Enlarge / The output of a modern climate model allows us to detect trends despite the chaotic nature of the underlying system. (credit: NOAA)
Complex behavior is all around us. Think of something like the economy. It has many components, each with its own set of rules and all of them interacting in complicated ways. Trying to follow what’s going on from the ground up is nearly impossible. Yet some reasonably consistent behaviors emerge from that complexity, allowing us to understand some general rules for it.
This mix of complexity and emergent behavior shows up in many other systems involving aggregate human behavior, as well as in areas of physics, chemistry, and biology. This year’s Nobel in Physics is split evenly between two aspects of studying these systems. Half of the award goes to Giorgio Parisi, who helped find methods for understanding complex systems that can be applied more generally. And the other half is split between two climate modelers, Syukuro Manabe and Klaus Hasselmann, who helped developed systems that we now use to understand how the climate’s behavior emerges from the complicated interaction of its components and influences—including the growing influence of greenhouse gases.
Complex systems and emergent behavior
Giorgio Parisi’s work has its roots in the earliest days of statistical mechanics, most notably the work of James Clerk Maxwell (of Maxwell’s Demon fame) and Ludwig Boltzmann, who famously applied a statistical approach to the second law of thermodynamics (entropy). Finally, physicists had a mathematical tool capable of describing how properties on the macroscale—such as the temperature and pressure of a gas—emerge from the random, disordered movements of particles on the microscale. Parisi’s work uncovered the hidden rules that govern these kinds of complex disordered systems and their emergent properties.
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