"What is required is the wholesale adoption of the standards applied in the pharmaceutical industry drug trials: double blind trials (aka peer reviewing)"
I think the gentleman who authored this article neglected to look up the terms in question.
Rofl. I gave up on the article after the first paragraph, so I missed that nugget.
Did he explain how you conduct a double blind trial on climate change? That's like asking me (an astrophysicist) to conduct a double blind trial on the Big Bang.
It's not possible to do trials on some systems, either because there is only one or because it's impossible to manipulate it. In those cases, you are unfortunately stuck with collecting data and building (physically reasonable) models where you try to match those data and suggest new data which are predicted by the theory that can be used for testing it.
It is important to do the latter. Just because you can adjust a bunch of parameters in the model to match existing data doesn't give a lot of confidence in your model, because of the feedback loop that causes you to work on the model until it fits the data. What you need to do is then say "given this model, we predict x" and then go and look for x.
From what I know about the climate modeling, it would be nice to see more of the latter. I know there are some things (development of regional patterns of changes) that match the models, but I don't know whether those were pre- or post-dictions.
Did he explain how you conduct a double blind trial on climate change? That's like asking me (an astrophysicist) to conduct a double blind trial on the Big Bang.
It's not possible to do trials on some systems, either because there is only one or because it's impossible to manipulate it. In those cases, you are unfortunately stuck with collecting data and building (physically reasonable) models where you try to match those data and suggest new data which are predicted by the theory that can be used for testing it.
It is important to do the latter. Just because you can adjust a bunch of parameters in the model to match existing data doesn't give a lot of confidence in your model, because of the feedback loop that causes you to work on the model until it fits the data. What you need to do is then say "given this model, we predict x" and then go and look for x.
From what I know about the climate modeling, it would be nice to see more of the latter. I know there are some things (development of regional patterns of changes) that match the models, but I don't know whether those were pre- or post-dictions.