G'day DA,
I do admire your passion in the face of vehement opposition and the almost complete lack of facts to back up your statements. But since when do you need facts when your position seems to be: ?When all else fails in an argument, insult those who do not agree with you?
I find amazing you use a quote that really is particularly good to argue the opposite to the quote. Actually I?d like anyone arguing about Global Warming to read the House of Lords report
web page . This is one presentation heavy on facts and light on supposition. Instead of finding fault with one comment which really does have a great deal of support including by scientists that fully support Global Warming (again I refer you to your one reference ? the Goddard Institute ? for comments in respect to the accuracy of data) how?s about countering the main argument or the data presented in the paper.
Since when is a comment obviously wrong because the levies in New Orleans failed and some people stuck their head in the sand and said they were going to be all right ? which might have had something to do with the US disaster organisation being subsumed by Homeland Security and the very big risk of natural disasters and the budgets that go with it being shredded in order to fund the much smaller per capita risk of terrorist attacks.
Oh, and by the way there was considerable concern, including from the Army Corp of Engineers concerning the New Orleans levies for a long time before Katrina. I remember even seeing a news piece on CNN when Katrina was only just starting out that voiced concern that the extensive levy system in New Orleans would probably not take a direct hit by a hurricane.
A better analogy would have been in the issue that the concerns over the levies were ignored despite the fact that there was good evidence to support the concerns. But it is still a lousy analogy just the same.
And because it is so good I think the original quote is worth repeating:
"For the last 30 years, our data sets are so contaminated by personal interpretations and personal choices that it is almost impossible to sort up the mess in reliable and unreliable data." Richard
