Time: Semester 1 2023

Location: on campus (University of Melbourne, Parkville) and online (dual delivery)

Coordinator: Dr Josephine Brown, josephine.brown@unimelb.edu.au

The history of Earth’s climate provides examples of widely different states, ranging from cold glacial climates to hot greenhouse climates. Palaeoclimatology seeks to reconstruct past climate conditions and understand the dynamics and variability of the climate system on a range of time scales. This course will explore key examples of past warm and cold climates, including the Palaeocene-Eocene Thermal Maximum, the Pliocene, the warm last interglacial period and the last glacial maximum. The drivers and mechanisms of past climate change will be discussed, with a focus on topics of current debate in palaeoclimate science. Proxy records used to reconstruct past climate will be discussed, such as ice cores, marine sediments, tree ring and coral records. The use of climate models to simulate past climates will also be a explored. The course will also address the relevance of past climates for understanding future climate change due to human activity.

Time: Semester 2 2023

Location: on campus, Parkville

Coordinator: Assoc. Prof. Malte Meinshausen, malte.meinshausen@unimelb.edu.au


This subject describes the physics of the climate system, and how the system is represented in numerical models.

Key aspects include:

  • Radiation balance and heat balance of the earth
  • Carbon dioxide, water vapour and other Greenhouse Gas absorption spectra
  • Other key climate drivers including solar variability, aerosols and clouds
  • The global carbon cycle and the modelling of other greenhouse gases
  • Impacts of climate change including sea level rise and extreme events

It covers aspects of uncertainty and chaos to understand why climate models are imperfect but invaluable tools. Students will build a simple climate model and run numerical experiments with different greenhouse gases. Existing knowledge in python programming is recommended but can be acquired throughout the course. The subject will also briefly discuss the processes of the United Nations Framework Convention on Climate Change (UNCCC) and Intergovernmental Panel on Climate Change (IPCC).

The 12 lectures cover the following themes: 1. Introduction; 2. Radiative forcing; 3. Climate feedbacks; 4. Carbon & gas cycles; 5. Oceans & sea level rise; 6. Aerosols & Clouds; 7. Variability and El Nino*; 8. Water Cycle and Extremes; 9. Ensemble & probabilistic projections, D&A; 10. Scenarios, carbon dioxide removal and solar radiation management; 11. Climate Targets, carbon budgets and the Paris Agreement*; 12. Wrap Up

The lectures are accompanied with weekly exercises that provide students with hands-on conceptual learning, modelling and data analysis experience.

Time: Semester 2 2023

Location: on campus, Clayton, Monash University


The aim of the subject is to explore the basic dynamical principles governing flow in a rotating frame of reference (the Earth's frame of reference), and to use these principles to understand the large-scale dynamics of the atmosphere.

Time: Semester 1 2023

Location: on campus (Clayton), Monash University


The aim of this unit is to describe the design of global atmospheric models as they are used in Numerical Weather Prediction, seasonal prediction and climate simulation. The unit aims to provide a basic understanding of all aspects of global atmospheric modelling. It will describe modelling techniques required to apply the fundamental equations that govern atmospheric flow in the settings of a modern General Circulation Model.

Time and delivery: Semester 1 2023, on campus (Parkville) 

Climate change is one of the most important issues of our time. This subject covers the basics of climate science - including climate change, natural variability, extremes, climate scenarios, and detection and attribution - and how this translates into impacts on society, ecosystems and economies. The subject focuses on the production of climate science and data and how its creation, analysis, and use informs decisions made from multiple perspectives and across multiple levels, including governments, industry and communities. The subject has a particular focus on the Intergovernmental Panel on Climate Change (IPCC) reports. To develop practical skills, students are required to apply knowledge from the course to develop and justify various stakeholder positions, policies, or business cases. Students will build climate profiles for relevant stakeholders in order to assess and debate how national or other circumstances frame responses at the local, state and international level.



  • Analysis of each week's topic, 8 x 250 words, 40% of final mark
  • Written assessment/s - due Weeks 5, 9 and at the end of semester, 2000 words , 40% of final mark
  • Participation in a negotiation (session held during the final seminar), 20% of final mark


Time & Location:
Semester 1 (27 February – 26 May), Parkville Campus

Alister Self, alister.self@climate-energy-college.org

Time: Semester 1 2023 

Location: Monash University, Clayton Campus

Venue: Rainforest walk 9, Boardroom 107

Costs: None

Course Details: The unit will discuss some basic statistical methods for analysing climate dynamics with the aim of understanding the physical mechanisms driving the observed structures (statistics).  The unit will start with a discussion on the basics of probability theory, time series analysis, stochastic models and multi-variate data (pattern) analysis.  It will then focus on the principles of decision making in statistical analysis (significance tests), which is followed by a discussion of the pitfalls and general strategies in statistical analysis.  The unit will not focus on deriving statistical parameters, but rather will emphasise how these methods can be applied and will discuss the potential pitfalls in interpreting statistical results. For additional information please see (https://handbook.unimelb.edu.au/2019/subjects/atoc90010). 


On completion of this unit students will be able to:

1.     Do statistical analysis on probability distributions, time series, and multi-variate data.

2.     Apply standard statistical methods in climate dynamics data analysis.

3.     Interpret the outcomes of the statistical analysis in the context of climate dynamics.

4.     Read, understand and critically analyse the scientific literature on data analysis in climate dynamics.

Prerequisites: This unit assumes basic university level math. This includes basic calculus and linear algebra.



Examination (closes book; 3hrs): 60%

Assignments (~weekly): 40%


Dates, Times, Schedule: Unit is done in 6 weeks.

Start: week 2 Mar.

End: week 17 April.

What you Need to Bring: Some unit assignments are based on MatLab, so students are required to have access to a computer that is running MatLab (or equivalent; e.g. Octave). 

Registration Deadline: 15 February 2020.

Lecturer: Assoc. Prof. Dietmar Dommenget

ARC Centre of Excellence for Climate Extremes
School of Earth, Atmosphere and Environment
Monash University, VIC 3800

Phone: +61-3-990-54495
Email: dietmar.dommenget@monash.edu
Website: users.monash.edu.au/~dietmard/index.html