The 2021 Nobel Prize in Physics was awarded to Syukuro Manabe, Klaus Hasselmann and Giorgio Parisi “for their revolutionary contributions to our understanding of complex physical systems”.
Every year on the morning of the first Tuesday in October, it is customary for one of the physics writers of the Nature towers to suddenly remember that the Nobel Prize is about to be announced. In turn, they send out a message reminding their editorial colleagues, so that they can put aside any idea of doing any work that morning. And then, inevitably, the question arises: “So who will win this time?
Syukuro Manabe, Klaus Hasselmann and Giorgio Parisi.
Credit: © Nobel Media AB 2021 / Niklas Elmehed.
And of course, we don’t have a clue. There are, of course, preferences expressed and bets made – one or two of us will also claim that we are not fans of the idea of giving so few people so much credit at all – but every time someone does. one says “what about complex systems?” “, The result is only one more question:” but who would they give this to?
By awarding half of the 2021 prize to Syukuro Manabe and Klaus Hasselmann “for the physical modeling of the earth’s climate, the quantification of variability and reliable forecasting of global warming” and the other half to Giorgio Parisi “for the discovery of the interaction of disorder and fluctuations in physical systems from atomic scale to planetary scale, ”the Nobel committee gave a convincing answer.
The fluctuations and the subtle mechanisms by which ordered phenomena emerge within disordered and chaotic systems play an essential and much underestimated role in determining the properties and dynamics that manifest at all length scales, materials such as glass to climate.
An important skill for a scientist is to identify a correct minimal model that economically captures the phenomena essential to the study. One example is Syukuro Manabe’s work in the 1960s exploring the interaction between the radiative balance and the vertical transport of air masses in the atmosphere: he first modeled this as a one-dimensional column, but in doing so , he captured how increased levels of carbon dioxide carbon in the atmosphere cause increased temperatures on the Earth’s surface.
All models have their limitations and pitfalls, and understanding them is essential for making a meaningful connection to empirical observation. For a system as complex and chaotic as the atmosphere, in which the weather can be notoriously unpredictable on a timescale in days, it is especially important to understand why climate models can be considered reliable on a timescale in months. and in years.
Klaus Hasselmann’s work has provided in-depth information in this regard: by drawing an analogy with Brownian motion, he formulated a stochastic model which gives an idea of the variability of the climate and avoids the pitfalls of misinterpretation. statistical quantities such as variance and mean in observational data. As a result, he was able to provide a framework for separating signal (large-scale climate dynamics) from noise (short-range weather changes), and further develop methods to identify fingerprints from natural effects. and human-induced in this data. These approaches have been used to prove that the increase in temperature in the atmosphere is due to human emissions of carbon dioxide.
Stochastic models of climate are built on fundamental concepts of hydrodynamics and share a deep connection with statistical mechanics. In a fundamental sense, both disciplines are ultimately grappling with the exploration of extremely complex energetic landscapes that result from nonlinear effects due to disorder and fluctuations on a length scale, making their consequences manifest at many scales. bigger. And what better example of this phenomenon than glass, a material that ages on a geological time scale due to the subtle effects of impurities and disorder on the atomic scale.
Giorgio Parisi’s work on spin glasses, in particular the replica symmetry breaking solution he devised to calculate the partition function of these magnetic analogues of glass, is perhaps his most famous contribution. But over the course of a career spanning decades, his knowledge in various fields of mathematics, neuroscience and machine learning testifies to the power of his theoretical approach and is among the most important contributions to the theory of complex systems.
There is a deep humility which is the basis of the scientific approach adopted by scientists such as Manabe, Hasselmann and Parisi, which forces one to accept uncertainty, variation and even doubt. Contrary to the perception that more is better, to understand a phenomenon it is not necessary to construct a faithful representation of the entire physical system including as much fine detail as possible. But it is essential to identify the fundamental ingredients that really matter in understanding the problem and to appreciate their (sometimes unintended) effects on very different time scales. When it comes to climate change, we have to hope that we will also find the collective humility to do something.
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The power of fluctuations.
Nat. Phys. 17, 1185 (2021). https://doi.org/10.1038/s41567-021-01420-y