I recently read a great article in the July/August 2014 issue of Analog: Science Fiction and Fact. The article was 'Spanking Bad Data Won't Make Them Behave, by Michael F. Flynn' that goes on to discuss how facts are postulated through theory and how those facts can be interpreted differently by others. It really lays out a good argument against the global warming theory. The author makes a pretty good case that all theories are subject to dismissal if put in context against dissenting data of a conflicting theory.
There are several ways to collect data, but all collection methods can be subject to issues given the parameters of the sample set. You see if you were to take climate change numbers for example, CO2 being the one always quoted, the numbers currently seem to be on the rise. A sudden sharp rise from about the 1960s to now. If we look at how those samples were taken we also see a direct correlation with the evolution of transistors, a key component in the measuring equipment of CO2. Kind of makes you think does it not? Could the meteoric rise in measurable CO2 actually be a function of more efficient measuring equipment? Which brings us to 'Operational defintions'. The act of changing equipment, method and even operator can change the data. I would be very curious to compare notes with some of these climate scientists who champion CO2 as a deciding factor of this change.
Every 100,000 years or so there is a noticeable spike in CO2 levels that is followed by a cooling period. Guess how many years ago the last spike occurred? They like to point to this data and jump up and down at their 'EUREKA!!' moment because of the 100ppm higher spike than the fossil record. This is where the issues with data comes into play. There are several ways that data can 'behave badly'. Usually this behavior is driven by the collection methods. Judgement and Convenience samples are sometimes what skews the data. It's be proven that global warming data has been subject to both of these data killers. According to the data they have used there have been swings from a high of 7000ppm to a low of 180ppm. It is near impossible to measure past CO2 levels accurately because all samples are subject to 'Convenience' data contamination. You can't just fly back a million years ago and take a measurement at the Mauna Loa Observatory can you? So all of the samples are samples of convenience. They had to get them where they could and it was not a broad spectrum analysis. Currently we are using data from a near volcanic(source of CO2) equatorial site and the fossil records are all from polar regions. It's very difficult to put these data sets in the same column.
sTo quote the article from Flynn, "Probabilities depend on statistical model applied, and for an unstable process there may be no model. Even for stable processes, the appropriate model may not be the normal; yet many folks use the good ol' Bell Curve as a substitute for thought." There are too many variables to use strictly CO2 as deciding factor of climate change. We do not completely understand the other factors being that our knowledge of how our climate works is still in it's infancy. Best models peg water vapor at being the largest contributor to global warming and the percentage swings from 36 to 70%. Quite a variation huh? How can you build a reliable model on a 100% variation? I don't expect my views to change the world. I do expect it to broaden horizons, to spark dialog and question the status quo. The question we should be trying to answer isn't how do we stop global warming. The real question should be, "Who profits from it?".
That's my two cents, spend 'em or put 'em in the dish for the next person.
