Last week, I ran a workshop for high school kids from across Toronto on “What can computer models tell us about climate change?“. I already posted some of the material I used: the history of our knowledge about climate change. Jorge, Jon and Val ran another workshop after mine, entitled “Climate change and the call to action: How you can make a difference“. They have already blogged their reflections: See Jon’s summary of the workshop plan, and reflections on how to do it better next time, and the need for better metaphors. I think both workshops could have done with being longer, for more discussion and reflection (we were scheduled only 75 minutes for each). But I enjoyed both workshops a lot, as I find it very useful for my own thinking to consider how to talk about climate change with kids, in this case mainly from grade 10 (≈15 years old).

The main idea I wanted to get across in my workshop was the role of computer models: what they are, and how we can use them to test out hypotheses about how the climate works. I really wanted to do some live experiments, but of course, this is a little hard when a typical climate simulation run takes weeks of processing time on a supercomputer. There are some tools that high school kids could play with in the classroom, but none of them are particularly easy to use, and of course, they all sacrifice resolution for ability to run on a desktop machine. Here are some that I’ve played with:

  • EdGCM – This is the most powerful of the bunch. It’s a full General Circulation Model (GCM), based on the NASA’s models, and does support many different types of experiment. The license isn’t cheap (personally, I think it ought to be free and open source, but I guess they need a rich sponsor for that), but I’ve been playing with the free 30-day license. A full century of simulation tied up my laptop for 24 hours, but I kinda liked that, as it’s a bit like how you have to wait for results on a full scale model too (it even got hot, and I had to think about how to cool it, again just like a real supercomputer…). I do like the way that the documentation guides you through the process of creating an experiment, and the idea of then ‘publishing’ the results of your experiment to a community website.
  • JCM – This is (as far as I can tell) a box model, that allows you to experiment with outcomes of various emissions scenarios, based on the IPCC projections, which means it’s simple enough to give interactive outputs. It’s free and open source, but a little cumbersome to use – the interface doesn’t offer enough guidance for novice users. It might work well in a workshop, with lots of structured guidance for how to use it, but I’m not convinced such a simplistic model offers much value over just showing some of the IPCC graphs and talking about them.
  • Climate Interactive (and the C-Roads model). C-ROADS is also a box model, but with the emissions of different countries/regions separated out, to allow exploration of the choices in international climate negotiations. I’ve played a little with C-ROADS, and found it frustrating because it ignores all the physics, and after all, my main goal in playing with climate models with kids is to explore how climate processes work, rather than the much narrower task of analyzing policy choices. It also seems to be hard to tell the difference between various different policy choices – even when I try to run it with  extreme choices (cease all emissions next year vs. business as usual), the outputs are all of a similar shape (“it gets steadily warmer”). This may well be the correct output, but the overall message is a little unfortunate: whatever policy path we choose, the results look pretty similar. Showing the results of different policies as a set of graphs showing the warming response doesn’t seem very insightful; it would be better to explore different regional impacts, but for that we’re back to needing a full GCM.
  • CCCSN – the Canadian Climate Change Scenarios Network. This isn’t a model at all, but rather a front end to the IPCC climate simulation dataset. The web tool allows you to get the results from a number of experiments that were run for the IPCC assessments, selecting which model you want, which scenario you want, which output variables you want (temperature, precipitation, etc), and allows you to extract just a particular region, or the full global data. I think this is more useful than C-ROADS, because once you download the data, you can graph it in various ways, and explore how different regions are affected.
  • Some Online models collected by David Archer, which I haven’t played with much, but which include some box models, some 1-dimensional models, and the outputs of NCAR’s GCM (which I think is the one of the datasets included in CCCSN). Not much explanation is provided here though – you have to know what you’re doing…
  • John Sterman’s Bathtub simulation. Again, a box model (actually, a stocks-and-flows dynamics model), but this one is intended more to educate people about the basic systems dynamics principles, rather than to explore policy choices. So I already like it better than C-ROADS, except that I think the user interface could do with a serious make-over, and there’s way too much explanatory text – there must be a way to do this with more hands on and less exposition. It also suffers from a problem similar t0 C-ROADS: it allows you to control emissions pathways, and explore the result on atmospheric concentrations and hence temperature. But the problem is, we can’t control emissions directly – we have to put in place a set of policies and deploy alternative energy technologies to indirectly affect emissions. So either we’d want to run the model backwards (to ask what emissions pathway we’d have to follow to keep below a specific temperature threshold), or we’d want as inputs the things we can affect – technology deployments, government investment, cap and trade policies, energy efficiency strategies, etc.

None of these support the full range of experiments I’d like to explore in a kids’ workshop, but I think EdGCM is an excellent start, and access to the IPCC datasets via the CCCSN site might be handy. But I don’t like the models that focus just on how different emissions pathways affect global temperature change, because I don’t think these offer any useful learning opportunities about the science and about how scientists work.

Can we improve the engineering of climate software?
How many errors should we expect in the IPCC reports?

2 Comments

  1. Hey up,

    All great stuff. New article in Nature on the latest climate models that include earth systems elements – and may thus have a much larger spread.

    http://www.nature.com/news/2010/100224/full/4631014a.html

    Let me know if you need a link to a PDF.

    It’s one element I’d love to development educational tools (though I’m still learning myself) – when does adding complexity help, when not? Along with other ‘simple science’ ideas like statistical significance, knowing when ‘complexity’ matters is a key skill I think more people need. It’s a hole that people like Monckton exploit with his ‘oo look, it’s a chaotic system so it can’t be predicted’ nonsense.

    On one level, the answer is entirely intuitive: weather = complex, can’t predict two weeks out; seasons = forcing from Earth’s angle to sun. Everyone can grasp that you can know which season we’ll be in six months from now, but not what the weather will be doing. It can get as complex as you like of course, but – and this is what makes the real science different from the cuckoo science – it can pretty much all start from clear, intuitive principles and build from there. Monckton’s tactic is to Wax Scientific in the hope of blinding his audience; real scientific education does exactly the reverse.

    All I’ve managed so far is a somewhat obscure little interactive illustration of chaos in the logistic equation, showing how decimal resolution affects ability to predict –

    http://www.coveredinbees.org/processing/exploringchaos/index.html

    On that: it does worry me a bit that the focus is on the huge models. I don’t know enough about it yet, but it seems to me it’s missing a basic point people need to grasp – those models are trying to get a finer grain on outcomes. The radiative forcing issue isn’t in question – what I’d like to see is some smaller models, the smallest possible, that illustrate we *know* about the forcing, we just can’t predict the exact effects, or the tipping points. Educational models should be like little alien worlds: enough like ours to illustrate the key points and give people the critical tools to spot a Monckton coming a mile off.

  2. Steve,

    Perhaps PRECIS http://precis.metoffice.com/ might be useful for this kind of workshop.

    Michael

  3. Pingback: Climate Kids | Serendipity

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