I don’t follow this too closely, but it looks like you two do.
I haven't followed the issues closely for a few years, since it seemed that politics was likely to continue to trump science.
Can I ask, are you familiar with any good studies that question if long term CO2 increases are even possible?
So wouldn’t oxygen be created that brings CO2 levels back down again? Do you think that this balance is adequately addressed in global warming/climate change models?
I can't answer either question. But you might check out
www.co2science.org for those specific questions, and
www.junkscience.com and
www.john-daly.com for more general information. John Daly died last year, and his site, though still maintained, is not as active as before. Not sure if all his work is still available there.
A prime piece of evidence linking human activity to climate change turns out to be an artifact of poor mathematics.
In PCA and similar techniques, each of the (in this case,
typically 70) different data sets have their averages
subtracted (so they have a mean of zero), and then are
multiplied by a number to make their average variation
around that mean to be equal to one; in technical jargon,
we say that each data set is normalized to zero mean and
unit variance. In standard PCA, each data set is
normalized over its complete data period; for key climate
data sets that Mann used to create his hockey stick graph,
this was the interval 1400-1980. But the computer program
Mann used did not do that. Instead, it forced each data
set to have zero mean for the time period 1902-1980, and
to match the historical records for this interval. This is
the time when the historical temperature is well known, so
this procedure does guarantee the most accurate
temperature scale. But it completely screws up PCA. PCA is
mostly concerned with the data sets that have high
variance, and the Mann normalization procedure tends to
give very high variance to any data set with a hockey
stick shape. (Such data sets have zero mean only over the
1902-1980 period, not over the longer 1400-1980 period.)
The net result: the “principal component” will have a
hockey stick shape even if most of the data do not.
Mann used normalization.
He made his data conform to his own opinion.