Coronavirus models and climate change models both have their deficiencies. Here are excerpts from Ken Haapala’s latest thoughts on the topic, from the SEPP website (Science and Environmental Policy Project):
In the midst of the lock-down of much of the U.S. public and the collapsing economy; some Americans are learning a few important lessons. One, the country is a republic with a written Constitution. As President Trump realized this week, that Constitution grants the Federal government limited powers, even during a health emergency.
And two, numerical models are not infallible. Indeed, almost daily, Drs. Birx and Fauci repeat on television that: “this model is only as good as the data we put into it.” Speculation, scenarios or projections, may be interesting but must be supported by evidence fitting the issue. Unfortunately, all too frequently government policy has been based on models using inappropriate data.
For example, for several decades beginning in the 1970s, Federal government energy policy was based on the fear the country was about to run out of oil and natural gas based on Federal energy models. These models were based on easily recoverable reservoirs, subsurface pools, that were on shore, and ignored the vast offshore resources such as the Gulf of Mexico and the North Slope of Alaska, and vast difficult-to-release onshore resources, especially tight shale.
Similarly, the UN and some U.S. government entities are promoting the fear that carbon dioxide and other greenhouse gases are causing dangerous global warming by ignoring the vast evidence that greenhouse gases are not causing a dangerous warming of the atmosphere, where the greenhouse effect occurs.
* * *
One has to be skeptical of any model projecting future deaths which was designed using the numbers from China. Correspondingly, one has to be skeptical of the dubious quality of the doctored surface data used in designing the climate models created by laboratories in the US and those largely used by the UN Intergovernmental Panel on Climate Change (IPCC).