Feedbacks Misdiagnosed

I have been following the climate debates rather closely these days. I'd rather be doing IEC Fusion but that is stymied for lack of research funds. So the climate debate keeps my brain engaged until I can put it to more productive uses.

Let me start from the beginning. Here is how the warmists say global warming works:

1. Extra CO2 makes the atmosphere less transmissive of heat
2. That causes the atmosphere to get hotter
3. That causes more water vapor in the air
4. Which causes the atmosphere to get much hotter

Item #4 - more water vapor leads to heating is based on measurements and calculations. The measurements are pretty good in this case since they are done by satellites, so the question is are the calculations correct?

Roy Spencer says we are not doing the calculations right because we are assuming that certain things are uncorrelated when in fact they are correlated. He says that because of the way the calculations are done that this almost always leads to a positive feedback result from the calculations.

First he does a software experiment and proves his thesis with that. Well you can prove anything with computers. How about some real live data.

Now, what we really need in the climate system is some big, non-cloud source of radiative forcing, where the cloud feedback signal is not so contaminated by the obscuring effect of cloud forcing. The only good example we have of this during the satellite era is the cooling after the 1991 eruption of Mt. Pinatubo.

And guess what? The SW [shortwave - ed.] cloud feedback calculation from the Pinatubo-caused variability in Forster and Gregory was – surprise, surprise! – anomalously negative, rather than positive like all of their other examples of feedback diagnosed from interannual variability!

So what is Roy's conclusion?

What I fear is that we have been fooling ourselves with what we thought was positive cloud feedback in observational data, when in fact what we have been seeing was mostly non-feedback cloud “forcing” of surface temperature. In order to have any hope of ferreting out feedback signals, we must stop averaging observational data to long time scales, and instead examine short time-scale behavior. This is why our GRL paper addressed daily variability.

Richard S. Lindzen has been saying this since at least 2001. Here is a somewhat less technical explanation with better pictures. Until this "experiment" Lindzen had no way to explain why what he thought was true was not explained by the data. It looks very much like the data is correct but our assumptions about its nature are not.

Which is another good reason why climate scientist must make public their data and methods. There could be other errors.

OK there is the science controversy. What does this mean politically? If the feed back is negative, not positive, CO2 is way less important than people have thought and the temperature rise from a given amount of CO2 will be much less than calculated by the current models.

This could be a big thing politically because if it holds up it means that we will not have to cut back our energy use while we work to solve our long term energy needs. Like with that fusion project I mentioned. Which could use $15 or 20 million for research. Contact me.

Lubos at The Reference Frame has some thoughts.

Cross Posted at Power and Control and at Classical Values