Climate models are some of the most complex pieces of software ever written, able to simulate a vast number of different parts of the overall system, such as the atmosphere or ocean. Many have been developed by hundreds of scientists over decades and are constantly being added to and refined. They can run to over a million lines of computer code—tens of thousands of printed pages.
Climate models are some of the most complex pieces of software ever written, able to simulate a vast number of different parts of the overall system, such as the atmosphere or ocean. Many have been developed by hundreds of scientists over decades and are constantly being added to and refined. They can run to over a million lines of computer code—tens of thousands of printed pages.
Not surprisingly, these models are expensive. The simulations take time, frequently several months, and the supercomputers on which the models are run consume a lot of energy. But a new algorithm I have developed promises to make many of these climate model simulations ten times faster, and could ultimately be an important tool in the fight against climate change.
One reason climate modeling takes so long is that some of the processes being simulated are intrinsically slow. The ocean is a good example. It takes a few thousand years for water to circulate from the surface to the deep ocean and back (by contrast, the atmosphere has a « mixing time » of weeks).
Ever since the first climate models were developed in the 1970s, scientists realized this was going to be a problem. To use a model to simulate climate change, it has to be started from conditions representative of before industrialization led to the release of greenhouse gases into the atmosphere.
To produce such a stable equilibrium, scientists « spin-up » their model by essentially letting it run until it stops changing (the system is so complex that, as in the real world, some fluctuations will always be present).
An initial condition with minimal « drift » is essential to accurately simulate the effects of human-made factors on the climate. But thanks to the ocean and other sluggish components this can take several months even on large supercomputers. No wonder climate scientists have called this bottleneck one of the « grand challenges » of their field.
