Guest Post by Willis Eschenbach
After many false starts, thanks to Steven Mosher and Derecho64 I was able to access the forcings used by the CCSM3 climate model. This is an important model because its successor, the CESM3 model, is going to be used in the laughably named “CIM-EARTH Project.” Anyhow, just as new telescopes have “first light” when they are first used, so here I’ll provide the first light from the CCSM3 ozone forcings. These are the forcings used by the CCSM3 model in their hindcast of the 20th Century (called the “20C3M” simulations in the trade). How well did they do with the hindcast? Not all that well … but that’s a future story. This story is about ozone concentrations. Figure 1 shows the concentration at the highest-altitude of the 18 atmospheric levels, concentrations that were used as one of the forcings for the 20C3M climate model runs.
There are so many things wrong with using that “data” as an input to a climate model that I scarcely know where to start.
First, the provenance. Is this historical data, some kind of record of observations? Nope. Turns out that this is the output of a separate ozone model. So instead of being observations, it’s like a Hollywood movie that’s “based on a true story”, yeah, right … and even then only for part of the time.
Second, what’s up with the strange sub-annual ups and downs (darker sections) in the annual cycle? They start out in the upper part of the annual swing, and then they change to the lower part after about 1970. Nor is this the only altitude level with this kind of oddity. There are 18 levels, and most of them show this strangeness in different forms. Figure 2 shows their claimed ozone concentrations from about half that altitude:
Again you can see the sub-annual cycles, but this time only post-1970. Before that, it goes up and down in a regular annual variation, as we would expect. After that, we see the strange mid-year variation. Most other altitude levels show similar oddities. Again, it appears that the modelers are not applying the famous “eyeball test”.
Third, how on earth can they justify using this kind of manufactured, obviously and ridiculously incorrect “data” as input to a climate model? If you are trying to hindcast the 20th century, using that kind of hockeystick nonsense as input to your climate model is not scientific in any sense, and at least gives the appearance that you are cooking the books to get a desired outcome.
Anyhow, that’s not why I wanted to access the forcings. I wanted to compare them to the output of the model, to see if (like the GISS model) it is functionally equivalent to a trivially simple single-line equation. I’m working on that, these things take time. I just posted this up because it was so bizarre and … well … so hockeystick-like.
More results as they occur,