging debate about CO2, and whether it has an effect or no, and whether there is transparency or secrets kept, in the field of climatology. that debate is slightly more appropriately placed here.

So,
Given a spinning sphere, period=24h, radius=6371km, albedo=0.367, at 1AU from the Sun, atmosphere scale height=7 km, and known concentrations of various gases, it should be possible to calculate the contribution of each one on temperature from their absorption spectra. This is an incomplete model, certainly, but regardless of validity we should be able to learn something from it.

So: what then, does it say, about the effect of GHG concentrations, eg CO2 between 200 – 1000 ppm, upon average global temperatures?

http://www.te-software.co.nz/blog/auer_files/image001.gif

Surely the transparency exists in the research to make it possible for any ordinary person, like me, to run this?
Surely I dont need to join some club, and make an oath of silence?
Surely I can publish, even self-publish, all the results and the code for verification, if i write it myself?

[Author]

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