Global Warming Part I: The Science?

This has been rattling around in my head for some time now, but as I was writing this up I found I had far too much to say for one post and so I've broken this down into a multi-part series. Part I is about the science behind the whole Global Warming fad.

Global warming has become the hot topic of the day. It seems hardly a day goes by that we don't hear something about it in the news and politicians are going on and on about it and what we should do about it. Usually this takes the form of regulating carbon emissions and many countries and states have already put in place restrictions on these emissions. A lot of people are very worried about global warming and what it will do to us all, so much so that a group of politicians got together and decided to enact something call the Kyoto Protocol which requires assenting nations to greatly reduce their greenhouse gas emissions. But what exactly is all the hype about? Should we really be getting all worked up about global warming and be spending trillions of dollars in an attempt to curb it? I think not. Let me explain why.

First of all it's poor science. Well actually to be more precise, it is not science at all. You see, science involves using the scientific method to arrive at a conclusion. This means it needs two key things: observable and measurable evidence, and repeatability. Thus for example something like the law of gravity is scientific. We can observe what happens when we drop something and we can measure the acceleration change and we can do this over and over and over again making us extremely certain that this law holds true.

Global warming on the other hand does not involve repeatability of any kind since it is merely conjecture about the the future. Also, It only involves evidence insofar as it extrapolates far beyond what is mathematically and scientifically acceptable, and it ignores true evidence in that most of the parameters in models have to be guessed at or estimated since we cannot now everything about our climate. It is far to complicated for even the most powerful computers to come even close to calculating the effect of every parameter, without even considering the fact that we are far from know what exactly all these effects are. Let me briefly illustrate this fact. There is something that is known as the butterfly effect I know that link is quite technical but the point of what I'm trying to show you is that potentially every flutter of a butterfly's wings can have a huge effect on the weather and thus unless our models account for every flutter of every butterfly's wing, ever bird that flies, every man and animal and plant and fish that moves on this earth, unless it accounts for every fluctuation in the sun's energy output, unless it accounts for all the forest fires and volcanoes, unless it accounts for so many parameters that we can never know, it will not be truly accurate. The question is how accurate do we have to be to have a reasonable model? How much stuff can we ignore and how much do we need to include? We don't know. We are missing the repeatability factor and so much of what is done is just educated guesswork. The parameters used and the weight they are given in the models is guesswork. The model designers use the parameters they think matter the most and then assign them the values they think they will have.

Now of course we don't need to know any of these things to be able to say that global warming will happen. If, for example, we were to look at global temperatures and say that for the last 500 year the temperature has always gone up be 0.01 degrees per year we would be able to say with a large degree of certainty that it will continue to do so. However to look at the approximately 30 years of data that we have indicating a global warming trend and extrapolate that into the next 100+ years is HORRIBLE science. I would receive an instant F if I tried to do anything of that sort on a lab or assignment. With only 30 years of data you cannot extrapolate more than 5 years into the future and still have any degree of certainty. For example if we were to look at the 30 year warming trend that occurred from ~1915-1945 we would predict that average world temps would be about 1 degree F higher than they are right now. We can't use the data that we have to extrapolate into the future until we have much more of it.

Therefore, we see that since the whole global warming theory relies on simplified parameter inputs (and therefore is highly susceptible to the preconceptions and assumptions of the person creating the model and entering the parameters) and also has no repeatability and cannot be verified or tested it is not true science.

Coming next: The consensus?