I picked up Stephen Schneider’s “Science as a Contact Sport” to read on travel this week. I’m not that far into it yet (it’s been a busy trip), but was struck by a comment in chapter 1 about how he got involved in climate modeling. In the late 1960’s, he was working on his PhD thesis in plasma physics, and (in his words) “knew how to calculate magneto-hydro-dynamic shocks at 20,000 times the speed of sound”, with “one-and-a-half dimensional models of ionized gases” (Okay, I admit it, I have no idea what that means, but it sounds impressive)…
…Anyway, along comes Joe Smagorinsky from Princeton, to give a talk on the challenges of modeling the atmosphere as a three-dimensional fluid flow problem on a rotating sphere, and Schneider is immediately fascinated by both the mathematical challenges and the potential of this as important and useful research. He goes on to talk about the early modeling work and the mis-steps made in the early 1970’s on figuring out whether the global cooling from aerosols would be stronger than the global warming from greenhouse gases, and getting the relative magnitudes wrong by running the model without including the stratosphere. And how global warming denialists today like to repeat the line about “first you predicted global cooling, then you predicted global warming…” without understanding that this is exactly how science proceeds, by trying stuff, making mistakes, and learning from them. Or as Ms. Frizzle would say, “Take chances! Make Mistakes! Get Messy!” (No, Schneider doesn’t mention Magic School Bus in the book. He’s too old for that).
Anyway, I didn’t get much further reading the chapter, because my brain decided to have fun with the evocative phrase “modeling the atmosphere as a three-dimensional fluid flow problem on a rotating sphere”, which is perhaps the most succinct description I’ve heard yet of what a climate model is. And what would happen if Ms. Frizzle got hold of this model and encouraged her kids to “get messy” with it. What would they do?
Let’s assume the kids can run the model, and play around with its settings. Let’s assume that they have some wonderfully evocative ways of viewing the outputs too, such as these incredible animations of precipitation from a model (my favourite is “August“) from NCAR, and where greenhouse gases go after we emit them (okay, the latter was real data, rather than a model, but you get the idea).
What experiments might the kids try with the model? How about:
- Stop the rotation of the earth. What happens to the storms? Why? (we’ll continue to ask “why?” for each one…)
- Remove the land-masses. What happens to the gulf stream?
- Remove the ice at the poles. What happens to polar temperatures? Why? (we’ll switch to a different visualization for this one)
- Remove all CO2 from the atmosphere. How much colder is the earth? Why? What happens if you leave it running?
- Erupt a whole bunch of volcanoes all at once. What happens? Why? How long does the effect last? Does it depend on how many volcanoes you use?
- Remove all human activity (i.e. GHG emissions drop to zero instantly). How long does it take for the greenhouse gases to return to the levels they were at before the industrial revolution? Why?
- Change the tilt of the earth’s axis a bit. What happens to seasonal variability? Why? Can you induce an ice age? If so, why?
- Move the earth a little closer to the sun. What happens to temperatures? How long do they take to stabilize? Why that long?
- Burn all the remaining (estimated) reserves of fossil fuels all at once. What happens to temperatures? Sea levels? Polar ice?
- Set up the earth as it was in the last ice age. How much colder are global temperatures? How much colder are the poles? Why the difference? How much colder is it where you live?
- Melt all the ice at the poles (by whatever means you can). What happens to the coastlines near where you live? Over the rest of your continent? Which country loses the most land area?
- Keep CO2 levels constant at the level they were at in 1900, and run a century-long simulation. What happens to temperatures? Now try keeping aerosols constant at 1900 levels instead. What happens? How do these two results compare to what actually happened?
Now compare your answers with what the rest of the class got. And discuss what we’ve learned. [And finally, for the advanced students – look at the model software code, and point to the bits that are responsible for each outcome… Okay, I’m just kidding about that bit. We’d need literate code for that].
Okay, this seems like a worthwhile project. We’d need to wrap a desktop-runnable model in a simple user interface with the appropriate switches and dials. But is there any model out there that would come anywhere close to being useable in a classroom situation for this kind of exercise?
(feel free to suggest more experiments in the comments…)