There were many comments about good science, bad science, and what not. Let us not forget the scientific method. That method requires the following
- Make observations on a subject (in this case global temperature changes)
- Develop an hypothesis based on those observations
- Make predictions based on the hypothesis
- Define experiments or additional observations to test the hypothesis
- Execute the experiment or make the observations and compare against the prediction
- If the predictions are not observed, go back to the second step. If the predictions are observed go to the third step
Only after many, MANY iterations of this method can we say that the hypothesis is converging on something useful and sound.
So, there was an observation do in the '80's that showed a rapid increase in temperature. A hypothesis was created that stated that the increase was caused by a greenhouse gas effect, and CO2 being a greenhouse gas, the cause was manmade CO2 accumulation. The prediction of this hypothesis is that global temperatures will continue to rise until we can stop manmade CO2 accumulations.
since it is a little tough to run the experiments directly on the earth, computer models of the earth were created and the experiments were run on these computer models. The output of these simulated experiments met the predictions, and therefore the scientists indicated that hypothesis had some credence. Additional hypothesis were added (such as melting glaciers) and the models were enhanced to run the experiments to test the new predictions.
All of this is good science in that it is following the scientific method correctly. The problem, of course, is the experiments are not conducted on anything real, but only on models of a real thing. If the model is incomplete or biased, the data gathered from the model is incomplete or biased. The conclusions therefore can only apply to the model, not to reality. However, this subtle distinction is lost on the media and the government officials pushing an agenda. It is also not emphasized by the scientists looking for funding from the same government officials pushing an agenda.
So, how do we test the models? Well, we could run them backwards and see if they predict the past (they all fail). We could test to see if the predictions on data from 1900-1999 entered into the model will predict accurately the results of 2000-2009 (especially 2008-2009 timeframe). As far as I know, they all fail with this test as well.
You see, all of the models are based on limited time scale. They do not take into account the 26,000 year earth tilting cycle. They do not take into account solar activity cycles. They do not take into account non-cyclic volcanic and other seismic actions. They do not take into account any other action for which we have little or no data.
When we look at the data over ranges exceeding 200 years (the timeframe covered by large CO2 generations by humans), we see a much larger set of variations in climate than anything predicted by these models, and all of these variations have nothing to do with manmade anything.
So, that bad science comes from using a model and a data set that is so limited in scope that it cannot possibly be anything by an interesting game, and yet refusing to accept the scientific method once this has been pointed out. Worse, the politicians with an agenda are now using this “science” as the ultimate law of nature to force new policies on the public. These new policies will cost the world trillions of dollars in redirected resources and efforts to solve a problem that not only does not exist, but the solution will not have a measurable impact to climate change at all. (If pumping billions of tons of CO2 into the atmosphere is NOT the cause of climate change, then eliminating this CO2 generation will not reverse any observed climate change.)
I would like to make one last point before I leave this subject. Someone was looking at the temperature/CO2 level graph of the last 600 million and saw what they considered to be a correlation. First off, it is amazing what patterns the brain can see in random events (many pieces of modern art use that very feature). However, even if there was a complete correlation, the scale is such that it is impossible to tell which is causing what. It is highly possible, and in fact likely, that increases in temperature actually cause an increase in CO2, not the other way around.
As an example, I will point out that a tropical rain forest does not absorb any new CO2 – it has reached a steady state. While a tree may store a lot of CO2, when that tree dies and falls over, the bacteria, fungus, ants, termites, and what not eat that tree, releasing all of its carbon back into the atmosphere as CO2 and methane (and a few other things). None of it remains in the ground, sequestered from the atmosphere. On the other hand, a savanna actually does sequester carbon in the form of an increasingly thick layer of loam (where organic material stays in the dirt). As temperatures rise, tropical, sub tropical, and temperate forests expand into grasslands, resulting in releasing of the carbon stored in the dirt. This release could, in fact, cause CO2 levels to rise because temperatures rose. This is opposite of the assumption that it is CO2 levels rising that causes the temperatures to increase.
The bottom line: we know so little about how our climate works, and our models are missing so much information, any policy based on these hypotheses is way more likely to be wrong – completely wrong than they are in being right. It would be nice if this issue would be removed from public debate and put back into the scientific method.