26 October 2015

Linear Thinkers

One of the themes on blog of late, particularly in the past two posts, is that global warming apologists aren't very good at approaching science holistically.  Obviously, this is very problematic for people who wish to study global warming because analyzing a matter on a global scale will obviously require massive amounts of data and balancing a very wide array of variables.  Clearly, most climate scientists and apologists are not doing this at all.

In fact, the shrillest doomsday predictors often seem focused on variable to the near exclusion of all others.  Those who are concerned about CO2's effect on the atmosphere seem downright ignorant of its effect on plant life.  Those concerned about melting ice caps seem almost uninterested in oceanic water evaporation.  The irony is that in each case, the presumed negative effect is, to some degree, offset by the positive effect and--most importantly--inseparable.

I suppose that the biggest issue with the global warming screamers is that, while they are certainly more clever than average, they are very much linear thinkers.  In fact, I would suggest that they are probably be the smartest linear thinkers.

Unfortunately, climatology is not a branch of science that is well-suited for linear logic.  Isolating a variable and extrapolating its effects is an extremely stupid thing to do in climatology because a) every variable has multiple effects and b) no variable is truly independent in reality.  More CO2 may lead to a greater greenhouse effect, to be sure.  The point of a greenhouse, though, has always been to leverage a warmer, more humid environment into increased plant growth and yields.  Thus, an increased greenhouse effect would likely have a positive effect on crop yields and subsequently ameliorate global poverty.

Thus, applying the tool of linear logic to an isolated variable is akin to digging a hole with a shovel.  The tool simply isn't meant for the job.  So, while the global warming crowd may be quite clever at using their analytic method, when's all is said and done they are not really clever enough to realize that they are using the wrong tool for the job.  So really, they aren't even that clever.

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