Archive for August, 2009

144 Month Trends In Models

August 31, 2009

Tada:

Since most of these trends are positive, it looks like a lot of models are inconsistent extend periods of no warming such as the last twelve year period in the satellite data, but not universally so. So which models will pass my ultimate test? Dunno. I haven’t figured out the details yet. Just dumping the data out as a graph for now.

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Drought History….

August 30, 2009

Yes, I’m still working on the model stuff. And yes, I’m busy trying to teach myself R. In the mean time, I felt like sharing this with you: The Drought History of the US:

% Area of the US Moderately to Extremely Dry (red) and Severely to Extremely Dry (Orange).
Just so that there is a hypothesis test here: Did anyone hypothesize that AGW would cause more droughts in the US? If so, I think this is enough to invalidate that idea.

But I doubt anyone familiar with the actual data or science would make such a silly claim. So it was probably Al Gore.

Sources:

http://www.ncdc.noaa.gov/oa/climate/research/2009/jul/uspctarea-wetdry-svr.txt

http://www.ncdc.noaa.gov/oa/climate/research/2009/apr/uspctarea-wetdry-mod.txt

And yes we are getting wetter. Bad? I don’t think so. But people are welcome to spurn rain if they wish.

Model Data Download Still In Progress…

August 29, 2009

…This may take a while. Any suggestions of other hypotheses to test in the mean time?

Multiple Regression Models for Tropospheric Temperature Variations

August 28, 2009

Just thought I’d call everyone’s attention to my cry for help with a pet project.

And yes, I’m still working on my hypothesis test of twelve year trends in models. Just not this second.

Downloading Model Runs…

August 27, 2009

So anyway, what hypotheses do I feel like testing? Oh, yes. I want to look at the distributions of trends in various climate model situations. I think it’s well established that the recent period of temperature stability appears to be explainable via ENSO and solar cycles, with a trend still present in the data (slides 15-22) however I’m curious whether a period of no warming for 12 years is a manifestation of natural variability in models. And if so, is there a subpopulation of models which don’t occassionally have extended periods of no warming? The reason I am curious about this is that the most recent UAH data shows a period of essentially no trend since April 1997, as of today, and also because, while a recent paper:

Easterling, D. R., and M. F. Wehner (2009), Is the climate warming or cooling?,
Geophys. Res. Lett., 36, L08706, doi:10.1029/2009GL037810.

Focused on the ten year trend in the surface data set, which has issues as pointed out recently by:

Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2009: An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J. Geophys. Res., in press.

And also, for whatever reason, E&W only seemed interested in asking whether the recent trends were inconsistent with all models-when a much more interesting question is whether there are models which don’t do that which can then be considered individually rejected hypotheses. And of course what that does to the future projections.

That’s the hypothesis I hope to test. To that end, I plan to download some climate model runs. I’ll keep you posted. Any tips or comments are appreciated.

Does Tamino Understand Criticisms of Models?

August 27, 2009

First, let me introduce myself. I’m Andrew. I’m an engineering student and I live in Florida. I comment at some blogs, in particular those on climate related topics. I usually go by Andrew at those blogs. At one of those blogs, a very interesting discussion has arisen related to a post on the blog of a “climate scientist” named Grant Foster, who prefers to go by “Tamino”. The blog which the discussion arose (and continues) on is The Blackboard. The gist of the discussion, as I read it, is whether Tamino’s two box EBM has physically realistic parameters. From what I can tell, Tamino is losing the argument. But I personally found something very interesting about the original post by Tamino himself. What he said was highlight on another climate blog, The Air Vent, here. What he said-and I do not link directly to him because I fundamentally object to Tamino’s comment policy-is really quite remarkable:

Denialists love to denigrate computer models of earth’s climate. In my opinion they only do this because they’re in denial of the result, not because of any valid evidence. They also love to make the false claim that without computer models there’s no reason to believe that global warming is real, and is going to get worse.

The term “computer model” refers to an actual simulation of earth’s climate, often in remarkable detail. Such models are (of course!) not able to predict, or even post-dict, the chaotic aspects of the sytem (the weather), but they do an outstanding job of post-dicting the global statistical characterization of the system (the climate).

What we learn from Tamino is that anyone critical of climate models is a “Denialist” whatever that means, and he then goes on to make some claims about what models do well, and what they shouldn’t be expected to do well. This is interesting in regard to the reason for this blog’s existence, which, as I hope is obvious, is trying to figure out hypotheses that can be tested about people’s beliefs about climate. Tamino is essentially say that hypothesis tests of models are appropriate on a “climatic” scale, but not on a “weather” scale. He seems to be saying that this is related to their geographic accuracy, which is odd, because the usual weather versus climate distinction is in fact in reference to time. But the claim is also false because one can readily identify key failures of models to simulate the “climate” realistically. Here is an example of a large scale, long term history of a key climatic parameter-the diurnal temperature range-and climate model simulations of it:

None of the models seems to realistically simulate the decline of the diurnal temperature range-they predict a steady decline, but the data suggest a rather rapid decline confined to about 1960-1980. Of course, it may well be that this is because of the influence landuse/urbanization on minimum temperatures (see) but I hardly think that Tamino would take that tack in criticizing this instance (one of many) in which models are seen to perform rather poorly. But enough about that. In rebutting the criticisms of models, Tamino figures it “doesn’t matter” because he can get the same answer with a simple two box model.

Is Tamino’s Reasoning Circular?

Oh, only probably. In choosing his parameters, he chooses to use 1. The same input as the GISS model and 2. The same Response time as the GISS model. The result isn’t surprising. The fit to observed temperatures is as good as GISS’s model gets. In fact, I imagine it’s pretty much identical. Except perhaps for the unphysical-ness issue.

Too Complex or Too Simple?

In defending models, Tamino seems to get the impression that the objection to models is the “computer” aspect, and thus by simplifying the model, anyone concerned that models aren’t transparent enough or that in being complex there are too many adjustable parameters, or too many things to get wrong, will be effectively rebutted. But in fact while it is true that complex models are concerning for the aforementioned reasons, there is a more important objection to model complex system which applies to Tamino’s simple model to: They aren’t complex enough. They can’t resolve weather on a spatial scale smaller than their “grids” for one thing. And any model which attempts to be complex enough will be 1. Not complex enough and 2. Take a very very very long time to run. Chris Essex gave a very good talk about these issues-and would presumably be a “denialist” for his criticism of models-here.

What’s ironic is that Tamino’s result is actually rather unsettling. It suggests that even with much more complex models, the results don’t get any better. This means that it may in fact be even harder than building bigger, badder computers to get improved results. We might-gasp!-have to actually focus on testing them against data-in particular data they haven’t been tuned to agree with already. I not sure but I think this is what “denialists” have been saying all along.

Does Tamino’s fit make sense?

Doubtless it makes sense to him. But he assumes that 1. The GISS forcing data accurately account for the time histories and magnitudes of all the relevant forcings 2. That the response times he chose are realistic 3. That the surface temperature history is accurate and has any valid thermodynamic interpretation…One could quibble with any of these. I didn’t do to bad with my own even simpler but very different model and assumptions.

Does it “matter”?

Only in the sense that any of these climate blog wars seem to matter…which is to say it doesn’t matter. Which is cliche. But true.

Anyway, I’m rather disappointed that this had to be the incident that got me to make this blog. It sends the totally wrong message. The goal of this blog is to test hypotheses and I didn’t get to test any. The good news is that I plan on thinking of some to test eventually. And thinking of ways to actually test them.