which is weak, with CAUSE of warming, which is non-existent. Since 2001 there has been no significant warming. Of course, you must understand that the El Nino peaks in 1998 and 2016 are atypical and not evidence of anything in particular.
Source:
http://www.drroyspencer.com/latest-global-temperatures/Again, I want to point out that the vertical scale is in tenths of a degree C. Then entire range is less than one degree C. As a reality check, you could not even measure the temperature of the room that you are in to within one degree C no matter how hard you tried, let alone to tenths of a degree. The noise level is clearly over 0.4 degrees. I wish to remind you of the famed
"Emperor of China Fallacy" which states:
From pg812-1020 of Chapter 8 “Sufficiency, Ancillarity, And All That” of Probability Theory: The Logic of Science by E.T. Jaynes:
The classical example showing the error of this kind of reasoning is the fable about the height of the Emperor of China. Supposing that each person in China surely knows the height of the Emperor to an accuracy of at least ±1 meter, if there are N=1,000,000,000 inhabitants, then it seems that we could determine his height to an accuracy at least as good as
merely by asking each person’s opinion and averaging the results.
The absurdity of the conclusion tells us rather forcefully that the rule is not always valid, even when the separate data values are causally independent; it requires them to be logically independent. In this case, we know that the vast majority of the inhabitants of China have never seen the Emperor; yet they have been discussing the Emperor among themselves and some kind of mental image of him has evolved as folklore. Then knowledge of the answer given by one does tell us something about the answer likely to be given by another, so they are not logically independent. Indeed, folklore has almost surely generated a systematic error, which survives the averaging; thus the above estimate would tell us something about the folklore, but almost nothing about the Emperor.
The point being that it is folly to draw conclusions from data that fall outside the measurement noise level. Since the noise level is larger than the thing that we think that we are measuring, we don't know a damned thing about global temperatures since 2001. While we would like to know if humans are causing global warming, we don't. We cannot even determine with reasonable certainty that global warming is continuing past the year 2001.
There are many things that we would like to know but do not. This leads to a temptation to jump to conclusions. But it is very bad to base policy decisions on highly uncertain conclusions.
DFM