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Climate 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.

The 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...

The 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 ...

Over 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...

The 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.

Oceanic flows stir and mix tracers such heat, salt, carbon, and plankton and understanding the details of the tracer dispersion is key to developing effective parameterizations for large climate-scale models. Unfortunately, the flow structure in the ocean is highly variable as a function of spatial scales. For instance O(100 km) mesoscale flows are significantly different from O(10 km) submesoscale flows. In this talk I'll use results from a recent study to explain how tracer dispersion characteristics change as we move from large mesoscales to small submesoscales in the oceans.

I present the recurrence analysis of temperature and relative humidity data from various locations spread over India, including the mountainous region, coastal region, and central and north eastern parts of India. This study reveals the spatiotemporal pattern underlying the climate dynamics and captures the variations in the complexity of the dynamics over the period 1948 to 2022. By reconstructing the dynamics from data, the recurrence pattern is studied using recurrence networks and the measures of the networks computed using a sliding window analysis on the data sets. This brings out the climate variability in different spatial locations and the heterogeneity across the locations chosen. The variations observed in dynamics can be correlated with reported shifts in the climate related to strong and moderate El Niño–Southern Oscillation events.

Critical transitions, relatively sudden transitions between qualitatively different dynamics, are due to various distinct mechanisms. So far, bifurcation induced, noise- induced, shock-induced or rate-induced transitions have been studied extensively. In complex systems like the climate system or ecosystems, particularly in coupled versions of them, the dynamics of different components or different subsystems is characterized by different timescales. One simple example are ecosystems exhibiting allometric slowing down, that means that the duration of lifecycles increases with the trophic level. Coupling different compartments of the climate system involves also different timescales as the intrinsic timescales of flow patterns in the atmosphere are much faster than in the ocean. To study the dynamics of such systems requires the use of the methodology of slow-fast systems to account properly for such timescale separation. We will discuss the concept of critical manifolds in slow-fast sy...