Why are climate-change models so flawed? Because climate science is so incomplete
There is a popular theory that atmospheric CO2 amplifies the creation of water vapor, thereby increasing warming through a “positive feedback loop.” But that theory so far is mostly speculative; climate projections using models based on it have consistently failed, nearly always predicting far more warming than has occurred. It should go without saying that if scientists cannot yet make accurate predictions about future climate change, then their understanding of climate science remains highly incomplete.
Earth’s climate
system is unfathomably complex. It is affected by innumerable
interacting variables, atmospheric CO2 levels being just one. The more
variables there are in any system or train of events, the lower the
probability of all of them coming to pass. Your odds of correctly
guessing the outcome of a flipped coin are 1 in 2, but your odds of
guessing correctly twice in a row are only 1 in 4 — i.e., ½ x ½
Extending your winning streak to a third guess is even less probable:
just 1 in 8.
Apply that approach to climate change, and it becomes
clear why the best response to the alarmists’ frantic predictions is a
healthy skepticism.
The list of
variables that shape climate includes cloud formation, topography,
altitude, proximity to the equator, plate tectonics, sunspot cycles,
volcanic activity, expansion or contraction of sea ice, conversion of
land to agriculture, deforestation, reforestation, direction of winds,
soil quality, El Niño and La Niña ocean cycles, prevalence of aerosols
(airborne soot, dust, and salt) — and, of course, atmospheric greenhouse
gases, both natural and manmade. A comprehensive list would run to
hundreds, if not thousands, of elements, none of which scientists would
claim to understand with absolute precision.
But
for the sake of argument, say there are merely 15 variables involved in
predicting global climate change, and assume that climatologists have
mastered each one to a near-perfect accuracy of 95 percent. What are the
odds that a climate model built on a system that simple would be
reliable? Less than 50/50. (Multiplying .95 by itself 15 times yields
46.3 percent.) Is it any surprise that climate-change predictions in the
real world — where the complexities are exponentially greater and the
exactitude of knowledge much less — have such a poor track record?
Pruitt
got it right: Measuring human impacts on climate is indeed “very
challenging.” The science is far from settled. That is why calls to
radically reduce carbon emissions are so irresponsible — and why dire
warnings of what will happen if we don’t are little better than reckless
fearmongering.
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