A Multifarious Dichotomy (but I'll guide you along)

My interests are all over the place and I'll explore them as I go along. As of now there's no reason for anyone else to care about this blog, but it's my responsibility to generate interest and build a following. I'm no salesman, so this might be difficult, but it WILL be honest.

Wednesday, November 25, 2009

I knew we'd live to see the day

I've said many times in the last several years that people of my generation (I'm 35) would live to see the day when "anthropogenic global warming" (AGW) would be exposed as a scam. But I really didn't think it would be so soon. The new "Climategate" development shows that there is little pure science involved in thinks such as the IPCC reports and other global warming models. Especially when grant money and the mere existence of climate studies departments (and your job) hinge upon the persuasiveness of the data, there is a great deal of pressure to get the anticipated results. But that simply exemplifies the problems inherent in the blurring of science, politics, and religious fervor (on the part of AGW's "True Believers")

Let me explain one thing: I have zero intellectual respect for most climatologists, meteorologists, ecologists and environmental scientists. My undergraduate degree is a BS in physics, and I have known, taken classes with and spent leisure time with (read: drank with) these students of the "soft sciences." And I must say that few of these people are what you could call mental heavyweights. If you could buy them for how smart they are and sell them for how smart they think they are, you'd make double and triple digit profits almost every time. so it comes as no surprise that they have cooked the books and fudged the numbers.

Now, there will be long cycles of damage control that may have some effect to blunt the blow to the AGW movement, but I have more confidence than ever that the debate isn't over after all, and perhaps true science may yet be performed on climate issues. All I ask for is that we ask honest questions (not leading or "gotcha" ones), that we acknowledge the limitations of out measurements and modeling methods, and that we go where they evidence leads us, not the other way 'round.

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