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Forecasting Monsoon Onset and Withdrawal in the Face of Climate Change
Elena SurovyatkinaICTS:30266Lecture - Relativity, PHYS 604
Ghazal Geshnizjani Perimeter Institute for Theoretical Physics
Lecture - QFT II, PHYS 603
Francois David CEA Saclay
Why should India be concerned about climate change?
J. SrinivasanICTS:30279Climate Change is one of the greatest challenges human beings will face in the 21st century. A large majority of the people do not think climate change is an urgent problem because the impact of climate change is not as dramatic as the COVID epidemic. The impact of climate change will, however, pose an existential threat to all mammals. In this lecture I will discuss the science of climate change. I will show the recent insight from the study of the natural climate change during the past million years indicates that the earth’s climate is not stable and has many tipping points. The ability of human being and other mammals to adapt to global warming beyond 2 degrees C is limited. The high impact but low-probability event like the slowing down of the Atlantic Meridional Ocean Circulation (AMOC) will alter the tropical climate dramatically.
Forecasting Monsoon Onset and Withdrawal in the Face of Climate Change
Elena SurovyatkinaICTS:30266The timing of monsoon season onset and withdrawal is of paramount importance to the population of the Indian subcontinent. Despite the rainy season occurring annually between June and September, the onset and withdrawal dates vary by up to a month from year to year, making accurate predictions a significant challenge.
However, a revolutionary approach has been developed those promises to transform our understanding of this phenomenon. By comprehending the core physical mechanisms involved in monsoon onset and withdrawal, spatial-temporal regularities have been discovered that can be used for forecasting. This approach fundamentally diverges from the traditional numerical weather and climate models by relying on the Nonlinear Dynamics and Nonlinear Phenomena in Statistical Physics.
This approach demonstrated successful results over a rigorous nine-year testing period, forecasting the onset date up to 40 days in advance and the withdrawal date up to 70 days in advance. It is also a...
From Critical Phenomena to Prediction of the Indian Summer Monsoon
Elena SurovyatkinaICTS:30281The critical phenomena occur in the vicinity of the critical point. These phenomena are indicators of an impending critical transition. Earlier methods treated the critical phenomena as early warning signals. However, they do not show any example where early warning signals have been used to avert an impending transition. They have been used in models, experiments or retrospectively.
The talk will present a perspective on how to address this challenge. I will discuss important limitations that must be accepted to build the knowledge needed for better prediction. I will apply the theory of critical transitions to a prediction of the onset and withdrawal dates of the Indian summer monsoon.
The abruptness of the onset and end of the monsoon and its interannual variability within a month are key features of the phenomenon that make monsoon forecasting extremely challenging. I will describe the main principles of monsoon timing prediction and show the cases for central India. Special ...
Who speaks for Earth?
Anthony Bonato Toronto Metropolitan University
Carl Sagan’s iconic question, "Who speaks for Earth?" from Cosmos invites us to reflect on whose voices are heard as we contemplate humanity's place in the universe. I will explore this question from the perspective of a queer mathematician, intertwining my personal journey with the broader experiences of LGBTQ+ scientists. Our diverse identities contribute to the richness of the scientific narrative, and by embracing our queerness, we ensure that the full spectrum of experiences is represented in the pursuit of knowledge. Drawing on Sagan’s legacy, I will argue that our voices, and our kindness to each other, are not just necessary but essential in shaping the future of science and our collective understanding of the world.
Generalized Quantum Stein's Lemma and Second Law of Quantum Resource Theories
Hayata YamasakiThe second law of thermodynamics is the cornerstone of physics, characterizing the convertibility between thermodynamic states through a single function, entropy. Given the universal applicability of thermodynamics, a fundamental question in quantum information theory is whether an analogous second law can be formulated to characterize the convertibility of resources for quantum information processing by a single function. In 2008, a promising formulation was proposed, linking resource convertibility to the optimal performance of a variant of the quantum version of hypothesis testing. Central to this formulation was the generalized quantum Stein's lemma, which aimed to characterize this optimal performance by a measure of quantum resources, the regularized relative entropy of resource. If proven valid, the generalized quantum Stein's lemma would lead to the second law for quantum resources, with the regularized relative entropy of resource taking the role of entropy in thermodynamics. However, in 2023, a logical gap was found in the original proof of this lemma, casting doubt on the possibility of such a formulation of the second law. In this work, we address this problem by developing alternative techniques to successfully prove the generalized quantum Stein's lemma under a smaller set of assumptions than the original analysis. Based on our proof, we reestablish and extend the second law of quantum resource theories, applicable to both static resources of quantum states and a fundamental class of dynamical resources represented by classical-quantum (CQ) channels. These results resolve the fundamental problem of bridging the analogy between thermodynamics and quantum information theory. The talk is based on the following paper. https://arxiv.org/abs/2408.02722Lecture - QFT II, PHYS 603
Francois David CEA Saclay
Climate networks as a tool for data-driven hypothesis generation
Bedartha GoswamiICTS:30271Over the past decade, climate networks have emerged as a powerful tool to characterise high dimensional weather and climate datasets. Climate networks are a sparse representation of the dynamical similarities between weather time series from different geographical locations. Nodes represent the locations themselves, and network edges represent high dynamical similarity between pairs of locations. The topology of the resulting complex network encodes information about how atmospheric and oceanic dynamics “connect” different locations. For instance, strong monsoon years might yield a different network structure than weak monsoon years. With the tools of graph theory and complex networks at our disposal, we can characterise climate dynamics in novel and interesting ways, which yield, in part, results that corroborate what meteorologists already know, and, in part, results that generate new hypotheses about how atmospheric and oceanic processes influence different weather patterns. In this...
Role of Statistical Reasoning in Understanding Climate
Amit ApteICTS:30265The main focus of these pedagogical talks will be on discussing the interplay between statistics and climate science as a two-way street. On one hand, thinking about the climate helps us understand many aspects of statistics, from the fundamental to conceptual to practical. On the other, statistical thinking is crucial and indispensable in studying climate. I will also emphasize that statistics plays an important role not just in climate studies, but more generally in understanding any complex system such as those from biological and social sciences as well. Another thread will be the discussion of interplay between uncertainty and dynamics, with an emphasis on the role of dynamical instabilities.