Christy compared the outputs for the tropical troposphere of 73 models used by the IPCC in its latest report with satellite and weather balloon temperature trends since 1979. “The tropics is so important,” Christy explains in an email message, “because that is where models show the clearest and most distinct signal of greenhouse warming-so that is where the comparison should be made (rather than say for temperatures in North Dakota). Plus, the key cloud and water vapor feedback processes occur in the tropics.”
When it comes to simulating the atmospheric temperature trends of the last 35 years, Christy found, all of the IPCC models are running hotter than the actual climate. The IPCC report admits that “most, though not all, of [the climate models] overestimate the observed warming trend in the tropical troposphere during the satellite period 1979-2012.” To defend himself against any accusations of cherry-picking his data, Christy notes that his “comparisons start in 1979, so these are 35-year time series comparisons”-rather longer than the 15-year periods whose importance the IPCC downplays.
Why the discrepancy between the IPCC and Christy? As Georgia Tech climatologist Judith Curry notes, data don’t speak for themselves; researchers have to put them into a context. And your choice of context-say, the year you choose to begin with-can influence your conclusions considerably. While there may be nothing technically wrong with the way the IPCC chose to display its comparison between model data and observation data, Curry observes, “it will mislead the public to infer that climate models are better than we thought.” She adds, “What is wrong is the failure of the IPCC to note the failure of nearly all climate model simulations to reproduce a pause of 15-plus years.”
There is too much that they don’t, and at least for now, can’t capture. And it would be economically insane to base policy on them.
An amicus brief has been filed against the agency. Bottom line: the purpose of the Clean Air Act was to deal with local air-quality issues, not mythical global ones. The SCOTUS’s previous ruling was a terrible one, based on what can now be seen to be junk science.
The U.S. Supreme Court held that the Congress exceeded its authority by “mandating” the purchase of health insurance, but it saved the law by construing the mandate as a tax on being uninsured. Being surprised that the uninsured would object to such a tax is like being surprised that yacht owners would object to George H.W. Bush’s luxury tax on yachts.
In short, what ObamaCare means to the uninsured who were not uninsurable is higher prices for a product they already were disinclined to buy, along with a punitive tax on not buying it. That seems more like a mugging than a benefit.
How many of the uninsured lack insurance because of pre-existing conditions? It’s hard to know, but it would appear the proportion is not high. A September Kaiser Family Foundation study reported that “the high cost of insurance is the main reason why people go without coverage.” It includes a pie chart with the following breakdown of reasons for lacking insurance: Insurance not affordable, 31.6%; lost job, 29.4%; other, 17.4%; no offer, 11.2%; aged out/left school, 8.8%; no need, 1.5%.
Arguably the problem of the uninsurable was a market failure that justified government intervention of some sort. If ObamaCare’s architects had approached the matter intelligently, they would have conducted research to identify the extent of that precise problem and carefully targeted their response. Government is quite capable of implementing even modest programs disastrously, but the hubris of demanding “comprehensive reform” gave us a law that had to be marketed via massive consumer fraud, and that harms almost everyone it affects.
The next time this clown circus approaches any policy issue intelligently will be the first.