Climate Science seminars

A fundamental problem in neuroscience is understanding how the properties of individual neurons and synapses contribute to neuronal circuit dynamics and behavior. In recent years we have done both computational and experimental studies that demonstrate that the same physiological output can arise from multiple, degenerate solutions, and that individual animals with similar behavior can nonetheless have quite different sets of underlying circuit parameters. Most recently, we have been studying the resilience of individual animals to perturbations such as temperature and high potassium concentrations. This has revealed that extreme environmental experiences can produce long-term changes in circuit performance that can be hidden, or “cryptic” unless the animals are again challenged or perturbed. Our present experimental and computational work is designed to understand differential resilience in natural, wild-caught animals in response to climate change, and shows long-lasting influences of the animals’ temperature history. VVTNS Fourth Season Closing Lecture. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2024-06-26. Recording duration: 00:49:33.

Julie Robinson explores what maintaining human life aboard the International Space Station teaches us about Earth. Space habitation requires engineered substitutes for the air, water, surfaces and living systems that our planet supplies. Long-duration occupation of the station has produced lessons about building and operating these life-support systems. The station is also an observing platform for the Earth system below. Robinson connects the engineering lessons of living in space with Earth observations, climate change, and ways that spaceflight can help communities understand environmental change and strengthen their resilience.

The three lectures examine how physical theory can make sense of complex systems with fluctuations and many interacting components. Syukuro Manabe describes the construction of climate models that connect atmospheric radiation, heat transport and carbon dioxide to changes in surface temperature. Klaus Hasselmann addresses the relationship between short-term weather variability and long-term climate, including methods for distinguishing human influence from natural variation. Giorgio Parisi examines disordered systems and the coexistence of multiple equilibria, with spin glasses providing a central setting for understanding apparently irregular collective behaviour. The programme preserves both parts of the prize: quantitative climate science and the statistical physics of disorder, rather than treating either as a substitute for the other.

Climate change is one of our generation's greatest challenges, with increasingly severe consequences on global ecosystems and populations. Machine Learning has the potential to address many important challenges in climate change, from both mitigation (reducing its extent) and adaptation (preparing for unavoidable consequences) aspects. To present the extent of these opportunities, I will describe some of the projects that I am involved in, spanning from generative model to computer vision and natural language processing. There are many opportunities for fundamental innovation in this field, advancing the state-of-the-art in Machine Learning while ensuring that this fundamental progress translates into positive real-world impact.

Multi-agent reinforcement learning (MARL) has recently shown great promise as an approach to networked system control. Arguably, one of the most difficult and important tasks for which large scale networked system control is applicable is common-pool resource (CPR) management. Crucial CPRs include arable land, fresh water, wetlands, wildlife, fish stock, forests and the atmosphere, of which proper management is related to some of society’s greatest challenges such as food security, inequality and climate change. This talk will consist of three parts. In the first, we will briefly look at climate change and how it poses a significant threat to life on our planet. In the second, we will consider the potential of multi-agent systems for climate change mitigation and adaptation. And finally, in the third, we will discuss recent research from InstaDeep into better understanding the behaviour of networked MARL systems used for CPR management. More specifically, we will see how the tools from empirical game-theoretic analysis may be harnessed to analyse the differences in networked MARL systems. The results give new insights into the consequences associated with certain design choices and provide an additional dimension of comparison between systems beyond efficiency, robustness, scalability and mean control performance.

Amitav Ghosh considers why societies have struggled to imagine and respond to global warming. He argues that fiction has helped shape the priorities and consumption patterns of the modern world while often failing to confront the realities of climate change. The lecture connects stories of ordinary people and imperial histories with the cultural conditions of the climate crisis. Ghosh questions approaches that place responsibility only on individual conscience, arguing that the scale of the problem demands a collective response. His account asks how literature, public imagination and historical understanding can contribute to that response.