My thought is that it seems to me that both processes are driven at least as much by amount of rainfall and atmospheric CO2 content as by temperature. It would be begging the question to assume that high CO2 correlates to high temperature in the proxy measurement, then turn around and use that measure to determine that a temperature trend is caused by CO2.

The only thing I can think of (and it’s been years since I’ve delved into this level of mathematics, so I may simply be talking out of my ass on this) is that an “order 2 polynomial” would be based on the cross-sectional area of the cone (i.e., r^2–makes it 2nd order). They’d have to make some guesses and approximations, but maybe they’ve found a polynomial that does fit.

Of course, they could have just as easily found a 2nd degree polynomial that forces the data to fit their preconceived conclusions, so there you go. Without seeing the details (raw data, algorithms, mathematical justifications for certain modeling assumptions, etc.), there’s no way to know what is really happening behind the scenes.

But we should just trust them. They know what they’re doing….

C’mon already. quit making unprovable assumptions in theoretical mathematical models and passing this junk off as “science”.

It isn’t science anyway. It’s computer model backmasking and it just isn’t “settled”.