Those enamored of global warming - who have spent some $50 bn of our tax monies world-wide to try to prove that it is indeed happening - have some explaining to do.
This is the problem.
But it doesn't stop there.
The link above connects to an article written by someone who spent 6 years working on Carbon Accounting, working out the detailed effects of the carbon chain backwards and forwards.
According to him - and you can't discount the man, he did the work - he started out on the precautionary principle, i.e. the evidence was enough for him to start working on identifying the effects.
His problem today?
Simple.
Very simple.
There are no effects.
No hot spot in the troposphere at 10km height. If CO2 were heating things up, that is where it would appear. There is zilch, none, nada: if there is no effect, there is no cause.
Models are that: models. They are what the modeler makes them: an honest modeler does the hard work: the statistical analysis of empirical data; the correlations that lead to causality tests; the reproduction of historical effects from the empirically derived causal relationships; the approximate construction of causal effects for the future; the back-testing; the testing with pseudo-noise to eliminate model bias. This is hard and at many times very, very tedious work.
There are the modelers who know their field so well and who work with inherently poor data to construct models that make the best out of a bad thing, models which can be extremely accurate, but are based on expert knowledge, rather than purely on empirical evidence.
Then the are the dishonest modelers, who construct models to prove a point. If you put deterministic equations into your models, you will always get the results you want. If you are really determined to get the results you have decided on, construct the model such that it makes no difference what data is put in: you end up with Mann's Hockey Stick model, which at this point should serve as the prime example of what not to do (in his model, you got very similar results simply by feeding in pink or white noise: the model always gave you similar results).
The global warming alarmists want to spend, literally, hundreds of billions of dollars and want to force radical changes in human behavior.
But it doesn't stop there.
What if you were to approach those who are making the claims of global disaster and ask to see their work? What if the answer was "Why should I make the data available to you, when your aim is to try and find something wrong with it?"
I'd call for that person to be stripped of their title as scientist. Hasn't happened, of course: he is too well protected, politically, for him to suffer any consequences.
Think that this doesn't happen? See this here. You have to scroll down a bit to see that quote.
It makes no difference if someone has worked 25 or 125 years on the subject: the scientific method is one of testing hypotheses to find if they work: scientists should aim to try and find something wrong with the work.
Unless, of course, "science" here is meant to be dogma. Dogma can't be challenged: it is a belief.
The Hockey Stick is dead, dead, dead, and anyone who worked on that should be drummed out of the academic world. They used methods that led to fundamentally the same results - within a 99% confidence realm - when fed with random numbers.
I guess I'm flogging a dead horse. There is significant evidence that the "science" of global warming is nothing less than a fraud, despite billions having been spent: if anything, spending that money has created a Global Warming Industry that claims consensus by ignoring scientific methods and by condoning outright fraud: if the same group of "scientists" peer-review each others' papers in the journals that they themselves run, how can dissent make its voice heard if ears are plugged?
And this is the basis on which governments, in massively misplaced trust, plan to spend hundreds of billions of your dollars.
This is the problem.
But it doesn't stop there.
The link above connects to an article written by someone who spent 6 years working on Carbon Accounting, working out the detailed effects of the carbon chain backwards and forwards.
According to him - and you can't discount the man, he did the work - he started out on the precautionary principle, i.e. the evidence was enough for him to start working on identifying the effects.
His problem today?
Simple.
Very simple.
There are no effects.
No hot spot in the troposphere at 10km height. If CO2 were heating things up, that is where it would appear. There is zilch, none, nada: if there is no effect, there is no cause.
Models are that: models. They are what the modeler makes them: an honest modeler does the hard work: the statistical analysis of empirical data; the correlations that lead to causality tests; the reproduction of historical effects from the empirically derived causal relationships; the approximate construction of causal effects for the future; the back-testing; the testing with pseudo-noise to eliminate model bias. This is hard and at many times very, very tedious work.
There are the modelers who know their field so well and who work with inherently poor data to construct models that make the best out of a bad thing, models which can be extremely accurate, but are based on expert knowledge, rather than purely on empirical evidence.
Then the are the dishonest modelers, who construct models to prove a point. If you put deterministic equations into your models, you will always get the results you want. If you are really determined to get the results you have decided on, construct the model such that it makes no difference what data is put in: you end up with Mann's Hockey Stick model, which at this point should serve as the prime example of what not to do (in his model, you got very similar results simply by feeding in pink or white noise: the model always gave you similar results).
The global warming alarmists want to spend, literally, hundreds of billions of dollars and want to force radical changes in human behavior.
But it doesn't stop there.
What if you were to approach those who are making the claims of global disaster and ask to see their work? What if the answer was "Why should I make the data available to you, when your aim is to try and find something wrong with it?"
I'd call for that person to be stripped of their title as scientist. Hasn't happened, of course: he is too well protected, politically, for him to suffer any consequences.
Think that this doesn't happen? See this here. You have to scroll down a bit to see that quote.
It makes no difference if someone has worked 25 or 125 years on the subject: the scientific method is one of testing hypotheses to find if they work: scientists should aim to try and find something wrong with the work.
Unless, of course, "science" here is meant to be dogma. Dogma can't be challenged: it is a belief.
The Hockey Stick is dead, dead, dead, and anyone who worked on that should be drummed out of the academic world. They used methods that led to fundamentally the same results - within a 99% confidence realm - when fed with random numbers.
I guess I'm flogging a dead horse. There is significant evidence that the "science" of global warming is nothing less than a fraud, despite billions having been spent: if anything, spending that money has created a Global Warming Industry that claims consensus by ignoring scientific methods and by condoning outright fraud: if the same group of "scientists" peer-review each others' papers in the journals that they themselves run, how can dissent make its voice heard if ears are plugged?
And this is the basis on which governments, in massively misplaced trust, plan to spend hundreds of billions of your dollars.
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