Global Warming and Computer Modelled Anti-Life Equations

Today I saw an interesting article that might help others see the anti-life agenda of the global warming movement:

The Zeller-Nikolov climate discovery may turn the world upside down.

This is not the first time I have seen an article which casts credible doubt on the role of carbon in global warming. This is one of the best in terms of causing some serious doubt on whether there is any credible science to behind the environmentalist movement.

If it is true that carbon is not necessarily a significant contributor to global warming, why then do so many scientists think that it is?

Firstly, the consensus is not nearly as large as many would have us believe. There have long been many climate scientists whom either doubt the theory that carbon is a significant factor in global warming or are still undecided.

Below we can see a long list of such scientists.

List of scientists who disagree with the “97%” consensus on global warming.

But, in fact, it does not matter whether there is a consensus. It does not matter if 0% or 100% of scientists agree with something, in neither case is that an indication of whether something is true. At one point most people, including educated people that knew anything about anything, thought the Earth was flat or that the objects in space were divine in nature. But, no sane person would argue that the fact most people believed such things made any of them true.

Truth is a matter of concordance with reality, not a matter of how many people you can get to agree with whatever you think. 97% of people can be just as badly wrong as one person and having more people on your side is in no way an indicator that you might be right. Only the facts can indicate that.

But why do the climate scientists that do believe it, whatever the proportion that might be, believe it?

This can largely be attributed to computer modelling. They have run an endless series of computer models, many of which confirm their assumptions.

But one must be very careful with computer models. They prove nothing about how the things they model actually work. They are useful for helping to identify potential areas of research, but their results do not themselves prove anything. They are not replacements for research and experiments in order to learn about how reality works.

They are nothing more than automated thought experiments and prove no more than would a thought experiment. If you conduct a thought experiment in your mind, it proves nothing about external reality. If you want to learn how reality outside your mind works, you have to study nature by performing experiments and collecting data.

Old Computer
it does not matter if you use this old thing or a supercomputer, it proves nothing.

A computer model is a mathematical model that processes data according to whatever rules its programmers program into it. It does whatever its programming tells it do and no more. If the assumptions of the programmer are wrong, then so is your model.

The model’s programmers have to make a series of such assumptions as to how to simulate the phenomena it is intended to model. According to their understanding of the phenomena and how closely they can get their model to simulate the actual phenomena.  Which can be very difficult when you are dealing with complicated things which are difficult to accurately model or which you do not properly understand.

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