Clarity in Climate Modeling
Computational models are splendid tools for understanding the intricacies of climate. But can we understand the intricacies of the models?
No computer simulations have ever had broader consequences for human life than the current generation of climate models. The models tell us that rising levels of atmospheric carbon dioxide and other greenhouse gases can trigger abrupt shifts in the planet’s climate; to avert those changes or mitigate their effects, the entire human population is urged to make fundamental economic and technological adjustments. In particular, we may have to forgo exploiting most of the world’s remaining reserves of fossil fuels. It’s not every day that the output of a computer program leads to a call for seven billion people to change their behavior.
I hasten to add that computer modeling is not the only line of evidence connecting human activities with global warming. We have observations of changes already under way, and there are records of past climate fluctuations showing a close correlation between temperature and atmospheric CO2. Still, the models provide a crucial link. They offer the only practical way to carry out controlled climate experiments—to change the inputs to the system and see the effect on the outputs. Moreover, the models can reveal causation rather than mere correlation, and they promise insight into the underlying mechanisms of climate change.
As someone interested in both climate and computation—and as a lifelong resident of planet Earth—I have been trying to gain a deeper understanding of how climate models are made. I have been dipping into the primary literature, working through textbooks, sampling the criticisms of global-warming skeptics, browsing the source code of climate models, building a tiny model of my own, and struggling to get a couple of larger models running on my computers. The experience has been rewarding, although the learning curve is steeper than it needs to be. So I have also been thinking about how the basics of climate modeling could be made more widely accessible.