On October 7, hordes of business executives prepped at the White House and then descended on (ascended to?) the Congress in support of climate change legislation. The thrust of their presentation was that cap and trade would stimulate the economy — particularly the economies of the companies for which they work.
Without even getting into dubious economic stuff, who would benefit financially or politically, or whether United States enactment of climate change legislation is needed to help President Obama confirm his humble place on the world stage, a useful preliminary question is whether any climate change legislation would have a beneficial impact on, well, the climate.
Al Gore et al. to the contrary notwithstanding, science has taken a backseat to ideology and financial interest, and the answer is not known. Carbon dioxide emissions — the focus of the current legislative efforts — may or may not contribute to climate change; if they are a significant causal factor, it is far from certain whether the change will be to make it warmer or cooler, better or worse.
Studies have shown that there seems to be a relationship between global warming and carbon dioxide concentrations; studies have also shown that warming trends occur before, and therefore not necessarily because of, increased carbon dioxide concentrations. Despite the lack of attention paid by the media, the world has been in a period of cooling for almost a decade and may well continue in that direction for at least the next couple of decades, despite (or even, perhaps, because of) the increases in carbon dioxide concentrations. The Arctic ice, said to be vanishing, may not be. According to a recent study, vector borne diseases (malaria, Lyme disease, etc.) have increased with warmer temperatures. The study, at least as reported in the article, does not seem to address the problem that we have had cooling for the past decade.
The only thing to be said with certainty is that there has been an increase in studies. “In 2008 alone, there were some 4000-odd peer-reviewed papers published on the topic.” One must wonder how many of them were funded by U.S. taxpayers.
Almost forty years ago, in the 1970s and as recently as the late 1980s, great concern was expressed about a coming carbon dioxide-induced ice age, and in 1986 it was claimed that something had to be done immediately to prevent global cooling from producing an ice age, likely to kill off a billion people due to reduced food production. Now global warming is itself the demon, likely to cause the planet to warm by 6.3 degrees Fahrenheit by the end of the current century. According to a report issued a few weeks ago by the United Nations Environment Program, this increase will occur “even if the world’s leaders fulfill their most ambitious climate pledges.” This is a “much faster and broader scale of change than forecast just two years ago.”
It seems highly unlikely that all of those “most ambitious” pledges will be met. According to a January 2009 NOAA study, the climate change that is taking place because of increases in carbon dioxide concentration is largely irreversible for 1,000 years after emissions stop. Among illustrative irreversible impacts that should be expected if atmospheric carbon dioxide concentrations increase from current levels near 385 parts per million by volume (ppmv) to a peak of 450-600 ppmv over the coming century are irreversible dry-season rainfall reductions in several regions comparable to those of the “Dust Bowl” era and inexorable sea level rise.
If so, it’s probably already too late to act; too much damage (if any?) has already been done.
One way to verify the predictive accuracy of a model is to put data from the past into it, predict the present, and see whether the prediction matches present conditions.
None of the alarmists and their supercomputer climate models ever predicted even a 30-year respite in their apocalyptic scenarios. Nor did they predict that the Sun, that thermonuclear furnace in the sky that has more influence on Earth’s climate than any number of Ford Explorers, would suddenly go quiet for an indefinite period. If the results don’t coincide with the model results, the model is wrong, the data are wrong, or both are wrong.