The 2021 Nobel Prize in Physics

Here’s this morning’s announcement of The 2021 Nobel Prize in Physics from the Royal Swedish Academy of Sciences in Stockholm in full:

The associated press release puts it this way:

The Royal Swedish Academy of Sciences has decided to award the Nobel Prize in Physics 2021

“for groundbreaking contributions to our understanding of complex physical systems”

with one half jointly to Syukuro Manabe, Princeton University, USA and Klaus Hasselmann, Max Planck Institute for Meteorology, Hamburg, Germany

“for the physical modelling of Earth’s climate, quantifying variability and reliably predicting global warming”

and the other half to Giorgio Parisi, Sapienza University of Rome, Italy

“for the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales”

The press release explains:

Complex systems are characterised by randomness and disorder and are difficult to understand. This year’s Prize recognises new methods for describing them and predicting their long-term behaviour.

One complex system of vital importance to humankind is Earth’s climate. Syukuro Manabe demonstrated how increased levels of carbon dioxide in the atmosphere lead to increased temperatures at the surface of the Earth. In the 1960s, he led the development of physical models of the Earth’s climate and was the first person to explore the interaction between radiation balance and the vertical transport of air masses. His work laid the foundation for the development of current climate models.

About ten years later, Klaus Hasselmann created a model that links together weather and climate, thus answering the question of why climate models can be reliable despite weather being changeable and chaotic. He also developed methods for identifying specific signals, fingerprints, that both natural phenomena and human activities imprint in he climate. His methods have been used to prove that the increased temperature in the atmosphere is due to human emissions of carbon dioxide.

Around 1980, Giorgio Parisi discovered hidden patterns in disordered complex materials. His discoveries are among the most important contributions to the theory of complex systems. They make it possible to understand and describe many different and apparently entirely random materials and phenomena, not only in physics but also in other, very different areas, such as mathematics, biology, neuroscience and machine learning.

“The discoveries being recognised this year demonstrate that our knowledge about the climate rests on a solid scientific foundation, based on a rigorous analysis of observations. This year’s Laureates have all contributed to us gaining deeper insight into the properties and evolution of complex physical systems,” says Thors Hans Hansson, chair of the Nobel Committee for Physics.

Here is Syukuro Manabe in 1988 explaining his prediction that the Arctic would warm faster than lower latitudes, thanks to the physics of sea ice:

Here is Professor John Mitchell’s explanation of the significance of Syukuro Manabe’s work for Carbon Brief:

Why is the 1967 paper so important? Manabe and Wetherald were the first to include all the main physical processes relevant to the problem, using a model that was no more complicated than necessary to achieve this. This led to much more realistic simulations and enabled the results to be explained in terms of processes which could be observed in the real world. Indeed, the paper is exemplary in the clarity and simplicity of the explanation of the results.

and here is a copy of Manabe and Wetherald’s ground breaking 1967 paper:

https://doi.org/10.1175/1520-0469(1967)024%3C0241:TEOTAW%3E2.0.CO;2

Radiative convective equilibrium of the atmosphere with a given distribution of relative humidity is computed as the asymptotic state of an initial value problem.

The results show that it takes almost twice as long to reach the state of radiative convective equilibrium for the atmosphere with a given distribution of relative humidity than for the atmosphere with a given distribution of absolute humidity.

Also, the surface equilibrium temperature of the former is almost twice as sensitive to change of various factors such as solar constant, CO2 content, O3 content, and cloudiness, than that of the latter, due to the adjustment of water vapor content to the temperature variation of the atmosphere.

According to our estimate, a doubling of the CO2 content in the atmosphere has the effect of raising the temperature of the atmosphere (whose relative humidity is fixed) by about 2C. Our model does not have the extreme sensitivity of atmospheric temperature to changes of CO2 content which was adduced by Möller.

Should you wish to experiment with a medium complexity climate model of your own on a Raspberry Pi or similar modern computing device here are instructions on how to do so:

4 thoughts on “The 2021 Nobel Prize in Physics

  1. An article in National Geographic about the 2021 Nobel Prize in Physics:

    How climate models got so accurate they earned a Nobel Prize

    Climate modelers are having a moment.

    Last month, Time Magazine listed two of them — Friederike Otto and Geert Jan van Oldenborg of the World Weather Attribution Project — among the 100 Most Influential People of 2021. Two weeks ago, Katharine Hayhoe of Texas Tech University was a guest on the popular CBS talk show Jimmy Kimmel Live! And on Tuesday, pioneering climate modelers Syukuro Manabe and Klaus Hasselman shared the Nobel Prize for Physics with theoretical physicist Giorgio Parisi—a recognition, said Thors Hans Hansson, chair of the Nobel Committee for Physics, that “our knowledge about the climate rests on a solid scientific foundation, based on a rigorous analysis of observations.”

    Here’s Katharine Hayhoe’s recent chat with Jimmy Kimmel:

    According to National Geographic once more:

    In the realm of climate modeling, “What hasn’t changed over the years is the overall assessment of just how much the world would warm as we increased CO2,” says Hayhoe, who is also Chief Scientist for the Nature Conservancy and author of Saving Us: A Climate Scientist’s Case for Hope and Healing in a Divided World. “What has changed is our understanding at smaller and smaller spatial and temporal scales. Our understanding of feedbacks in the climate system, our understanding of, for example, just how sensitive the Arctic really is.”

    As that understanding has increased, she says, so it has allowed the development of what she refers to as “the cutting edge of climate science today” — individual event attribution, the specialty for which Otto and van Oldenberg were recognized in Time, which for the first time is able to draw strong links between climate change and specific weather events, such as heat waves in the western United States or the amount of rain deposited by Hurricane Harvey.

    “We couldn’t do that without models,” Hayhoe says, “because we need the models to simulate a world without people. And we have to compare an Earth with no people to the Earth we’re living on with humans and carbon emissions. And when we compare those two Earths, we can see how human-induced climate change has altered the duration, the intensity, and even the damages associated with a specific event.”

    In Hayhoe’s case, the actual act of modeling involves “looking at thousands of lines of code, and it’s so intense that I often do it at night, when people aren’t emailing and the lights are off and I can focus on this bright screen in a dark room. Then I blink and it’s suddenly four-thirty in the morning.”

    Much of the work, she says, requires trying to find things that are wrong in the models, to ensure they reflect reality. “If it doesn’t quite match up, we have to look harder because there’s something we didn’t quite understand.”

  2. A Twitter thread from Chris Colose on the significance of Syukuro Manabe’s work:

    1. An article on Suki Manabe’s Nobel Prize by Piers Foster for The Conversation:

      The most influential climate science paper of all time

      After the second world war, many of Japan’s smartest scientists found jobs in North American laboratories. Syukuro (Suki) Manabe, a 27-year-old physicist, was part of this brain drain. He was working on weather forecasting but left Japan in 1958 to join a new research project by the US Weather Service to develop a numerical model that could be used to study the climate.

      Working alongside Joseph Smagorinsky, the Geophysical Fluid Dynamics Laboratory’s visionary first director, Manabe led a team of computer programmers to add missing physics to the lab’s weather model. Even the best computers in the world at the time were far less powerful than today’s mobile phones. So to get the model to work, Manabe needed to make the physics as simple as possible. This meant making a range of coding approximations to quantify how the air exchanged heat and water vapour with the land, ocean and ice.

  3. A deep dive into the work of Manabe and Hasselmann at RealClimate:

    A Nobel pursuit

    But the building of climate models and their application is broader than can be recognized like this. There are no prizes for the people that actually wrote the code for the models – people like Gary Russell or Ernst Maier-Reimer (nicely eulogized by Hasselmann), the specialists who designed the parameterizations, or the teams that developed the inputs and processed the outputs or the technicians that kept the old supercomputers running. In recent papers documenting model development, it’s not unusual to have dozens of authors – not the level of the CERN collaborations, but significantly beyond the Nobel limit. The huge advances in understanding we’ve seen since the 1970s have been the work of thousands of smart and dedicated people all around the world, only a few of which will ever be recognized as widely as this. We should always remember this while we celebrate the winners.

    Finally, while it is many scientists’ dream to win a Nobel Prize, Hasselmann’s statement that he would rather have “no global warming and no Nobel Prize” captures the ambiguity that many of us feel in successfully predicting events and trends that we don’t want to come true.

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