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I am in no way trying to say that human behavior has a negligible effect on global climate.
As I said previously, I think that water pollution is paramount to CO2 in terms of what should be our focus.
The idea of CO2 being the sole cause of global temperature change does not have valid research to back it up.
Just as I pointed to in the article, the research uses correlations that show temperature increases in isolated incidents, as well as the lack of evidence supporting other causes to establish causality for their hypothesis, and that is not proper science.
As far as the increase in global temperatures, if I am not mistaken, the earth recently began a cooling trend.
And once again, from my understanding, if one was to look at a graph of global temperature change over the past 100,000 years instead of the last 1000 years, then it shows that we are not experiencing anything out of the ordinary.
I am doing a search for a graph that will substantiate my previous comment, but it is very difficult to find the global temps graphed over the past 100,000 years.
I am only finding the past 1000, which would fall under the fallacy of scale in research.
The article is in no way scientific, I will give you that, but it is both what the scientists are saying and the overall theme and presentation of the article that I find to be so troubling.
Originally posted by NoHierarchy
reply to post by Josephus23
Haha, I was thinkin the same thing as I typed out one of my last responses. In a time like this, of such division, our minds seem to need deeper reminders of why we should all just get along.
Likewise on the friending. I added ya.
Originally posted by hotpinkurinalmint
Nobody is ever going to get a "smoking gun" in science that proves causation with metaphysical certainty. In areas like Environmental Science, where it is nearly impossible to conduct a laboratory experiment which exactly models the earth, all scientists can rely on is correlation.
This is not to say that relying on strong correlations is junk science. Scientist rely on correlations all the time to prove theories.
For example, drug makers rely on correlations to determine whether their experimental drugs are safe and effective. You can never show an experimental drug "caused" sick patients to get better. All you can show is a statistical correlation between sick patients taking the drug and getting better.