From American Thinker, Anthropogenic Global Warming and the Scientific Method by Betsy Gorisch

excerpts:

Science is about ruling things out. Any good scientific hypothesis will make predictions about the natural world — ideally, it will predict at least one natural effect whose existence cannot be caused by anything other than the hypothesis being tested. Observations are then made to acquire evidence, and the evidence is evaluated against the hypothesis’s predictions. Evidence can either rule the hypothesis out or not; if the evidence differs from the hypothesis’s predicted effects, then the hypothesis is wrong and is considered to be ruled out, or falsified. That which has not been ruled out by evidence remains possible. If enough confirmatory evidence is accumulated, the hypothesis is elevated to the status of a theory. Scientific Method is, conceptually, no more complicated than that.

Karl Popper, the great philosopher of science, used a simple observational experiment to illustrate the scientific method’s requirement of falsifiability — the requirement that a hypothesis be stated in such a way as to allow its testing against evidence with a view towards ruling it out. He noted that most people had once assumed that all swans are white. This assumption was based on the observation, over time, of uncounted numbers of white swans — and each such observation was taken as evidence supporting the assumption. However, there came a time when a black swan was found in Australia, and its discovery served to disprove the assumption that all swans are white. In generalizing from this discovery, Popper understood that you would not test the hypothesis that all swans are white by undertaking a search for white swans — because no matter how many white swans you found, you would neither have proven, nor even properly tested, the hypothesis. Instead, you must mount an intensive search for a single non-white swan. If you found even one of those, you would have ruled the hypothesis out. Alternatively, and without finding a non-white swan, it remained viable — but because there remained the possibility of a single undetected non-white swan, it could not be regarded as proven.

The AGW hypothesis that so many people claim accounts for what is essentially pretend global warming has never been treated this way. Initially, its proponents engaged in a search for supporting evidence: Elevated average annual temperatures, local glacial retreats, elevated-temperature indicators in proxy systems such as tree-ring records, measurable coincident increases in atmospheric CO2 concentration, and so on — a search for white swans. But these efforts ignored, and failed even to seek, either any alternative explanations or evidence that would have ruled the hypothesis out. AGW has failed the predictions test again and again; any true scientific hypothesis with so poor an evidence-based evaluation record would have been scrapped by now. Instead, its proponents elevated it to the status of a theory and, ignoring the fact that climate changes continually, renamed it “climate change.”

Models are essentially used as predictive tools, so they are only as good as the information upon which they are constructed. If there are any unknown components in the modeled system, then the model’s predictions will, almost by definition, be unreliable. In the case of a system both as complex and incompletely understood as Earth’s atmosphere, the model’s construction will essentially be required to include untested, incomplete, and/or unproven function assumptions and data. In such a case, the problems and pitfalls of using these models to construct governing policies quickly become self-evident: People trying to rely on the models essentially cannot know what they are doing. When, for example, their model does not predict their real-world observations, they tweak it until it does — which introduces errors-by-expectation into both output and the policies based upon it. These errors increase in magnitude, and therefore in effect, in a non-linear fashion directly proportional both to the size of the system and to the modeled outputs.

AGW’s predictions are not being reliably confirmed by observations. When stasis and/or cooling occur rather than warming — as has been the case over the last decade-and-a-half — atmospheric scientists fudge interpretations by saying that if it is cool, well, that is just weather; if it is warm, though, that is climate. Alternatively, they claim AGW predicts the cooling — as, for example, with the recent polar-vortex outbreaks. However, a theory that predicts everything predicts nothing — because a theory that predicts everything cannot be falsified through testing; nothing will serve to rule it out.

Read more: http://www.americanthinker.com/articles/2014/11/anthropogenic_global_warming_and_the_scientific_method.html#ixzz3K5Y6CxXN
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