99498 - CLIMATE VARIABILITY

Learning outcomes

The student will be able to determine the space-time scales of climatic structures and the main modes of climate variability. The student will acquire the mathematical-statistical knowledge to analyze climate variability from data and simulations of various sources. At the end of the course the student will be able to identify the major energy cycles and is capable to use these concepts for applications in predictability and predictions.

Course contents

The course introduces the main concepts and mechanisms of natural climate variability, combining theoretical foundations with practical data analysis and simple climate modelling. A strong practical component runs throughout the course. Using Python, students will analyse observational climate datasets, apply statistical methods to characterize climate variability, and develop, calibrate, and evaluate low-order climate models. Practical exercises include the implementation of conceptual models of ENSO, such as the delayed oscillator and recharge oscillator, together with analyses of other tropical climate modes. Practical activities consist of a combination of in-class computer sessions and take-home assignments.

The course also examines the processes governing the major atmospheric teleconnections, the influence of the stratosphere on the climate system, and the mechanisms of externally forced climate change. Students will investigate the predictability of weather and climate, and the foundations of operational prediction systems across timescales, from subseasonal forecasts to climate projections.

MODULE I

1. Characteristics of Climate Variability. Students will learn how climate variability is quantified and described across different temporal and spatial scales. The section introduces basic statistical tools, discusses examples from local and global climates, and examines the distinction between internal and external sources of climate variability.

2. Chaos and Stochastic Climate Variability. This section explores the chaotic nature of the climate system and the emergence of variability from atmospheric dynamics. Students will be introduced to stochastic climate models, including white-noise and red-noise processes, the Hasselmann stochastic climate model, and the interpretation of climate variability through power spectra.

3. Climate Modes and Climate Patterns. The course examines the spatial organization of climate variability and introduces the concept of climate modes. Statistical methods (e.g., EOF analysis, regression and composites maps) for identifying dominant patterns of variability are presented, together with major examples such as the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), Northern and Southern Annular Modes (NAM/SAM), and related large-scale patterns.

4. El Niño–Southern Oscillation (ENSO) and Other Ocean-Atmosphere Coupled Tropical Modes. A detailed study of ENSO, the dominant mode of interannual climate variability, covers its physical mechanisms, global teleconnections, predictability, and importance for seasonal climate prediction. The section also introduces the Indian Ocean Dipole (IOD) as another major mode of tropical climate variability.

5. Thermohaline Circulation and Abrupt Climate Change. Students will investigate the role of the global ocean overturning circulation in regulating Earth's climate. Topics include the Atlantic Meridional Overturning Circulation (AMOC), evidence from paleoclimate records, potential future changes under global warming, and conceptual models such as the Stommel two-box model that illustrate multiple equilibrium states and abrupt climate transitions.

MODULE II

1. Climate Variability and the Climate System. This unit introduces the Earth's climate system and the physical processes responsible for climate variability. Students will learn how climate variability is observed and monitored, and the major modes of natural climate variability. The unit also introduces atmospheric teleconnections and the advanced statistical methods commonly used to analyze climate data.

2. Atmospheric Dynamics and Modes. This unit examines the dominant modes of atmospheric variability in both the tropics and extratropics. Topics include the Madden–Julian Oscillation (MJO), ENSO teleconnections, monsoon systems, the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the Pacific–North American (PNA) pattern, and weather regimes. The role of the stratosphere in shaping climate variability is also explored through the Quasi-Biennial Oscillation (QBO), sudden stratospheric warmings, and stratospheric ozone.

3. Climate Change and Forced Variability. This unit focuses on externally forced changes in the climate system. Students will study the concept of radiative forcing, the effects of greenhouse gases, aerosols, and other climate forcings, as well as climate sensitivity and feedback mechanisms. The unit concludes with an overview of global warming and regional climate change.

4. Climate Predictability, Modelling, and Prediction Systems. This unit examines the scientific basis of weather and climate predictability in the presence of chaotic dynamics. Students will explore the limits of predictability, sources of forecast skill and uncertainty, and the role of ensemble prediction in probabilistic forecasting. Building on these foundations, students will examine operational prediction systems across timescales, including subseasonal, seasonal, decadal, and long-term climate projections.

Readings/Bibliography

• Notes and materials distributed by the professor

• Lectures notes on Introduction to climate dynamics by Dietmar Dommenget [https://virtuale.unibo.it/mod/url/view.php?id=1207497] (https://users.monash.edu.au/~dietmard/teaching/dommenget.climate.dynamics.lecture.notes.pdf )

Teaching methods

• Frontal lectures with blackboard and projector

• Practical sessions with Python/Jupyter Notebook

• Homework and final project in Python/Jupyter Notebook

Assessment methods

Students are required to develop a project assigned by the instructors. The project involves the analysis and interpretation of climate data and may also include numerical experiments and climate model simulations, depending on the assigned topic.

During the examination, students will first present and discuss their project with the instructors. This will be followed by an oral examination covering the course material from both Module I and Module II.

Both project discussion and the oral examination are about 20 minutes each.

Office hours

See the website of Giovanni Liguori

See the website of Paolo Ruggieri