Paul Greenberg offers some reflections on how a science community copes with discordant data … or doesn’t
|October 4, 2011||Posted by News under Science, Culture, Climate change, News|
Could happen to anyone really. CERN, whose Large Hadron Collider failed to produce the Higgs boson (the “God” particle) socked scientists another good one recently when
… CERN’s researchers have found that nearly half of the global warming observed of late isn’t traceable to man’s activities after all but to sunspots, specifically the fluctuations in solar cosmic rays that promote cloud formation …
In a world where we knew human-caused global warming must be true because kiddies read about it on their cereal boxes and desk blotters … So how did people cope?
The ranks of Global Warming’s true believers closed almost as soon as CERN’s latest findings got out. The sheer number of scientists, UN bureaucrats and politicians-speaking-as-scientists (see Gore, Al) is often cited as proof of man-made climate change. As if scientific truth were determined by majority vote. And climate change has won by a landslide!
Recommended reading: “The Truth About Greenhouse Gases” by William Happer, Cyrus Fogg Professor of Physics at Princeton, that nest of subversives, in the June/July issue of First Things. He compared the worldwide enthusiasm for this oh-so-scientific theory with the crazes chronicled by Charles Mackay in his classic “Extraordinary Popular Delusions and the Madness of Crowds.”
To quote from the second edition of that work in 1852: “Men, it has been said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, one by one.” And one by one, our scientists seem to be recovering. – “When Science Isn’t,” Townhall , October 3, 2011
From happer, worth the read,
Theory explains observations and makes predictions about what will be observed in the future. Observations anchor our understanding and weed out the theories that don’t work. This has been the scientific method for more than three hundred years. Recently, the advent of the computer has made possible another branch of inquiry: computer simulation models. Properly used, computer models can enhance and speed up scientific progress. But they are not meant to replace theory and observation and to serve as an authority of their own. We know they fail in economics. All of the proposed controls that would have such a significant impact on the world’s economic future are based on computer models that are so complex and chaotic that many runs are needed before we can get an “average” answer. Yet the models have failed the simple scientific test of prediction. We don’t even have a theory for how accurate the models should be.
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