Kenneth P. Green
Much of our understanding of anthropogenic climate change, and much of the debate over climate science and climate policy is based on information generated via mathematical modeling. Rarely, if ever, do we see much discussion of empirical measurements of climate change; global average temperature and sea level are rare exceptions.
… At the same time, many of the input assumptions that are used to shape, or parameterize, such models are simply speculation about the future put to numbers. Modellers create scenarios and story-lines of future societal development, estimate greenhouse-gas emissions from those scenarios and story-lines, and plug those values into mathematical climate models that predict future warming, and the harms of that warming.
For those who believe that public policy—the enactment of rules and regulations that are, by their nature, coercive tools of governance—should be based on evidence of a calibre one might demand in a court of law to determine guilt or innocence of a crime, the almost complete reliance on model outputs is problematic. This is so because model outputs are not, in fact, empirical evidence of anything concrete in the physical world. The outputs of computer models are speculative simulations that portray how things might be, rather than how things actually are. It is a critical distinction between science and not-science, evidence and not-evidence.
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