Nobel Prize 2021

Study of Hidden Patterns in Climate and Chaotic Physical Systems Wins the 2021 Physics Nobel Prize

Abstract

Every year, in the month of December, Nobel Prizes are awarded to ‘those who, during the preceding year, have conferred the greatest benefit to humankind’ in the areas of Physics, Chemistry, Physiology/Medicine, Literature, Peace and Economics, in keeping with Alfred Nobel’s will. This article will discuss the 2021 Physics Nobel prize and the work of the laureates. The Nobel prize in Physics has been awarded 115 times to 219 Nobel prize laureates from 1901 to 2021, out of which four were women. Only one laureate has won the Nobel prize in Physics twice, and that is John Bardeen.[1]

Triptych of portraits of Klaus Hasselmann, Giorgio Parisi and Syukuro Manabe

Figure 1: 2021 Physics Nobel laureates (left to right): Klaus Hasselmann, Giorgio Parisi and Syukuro Manabe. [J.J. Guillen/EPA/Shutterstock; Tania/Contrasto/Eyevine; Markus Marcetic, the Royal Swedish Academy of Sciences]

Three Laureates will share the Nobel Prize in Physics this year for their research into complex physical phenomena and climate change. Syukuro Manabe and Klaus Hasselmann have been recognised for establishing the groundwork for the understanding of our planet’s climate and how it is impacted by humans by developing climate change models have that accurately forecasted how rising carbon dioxide emission levels affect the climate. Giorgio Parisi shares the prize for his pioneering studies on complex disordered physical systems.

According to the Nobel Prize committee —

‘The Nobel Prize in Physics 2021 was awarded “for ground-breaking contributions to our understanding of complex systems” with one half jointly to Syukuro Manabe and Klaus Hasselmann “for the physical modelling of Earth’s climate, quantifying variability and reliably predicting global warming” and the other half to Giorgio Parisi “for the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales.”’[2]

What is Manabe’s Climate Model About?

Svante Arrhenius, the 1903 Chemistry Nobel Laureate had once asked, ‘Is the mean temperature of the ground in any way influenced by the presence of the heat-absorbing gases in the atmosphere?’ and went on to become one of the first scientists to investigate the effect of carbon dioxide on Earth’s climate.[3] Arrhenius understood that the outgoing radiation is proportional to the radiant body’s absolute temperature to the power of four (T⁴), and this realisation was one among the fundamental concepts behind global warming.

In the 1960s, Syukuro Manabe, a climatologist at Princeton University, along with Richard T. Wetherland, built upon Arrhenius’ idea and started developing physical models to explore the interaction between the vertical flow of air (due to convection) and the radiation balance1. As the climate is a nonlinear system, where the effect/feedback is not directly proportional to its cause, climate models2 that take into account the complex interplay between various variables in a system are developed.[4] Through his climate models, Manabe wanted to study how the increase in the levels of different gases in the atmosphere affect global temperatures.

In his models, Manabe took into account a vertical column of air stretching from the ground to the stratosphere (40 kilometres) and after countless hours of computing for model-testing, he found that while oxygen and nitrogen did not have a profound effect on the surface temperature, carbon dioxide, water vapour and other greenhouse gases had a powerful influence; he found that when the carbon dioxide levels were doubled, the global temperatures would rise by 2.3°C.[4]

Climate modelling: from Manabe and Wetherald to supercomputer JASMIN | by  UK Research and Innovation | Our Changing Climate | Oct, 2021 | Medium

Figure 2: Manabe’s Climate Model. [Johan Jarnestad/The Royal Swedish Academy of Sciences]

Greenhouse gases such as carbon dioxide, methane and water vapour strongly absorb and reemit the infrared radiation coming from Earth’s surface, and this causes warming. In his climate model, Manabe considered the fact that when hot air rises, it carries more water vapour (which is a strong greenhouse gas) along with it. When it reaches further up, it condenses to form cloud drops and release the latent heat stored in the water vapour.[4]

Figure 3: Light absorption by various gases in the atmosphere. [J.N. Howard (1959); R.M. Goody and G.D. Robinson (1951)]

Manabe’s model had confirmed that the heating of the atmosphere is due to the increase in the levels of carbon dioxide (he focused primarily on carbon dioxide), and not due to increased solar radiation. If that were the case, the entire atmosphere would have heated up and not just the lower part. Closer to the ground, temperatures are higher, and as distance from the ground increases, temperatures become colder. His findings have been pivotal in the latest climate models that have been used in IPCC reports as well.[5]

The Link Between Weather and Climate

About a decade after Manabe and Wetherland, Klaus Hasselmann, a German oceanographer and climate modeller, created models that linked weather, which is short-term, and climate, which is a long-term phenomenon; he incorporated the weather patterns into his climate model. When it comes to weather, it is very difficult to precisely predict what the weather at a particular place and time would be, given that weather is very chaotic. The chaotic weather patterns are often referred to as noise. Therefore, it is not possible to produce long-term weather forecasts. A crucial question that arises is how can climate models of 100 years into the future be created when the weather is a chaotic system? Hasselmann, inspired by Einstein’s theory of Brownian motion, showed that weather impacts the climate the same way how the random movement of air molecules at a microscopic level affects the random movement of dust particles at a macroscopic level.[6] He explained that a rapidly changing climate can slow down the variations in oceans.

After this, he went on to analyse the human impact on climate. He called the unique signals of global warming (such as those left by levels of greenhouse gases or volcanic particles) fingerprints. These fingerprints can be studied to trace the impact of humans on climate. He formulated optimal detection techniques for identifying the fingerprints, and found that the signals are the strongest where the noise is the weakest.[6] Hasselmann set the basis for the fact that climate change today can be traced back to human-made carbon dioxide emissions.

Figure 4: Use of models in detection & attribution of climate change. [Hegert & Zwiers/WIREs Climate Change]

Spin Glasses

While Hasselmann and Manabe were working on climate models, Giorgio Parisi of Sapienza Università di Roma, an Italian theoretical physicist, was enthralled with a complex physical system known as a spin glass. In layman terms, a spin glass is a complex disordered magnetic system. A simple example is an alloy of non-magnetic metal and some magnetic atoms mixed with it. The orientation of the atoms’ magnetic moment in relation to the electric field determines the system’s energy. If the magnetic moment is aligned with the field, the energy is lower, and if it is opposite to the field, the energy is larger.[7]

Spin glasses have captivated Parisi and many other physicists due to a special feature it possesses called frustration. Consider a simple triangular spin glass with three spins at the corners. Adjacent spins are more likely to point in the opposite direction. However, the three spins cannot all fulfil that limitation simultaneously as they flip back and forth seeking to find a stable configuration. This kind of system is called a frustrated system.[4]

Figure 5: A frustrated system [Johan Jarnestad/The Royal Swedish Academy of Sciences]

Based on this phenomenon, Parisi has devised the Replica Symmetry Breaking (RSB) theory. The replica technique, which is a mathematical technique based on the idea of handling several copies of the system at the same time, was used by Parisi to solve the orientation problem in a frustrated system. Discovering a means to actually solve the maths of the replicas, which included grappling with a ‘zero-dimensional’ geometry, was his greatest triumph.[7] Parisi showed that even chaotic systems such as the spin glass can behave in an orderly fashion. Studying complex physical systems has a variety of applications ranging from machine learning and AI to biology and mathematics.

Discussion & Conclusion

The development of change models to better understand the origins of global warming and how humans influence climate change, as well as the study of chaotic systems, were major breakthroughs, which in combination allowed scientists to predict how the chaotic behaviour of natural physical systems like oceans and the atmosphere evolve over time. Manabe was one of the first scientists to show the global climate over time can be predicted with the levels of carbon dioxide in the atmosphere. Hasselmann bridged the gap between climate and weather and traced the human impact on global climate through fingerprints. Parisi’s theories provided the framework for accurately depicting chaotic climate systems. In recent times, more advanced and sophisticated climate models have been developed that have given climate scientists a clear view of what would happen if the levels of greenhouse gases in the atmosphere continue to soar, and this year’s physics laureates laid the foundation for this.

Climate change is one of the most pressing issues in the 21st century. Hasselmann, during his Nobel prize telephone interview, said that action against climate change is urgently needed. He further added, ‘There are many things we can do to prevent climate change, and it is a whole question of whether people will realise that something which will happen in 20 or 30 years is something which you have to respond to now, and that is the main problem with climate change. We have been warning about climate change for 50 years or so, and it is just that people are not willing to accept the fact that they have to react now to something that will happen in a few years, and this is something we have been sort of battling against now for many years as climate scientists.’[8] It is now on the shoulders of this generation to solve the problem that Manabe, Parisi and Hasselmann helped the world understand better, and hopefully in the coming years, we can successfully meet the ‘below 1.5°C’ benchmark.

References

[1] All Nobel Prizes in Physics. NobelPrize.org. Nobel Prize Outreach AB 2021. Sat. 29 Oct. 2021, https://www.nobelprize.org/prizes/lists/all-nobel-prizes-in-physics.

[2] The Nobel Prize in Physics 2021. NobelPrize.org. Nobel Prize Outreach AB 2021. Sat. 16 Oct 2021, https://www.nobelprize.org/prizes/physics/2021/summary/.

[3] “Arrhenius.” Le Moyne College, https://web.lemoyne.edu/%7Egiunta/arrhenius.html. Accessed 29 Oct. 2021.

[4] Popular Information. NobelPrize.org. Nobel Prize Outreach AB 2021. Sat. 29 Oct. 2021. https://www.nobelprize.org/prizes/physics/2021/popular-information/.

[5] Nakamura, Kate. “Climate Scientists Win 2021 Nobel Prize in Physics for Linking Global Warming and Human Activity.” Global Citizen, 5 Oct. 2021, www.globalcitizen.org/en/content/nobel-prize-in-physics-2021-climate-scientists.

[6] Wolchover, Natalie. “Work on Earth’s Climate and Other Complex Systems Earns Nobel Prize in Physics.” Quanta Magazine, 6 Oct. 2021, www.quantamagazine.org/pioneering-climate-modelers-earn-nobel-prize-in-physics-20211005.

[7] Catanzaro, Michele. “Giorgio Parisi Wins the 2021 Nobel Prize in Physics.” Nature, Nature Editorial, 5 Oct. 2021, www.nature.com/articles/d43978-021-00122-6?error=cookies_not_supported&code=5380b77f-e0c7-4f07-8773-c3334321feb9.

Footnotes

1 The radiation balance or the net radiation is the algebraic sum of the incoming and outgoing radiation.

2 A climate model is a computer programme based on a set of mathematical equations that describe the physical laws that govern our planet’s climate. They are designed to simulate Earth’s climate so as to understand and predict its behaviour.

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