Arrhenius also predicted that feedbacks would cause an amplification of the effect of CO2.
Nope. In fact I have written about how I resolved my confusion on that point...
David Piepgrass

But you’ve literally seen the opposite. You’ve literally seen feedbacks sink *more* CO2 in response to increased human emissions.

Again, I think this goes back to the very basics — do you believe that atmospheric CO2 is driven by dependent variables, or independent variables?

Another analogy, perhaps this will break whatever cognitive logjam we have due to preconceptions — fat accumulation. Perhaps you’ve heard of “calories in/calories out”.

Now, one might expect that this is trivially true — you can only get fat if you eat more calories than you expend, and those excess calories get shunted into fat cells. But what if those two variables are dependent? What if, when you have too many calories in, the body finds ways to dump them without accumulating fat? Or the body finds ways to slow down the metabolism to reduce calorie usage?

Enter stage right, The Krebs Cycle. Fat accumulation actually has a hormonal driver, namely, insulin. The higher your insulin levels, the more calories get stuffed into fat cells. The lower your insulin levels, the more calories get released from fat cells. Each human having a different insulin sensitivity, the “insulin resistant” tend to get fatter, quicker, and the “insulin sensitive” tend never to get fat.

So what does this mean about calories? If the trivial model doesn’t actually work, and you are actually dealing with a factor that you weren’t even measuring in your original analysis, and that otherwise, all the variables in your original analysis were actually dynamically dependent on each other, you’ve got to change your thinking.

So, what do you think might be the “insulin” regarding atmospheric CO2? :)

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