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Why models of climate change matter: Gavin Schmidt at TED2014

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Gavin Schmidt. Photo: James Duncan Davidson

Gavin Schmidt is the author of Climate Change: Picturing the Science, described by Popular Mechanics as “the first book anyone seeking a layman’s understanding of the science of global warming should read.” He’s here to talk about the environment and the models we’ve built to understand this astonishingly complex issue. Because, for one thing, you can’t just take one element of the climate at a time. As he puts it, “I can’t use the normal products of reductionism to get something to study in a laboratory” in order to understand it. Where the environment is concerned: “It’s the whole or it’s nothing.”

To try and put this into some context, Schmidt explains that climate patterns span a range of 14 orders of magnitude across both space and time. That is, the climate is embedded in small particles that seed clouds — and it stretches right up to the mass of the planet itself. Similarly, it spans across tiny amounts of time right through to millennia. Climate models in the 1990s could only consider three of these orders of magnitude; in the 2010s we’re working with four of them. That’s not giving us the entire big picture — but it does provide us with individual jigsaw pieces we can put together to try to understand the whole.

So what does a climate model actually look like? Schmidt has some to show, including an old one consisting of a punch card and a single line of Fortran code. These days, creating a model that might, say, calculate how ice grows, melts or changes shape now takes at least one million lines of code. Schmidt shows us a representation of atmospheric column water vapor. It shows the emergent properties developing from small scale processes. “No code tells the model to do that wiggle in the Southern Ocean,” he says, referring to the animation onscreen. “No code says to have those two tropical cyclones.”

What happens to these models when, as he puts it, we “kick the system?” Well, there are certainly ways to do that, and Schmidt lists just some of them. “Changes in the solar cycles change climate. Big volcanoes go off and change climate. Changes in biomass burning. The ozone hole changed climate. Deforestation changes climate. Of course, greenhouse gases change the system…” The benefits of all of this? “Each of these different kicks provides us with a target to evaluate whether we understand system.” In this instance, looking at the individual parts allows a tantalizing glimpse at the whole.

The thing about models, however, is that they are always approximations. They can be incredibly useful, of course, but essentially they are always wrong. So while Schmidt is careful to list many of what he describes as “skillful models,” such as those calculating orbital changes over the last 6,000 years or tracking the ice sheets of 20,000 years ago, he also reminds us that they are still just a start. He quotes Thomas Knutson and Robert Tuleya, who pointed out that we rely on models to think about the future because, unfortunately, “observations of the future are not available at this time.”

“The future is unknown. There are choices,” Schmidt concludes. We have options, we have decisions to make, and while not all of these can be decided simply by looking at models, those models provide a useful and important basis for action. In conclusion, he quotes Sherwood Rowland, who won the Nobel Prize for chemistry in 1995: “What is the use of having developed a science well enough to make predictions if, in the end, all we’re willing to do is stand around and wait for them to come true?” That, Schmidt reminds us, is up to us.