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

In this course we will introduce the fundamental processes characterizing the climate systems on a wide range of spatial and temporal scales: from local (~km) to planetary (~10^4km) and from daily to multi-decadal. We will explore the physical principles and processes that control both the climate’s mean state and variability, and learn statistical methods commonly used in climate data analysis.

In the first part, we will begin with an overview of the observed state of the two main components of the climate system: the atmosphere and the world ocean. We will discuss the role of atmospheric circulations in maintaining the Earth’s energy, angular momentum, and water balances, which determine the planet’s distributions of temperatures, winds, and precipitation.

In the second part of the course, we will focus on the main modes of natural climate variability, from the seasonal to the multi-decadal timescale: the Madden-Julian Oscillation, the El Niño-Southern Oscillation, the Atlantic Multidecadal Variability and the Pacific Decadal Oscillation, and others. We end this part of the course with a discussion of the relevance of an accurate knowledge of natural climate variability within the context of anthropogenic climate variability (i.e., climate change).

In the third and last part, we will introduce basic statistical methods used to characterize recurrent spatial and temporal patterns of the climate system and apply them in practice with hands-on practical sessions.

Readings/Bibliography

Main textbook: 

Global Physical Climatology (Dennis L. Hartmann, 2016; Academic Press - Second edition)

The book is freely accessible at this [link] 

 

Other references: 

Climate Change and Climate Modeling ( David J. Neelin, 2010; Cambridge University Press, 282 pp.)

  Dannis L. Hartmann's note for his course of Objective Analysis [link]

 

Teaching methods

• Frontal lectures with slide projector
• Practical sessions in a computer lab  

Office hours

See the website of Giovanni Liguori

See the website of Salvatore Pascale