A Tale Of Two Convergences

Guest Post by Willis Eschenbach

In the course of doing the research for my previous post on thunderstorm evaporation, I came across something I’d read about but never had seen. This was the claim that the models showed not one, but two inter-tropical convergence zones (ITCZ).

Please allow me a small digression here, regarding my unusual methods of study and investigation. Faced with information about the possible existence of a dual intertropical convergence zone in the models, most scientists would start by going out and researching the question in the scientific literature. First they would find out everything that is known about the models having two ITCZs. They would study what other people have written about double ITCZs. They would read what people believe are the causes of the dual ITCZ. Then, and only then, would they take up independent research.

Me, I approach a new subject the other way ’round. I don’t want to start out already knowing what other people have written about double ITCZs. I don’t want to know the various theories about them when I begin my investigation. I don’t want to understand what scientists say are the causes before I begin. Instead, I want to start out without preconceptions, without prejudices, without formed ideas of what I will find. The Zen Buddhists have a lovely term for this condition. They call it “beginner’s mind”, and they strive to achieve and maintain it. Starting my investigations with beginner’s mind forces me to invent my own methods. It makes me have to dig in deeply to understand what I’m looking at. And most importantly, it shuts no doors, it rules nothing out, it leaves intact my awe and wonder at the myriad possibilities of the amazing system I’m studying. I like to start out with the clear understanding that I understand nothing. It is a huge advantage if you wish to discover new things.

Once I have formed my own ideas about what is going on, once I’ve graphed and mapped and sliced and diced the data, once I’ve pondered the findings and the graphics to the point where I think I understand the relationships and the implications, then and only then do I go and read what other people have said about the subject.

Now, I understand that there are a lot of folks who do it the other way. And I have no problem with that. However, I do get flack for the way that I do it, people insisting that I should always start by studying what is known before I start my own investigations. Sorry, not my style. Especially in climate science, what is “known” is far too often not true in the slightest. I don’t want to be burdened with that. As Mark Twain, one of my lifelong literary heroes, said:

It’s not what you don’t know that kills you, it’s what you know for sure that ain’t true.

Now, I’m aware that sometimes my way leads me to error … and given the number of folks who notify me whenever such an error occurs, I could hardly be unaware of it.

But the other way often leads to error as well. Worse than that, however, is that it leads to a hidebound view of the subject, one which has already closed a host of doors and ruled out a host of possibilities. If someone doesn’t do independent research into a subject until AFTER they have been totally indoctrinated into whatever the current view of the subject might be, they’ve already put the blinders on. They’ve already taken up the current paradigm and the current frame without even noticing it, and sadly, that means that they are very unlikely to ever discover anything outside of that frame and paradigm … but I digress.

As you might imagine given my method described above, my first move was to go grab the rainfall data and consider the ITCZ:

Figure 1. Annual average rainfall from the Tropical Rainfall Measuring Mission (TRMM).

One of the surprises to me when I first graphed this up were the large areas of ocean in both the northern and southern hemispheres which get little or no rainfall. I never considered that there would be oceanic “deserts” of such size and scope.

The ITCZ (inter-tropical convergence zone) can be seen clearly in the TRMM average rainfall record. It is the yellow/red area that runs along and generally above the Equator. As the name suggests, the ITCZ is the area where the winds of the two hemispheres converge.

Next, I got rainfall data from a random model to see what the ITCZ looked like in the model output. It’s the bcc-csm1 model, chosen because they were listed alphabetically and I took the first one. I’ve trimmed the model output to 40°N to 40°S to match the TRMM data to allow easy and accurate comparison.

Figure 2. Annual average rainfall from the bcc-csm1 model. Data Source: KNMI

Yikes! … I’d sure call that a “double ITCZ”, all right. I can see why this would be very worrisome. The model is claiming extensive rainfall in parts of the central Pacific where in fact there is almost no rain at all. For example, in the observations, the ITCZ in the Pacific has dark blue areas of no rain both above and below it. The model has neither. I also note that the model says that there is about 20% more rainfall in the covered area than the observations show. Finally, I note that this gives a modeled evaporative cooling about 15 W/m2 larger than in the real world. Errors like these make me laugh at the claims that the models can show the results of a change of a few W/m2 in the forcings … but once again I digress …

To gain a better understanding of the two convergence zones, I made a movie loop of the monthly modeled rainfall so I could compare it to the movie loop of actual rainfall that I showed in the last post. Here are those two movie loops.

Yikes again! It’s interesting. Even better, it’s not at all what I expected, which is the most fun part of science. Actually, the model appears to only have one ITCZ … but the model ITCZ spends half the year north of the equator and the other half south of the equator. The net result looks like two ITCZs, but it’s not.

The problem appears to be that the model is too symmetrical. As a result, the ITCZ is pulled evenly first north and then south of the equator. But for some unknown reason, that doesn’t happen in the real world. [Curiously, in both cases the ITCZ never occurs right at the equator. It may have something to do with the existence of the equatorial counter-current, which runs along the equator in the opposite direction to the waters just north and south of it … but that is just speculation.]

I can see that this would be a particularly thorny problem to solve. It’s one of the difficulties with iterative models. You can never be sure in advance what some small change might do. And in particular, this asymmetric oddity would require unknown pressures to maintain itself. Hard to even guess where and why the models are wrong, when as far as I know, we don’t know why the real ITCZ isn’t symmetrical in the same way that the modeled one is. (In passing, to me this is the real value of models—to point out the interesting areas where the world does NOT agree with the models.)

Now, I’m sure there’s more to learn in all of this investigation of modeled rainfall. And normally, this would be nearing the point in my investigation where I would go Google “double ITCZ climate models” or something and read some of the literature … but why? For me the model results are meaningless. Almost all of the active temperature-regulating emergent phenomena are far smaller than the model gridscale. So phenomena like thunderstorms, dust devils, tornadoes, and tropical cumulus are not modeled, they are merely parameterized … and those are the very phenomena which keep the global surface temperature regulated between narrow limits (e.g. ± 0.3°C over the 20th century). In my opinion, the lack of such sub-gridscale phenomena is why the modeled rainfall patterns over the ocean are so bizarre. Without the details of how and where and when the thunderstorms emerge, it would be hopeless to try to model oceanic rainfall.

Since the models don’t explicitly model the very phenomena that keep the world from overheating or excessive cooling, the model results are useless to me. So I try to not waste too much time on them.

Anyhow, that’s my first and likely only look at modeled rainfall. As Demetris Koutsoyiannis pointed out from his study back in 2008 entitled On the credibility of climate predictions,

The results show that models perform poorly, even at a climatic (30-year) scale. Thus local model projections cannot be credible, whereas a common argument that models can perform better at larger spatial scales is unsupported.

Can’t say fairer than that …

My best to everyone,

w.

My Usual Request: If you disagree with me or anyone, please quote the exact words you disagree with. I can defend my own words. I cannot defend someone’s interpretation of my words.

My New Request: If you think that e.g. I’m using the wrong method on the wrong dataset, please educate me and others by demonstrating the proper use of the right method on the right dataset. Simply claiming I’m wrong doesn’t advance the discussion.