162 - Tim Palmer: Chaos Theory, Probabilistic Forecasting, and Climate Change
Nov 3, 2023
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Tim Palmer, Royal Society Research Professor in Climate Physics at the University of Oxford, discusses topics such as black holes and the holographic principle, quantum mechanics, meteorology and probabilistic forecasting, chaos theory and consciousness, and the problem of climate change in this episode.
Ensemble forecasting with probabilistic outlook improves disaster preparedness and aids proactive decision-making.
Weather predictions rely on perturbations and stochastic noise to account for uncertainties and improve reliability.
Exploring the potential benefits of embracing noise in complex systems challenges traditional focus on precise computations.
Deep dives
The Importance of Noise in Weather Forecasting
The introduction of noise into weather and climate models has improved their reliability by explicitly representing uncertainty. Weather systems that are chaotic and sensitive require a recognition of the inherent uncertainty in predictions due to limited knowledge of initial conditions and equations governing system evolution. Ensemble forecasting, where multiple forecasts with slightly varied initial conditions are run, provides a probabilistic outlook and allows for estimation of uncertainties. This approach has revolutionized disaster preparedness, enabling humanitarian agencies to make proactive decisions about sending aid ahead of extreme weather events.
Understanding Chaos and Instability in Weather Systems
Weather systems exhibit chaos and instability due to nonlinearity and the occurrence of instabilities like baroclinic and convective instabilities. The coupling of large and small-scale circulations within the atmosphere leads to complex behavior, making predictions challenging. Unstable situations and their characteristics are difficult to define precisely, but retrospective analysis can reveal the impact of nonlinear behavior and interactions between different components of the weather system. Perturbations to initial conditions and stochastic noise introduced into computer models account for uncertainties in knowledge and contribute to ensemble forecasting, improving the reliability of weather predictions.
Exploring the Role of Noise in Computing and the Brain
The exploration of noise in computer models and its link to uncertainty led to a broader examination of the significance of noise in hardware systems. The brain, a noisy and energy-efficient system, uses noise effectively for cognitive processes such as creativity. Introducing stochastic noise into computer models has shown potential benefits for energy efficiency and computational capabilities. This perspective challenges the traditional focus on precise computations in digital computers and explores the potential advantages of embracing noise in complex systems.
Connections Between Noise, Cognitive Modes, and Scientific Discoveries
The concept of cognitive modes, including focused and multi-tasking states (system one and system two), provides insights into the role of noise in cognitive processes. Scientific discoveries often arise during moments of relaxed, multi-tasking cognition, when ideas seem to emerge unexpectedly. This phenomenon suggests a potential connection between the susceptibility to noise and unstructured thinking modes. Exploring the interplay between noise, cognitive modes, and scientific breakthroughs could offer valuable insights into the nature of innovation and creative thinking.
Understanding the Brain's Creativity and the Role of Chaos
The speaker discusses how creativity in the brain arises from two different modes of thinking, known as system one and system two. System one is associated with eureka moments and is susceptible to noise, while system two is deterministic and verifies the quality of ideas. The speaker argues that AI research should explore the potential of generating random ideas and developing algorithms to determine their usefulness, as the human brain does. He also discusses the link between chaos and noise in the brain and suggests that noise can emulate the unresolved small-scale details in representing the vast and complex world.
Determinism, Free Will, and Climate Change
The conversation touches on determinism and its relationship to free will, highlighting the moral responsibility conundrum. The speaker believes that the brain's cognitive model represents dominant structures explicitly and uses noise to depict unresolved details. While acknowledging the practical importance of noise, he considers it unimportant at a fundamental level due to its lack of determinism. The discussion then shifts to climate change, emphasizing the amplifying role of clouds and their impact on the severity of climate change outcomes. The speaker argues for taking action to mitigate the risks of climate change, weighing various options, including renewable energy, nuclear power, and carbon capture, while cautioning against reliance on wind and solar energy alone.
Tim Palmer is Royal Society Research Professor in Climate Physics at the University of Oxford, where he is a Senior Fellow at the Oxford Martin Institute and a Professorial Fellow at Jesus College. Tim works on the predictability and dynamics of weather and climate, including extreme events, and is well known within the field for developing probabilistic ensemble forecasting techniques. In this episode, Robinson and Tim discuss his recent book, The Primacy of Doubt: From Quantum Physics to Climate Change, How the Science of Uncertainty Can Help Us Understand Our Chaotic World (2022). More particularly, they talk about black holes and the holographic principle, the foundations of quantum mechanics, meteorology and probabilistic forecasting, chaos theory and consciousness, and the problem of climate change.
The Primacy of Doubt: https://a.co/d/dL8JfTn
OUTLINE
00:00 In This Episode…
00:37 Introduction
02:37 From Physics to Meteorology
13:17 Black Holes and the Holographic Principle
35:09 What Is the Butterfly Effect?
43:31 Why Is Weather Chaotic and What Can We Do About It?
01:09:34 Can Principles of Meteorology Be Applied to the Problems of Consciousness and Free Will?
Robinson Erhardt researches symbolic logic and the foundations of mathematics at Stanford University. Join him in conversations with philosophers, scientists, weightlifters, artists, and everyone in-between.
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