Guest Post by Willis Eschenbach
I wrote my first computer program in 1963. It was an implementation of the Sieve of Erastosthenes, used to find prime numbers. I haven’t stopped programming since then. So I am intimately acquainted with the innards of computers, computer programs, and computer models, both iterative and otherwise.
And those who read my writing know that I don’t have much use for the suite of IPCC computer climate models as a way to predict the future evolution of the global climate. I think they are Tinkertoy™ exercises in parameter tuning.
So it may come as a surprise that there is a model out there that I wouldn’t say I trusted, that would be far too strong. But I would say that it certainly bears watching, because it’s the best of the models. It bears scant similarity to any of the IPCC models. In its current incarnation, it has the lovely name of GATOR-GCMOM.
It came up recently in a Discover magazine article entitled “White Roofs May Actually Add to Global Warming”. Go figure, huh? Figure 1 shows what painting roofs white was supposed to do for the climate.
When I read the Discover story, I wasn’t surprised to find that the model that produced such a counterintuitive result was the same GATOR-GCMOM, whose development I’ve been following and speaking favorably of for over a decade. It’s the work of a brilliant man named Mark Jacobson at Stanford University. It started small, as a local or regional model to trace the paths of pollutants around point sources. In its current form it includes literally dozens and dozens of chemical, atmospheric, and oceanic processes which are not represented in any other climate model on the planet. It uses a variety of ingenious ways to do things to reduce computational overhead. A full list of the differences from IPCC models and a discussion of the development of the GATOR model is here (PDF).
So why does the GATOR-GCMOM model say that painting the roofs white will heat the planet?
The Discover article says:
The model found that more white roofs means less surface heat in cities (which is obvious enough to anyone who’s sat in a car with a black interior in the sun). Lower local temperature means less water evaporates and rises up to eventually form clouds, says lead author and Stanford University researcher Mark Jacobson. The decrease in clouds allows more sunlight to reach the Earth’s surface, leading to higher temperatures overall.
So, clouds once again affect the climate in an unexpected way. I’m shocked. The article also states:
The model also predicts that much of the light reflected by rooftops will eventually be absorbed by dark carbon soot and particulates that are especially prevalent in the air above urban areas. This could limit local cooling and cause warming elsewhere as the particles drift away.
This shows an unexpected (but reasonable) interaction between two factors, reflected sunlight and black carbon particles in the air.
Why would I think that Jacobson’s model might be showing something near reality in this question, when I am generally scornful of the IPCC models? Several reasons:
1. The time frame of the analysis is short, he’s not futzing around with 100 year fantasy forecasts.
2. Both outcomes, once examined, make sense. Changes in clouds, and in atmospheric heating from sunlight hitting black carbon, certainly would affect the outcome, the physics is well established.
3. The GATOR model started small, modeling local conditions, many years ago and built gradually outwards from there. From the start, it was frequently compared to reality and tested and refined. It wasn’t conceived of as a global model like many climate models. So it was continually being tested on how accurately it could represent the temporal evolution a host of local conditions around cities and bays, studying pollution plumes and their changes over time, comparing them to observations … a host of real-world testing unlike anything that any of the IPCC models have undergone. Then, over about twenty years, it has been slowly expanded to be a global model.
4. I may be wrong, but I cannot find any indication of tunable parameters anywhere. Seems like there must be some somewhere, but for the most part it’s truly physics and chemistry based, unlike IPCC models.
5. It uses a nesting grid scheme which allows for a variety of grid-size resolutions as needed. This lets some areas be intensively sampled (say around a city) while a larger area of the ocean might need far fewer samples.
6. It handles chemistry at a very detailed level, involving hundreds of chemical compounds in both the ocean and the atmosphere. Other climate models don’t even touch chemistry except perhaps in the simplest ways.
7. The result was counterintuitive, but still demonstrable. A model that only shows us what we already know is not that useful. This one showed us something we didn’t know.
Anyhow, for me the takeaway message is CLIMATE ISN’T LINEAR. The IPCC paradigm is, change the forcing and the temperature has to change proportionally.
But in this case, not only is the temperature response not proportional. It’s not even in the right direction. Kinda deals the whole “temperature change equals forcing change times climate sensitivity” idea a body blow …
So that’s all the reasons why I find this result quite plausible. It’s the best model on the planet, and it is uniquely qualified to look at this particular question. If Jacobson were to start using the model for hundred year runs looking for trends, that would be a big question mark for me, I don’t think any model can do that.
But for this kind of analysis? It does what the best of models can do—it points at things in front of our eyes which we might not have noticed. Doesn’t prove anything, the output of a computer model is never evidence … but it certainly teaches us something, which is much more valuable. It teaches us that in a complex system like the climate, a simple, totally obvious cause and effect relationship may not work out anything like that. As in this case, where something that obviously, logically, and unquestionably will cool the earth … may just end up warming it.
Anyhow, that’s the latest news from the land of Settled Science, where all temperatures are unshakably tied to forcings …
Regards to everyone,