Thank you for the link, Willis. The paper contains the fact(s) I was seeking.

There are too many interactions, too many feedbacks, to just assume that. You’d have to prove that before I’d buy it.

Amen.

See the discussion on the Briggs site.

w.

PS – I love their statement about albedo. The model is more than “somewhat” tuned for albedo, it is entirely tuned for albedo and for global radiation balance … the report sez:

The model is tuned (using the threshold relative humidity
U00 for the initiation of ice and water clouds) to
be in global radiative balance (i.e., net radiation at
TOA within 0.5 W m 2 of zero) and a reasonable
planetary albedo (between 29% and 31%) for the control
run simulations. In these experiments we use U00
0.59, 0.57, and 0.59 for ice clouds and 0.82, 0.82, and
0.83 for water clouds in M20, F20, and M23, respectively.

The interesting part to me is that when their clouds are tuned for the proper albedo (about 30%) and to achieve global radiation balance, the cloud cover is way low (58% vs 69%, see Table 3, p 159). If that were my model, I’d be disassembling it to see why the huge error … but they just carry on as if everything were just fine.

I thought that readers here might be interested in the following statements
from the GISS manuscript.

page 168

Similarly, satellites that see clouds cannot generally see thru them,
and this needs also to be accounted for.

The net albedo and TOA radiation balance are to some extent tuned for,
and so it should be no surprise that they are similar across models
and to observations.

So despite all of Gavin’s bluster, the article clearly states that the model has been tuned using multiple gimmicks to obtain agreement with certain questionable information. Isn’t that exactly what I proved earlier,
i.e. that by suitably choosing the forcing. one can obtain any solution that one wants, even for an inaccurate numerical model.

Jerry

Satellite data is not in situ and neither is reanalysis data.
The former is a blend of surface info (if it exists) and satellite radiance info. The accuracy of the transformation of radiances to model variables is
a very questionable procedure, especially in the presence of clouds.
The latter is a blend of model and observational data and can be completely in error, especially near the equator where there are few obs and the physics is not understood.

Note that GISS receives money from NASA. I was once told that anyone that
criticized NASA would have their funds chopped. I doubt that GISS is going to criticize the satellite data altough there has been an extensive discussion of its poor quality on this site.

Jerry

My understanding of what Gavin said is like your “b”. It was that, although things are in error in absolute terms, they are correct in relative terms. For example, suppose you want to model a car, and see what happens when you increase the fuel by some amount. Now, the exact modeled value for the car speed given a certain amount of fuel might be off.

But my understanding of the processes, my calculation of the conversion process of fuel to MPH, might be good enough so that the various changes from a given change in fuel would be reasonable, even though some absolute values might be off.

And in fact every model runs on just this assumption, that there are things that we can safely ignore and things that we have to pay close attention to.

I’d need a lot of supporting evidence, however, before I’d believe that a climate model with parameterized cloud formation could properly model the result of a given change in forcing. There are too many interactions, too many feedbacks, to just assume that. You’d have to prove that before I’d buy it.

Gavin, of course, says something like “But look at how well our model handles Pinatubo”, which is true. But he thinks that means something. Me, I think that the ability to correctly represent transient events is a much simpler problem than representing long-term evolutions in what I see as a naturally equilibrated system.

w.

“…In other words, despite the fact that their cloud representation is way off (59% areal coverage modeled, 69% measured) and is parameterized (by specifying ad-hoc the conditions at which clouds are supposed to form), their model is still accurate in measuring the difference in forcing between say, a run with CO2 doubled and a run with CO2 held steady.”

Can you please clarify Gavin’s claim for me? Is it:

a) Cloud formation doesn’t change in the presence of an external forcing from CO2.

b) The CO2-induced changes in cloud formation from a base of 59% are equal to the change(s) from a base of 69%. And since the incremental changes are the same in either case, the absolute error in baseline doesn’t matter.

c) Other?

Also, if possible, could you please post a link to the source(s) for your comparison of Planet Earth vs Planet GISS. I know you’ve posted it before, but one was a dead link, and I’m having trouble finding the other occurences.

Best,

James