A modern, futuristic university building with angular white structures, large glass panels, and tiered balconies. Students walk toward the entrance under a clear blue sky. A sign in the foreground reads “Monash” and indicates the Green Chemical Futures Building.

Honours opportunities at Monash University

The ARC Centre of Excellence for the Weather of the 21st Century explores how Australia’s weather is being reshaped by climate change. We periodically offer Honours projects intended to provide undergraduate students from Australian universities with an introduction to cutting-edge climate science and weather change research.

For more information about Honours projects at Monash University and to apply, go to: https://www.monash.edu/science/schools/earth-atmosphere-environment/honours

Current Opportunities

Tropical thunderstorms and the climate

Supervisor: A/Prof Martin Singh

The most intense thunderstorms on Earth are found in the tropics. Will their strength change with climate change? And how much do the storms themselves influence the climate as a whole? In this project we will use a relatively new method to investigate the two-way interaction of thunderstorms and their environment in observations and in climate models. The results will tell us about the ways in which clouds eject moisture into the environment, and how that influences subsequent cloud development.

Requirements: Experience with Python, GitHub or other coding and programming tools is desirable.


How bad will bushfires get in the future?

Supervisor: A/Prof Martin Singh

Bushfires are likely to get worse as the climate warms. This makes intuitive sense – things catch fire more easily if it is hot. But it is actually not high temperatures that makes fires worse, but low humidities. In the future, the atmosphere becomes more hungry for water vapour, evaporation increases, and fires worsen. What is less remarked upon is that this effect is very different if one thinks about relative humidity versus other measures of vapour demand (such as vapour deficit). In this project we will test how sensitive projections of fire danger are to how one thinks about the effect of moisture. Could we be vastly underestimating or overestimating future fire danger?

Requirements: Experience with Python, GitHub or other coding and programming tools is desirable.


Investigating the impact of changing fire-management practices on northern Australia rainfall trends

Supervisor: Prof Julie Arblaster

Northern Australian rainfall has increased significantly over the past 30-50 years, yet the drivers of this increase are unclear. This project will investigate how changes in fire-management practices and associated land-cover changes may have contributed to these rainfall trends. Indigenous fire-management practices, which involve setting small controlled fires early in the dry season, reducing fuel loads and preventing intense late-season fires, can alter the landscape on year-to-year and longer timescales, with feedbacks onto the atmosphere and potentially rainfall. Using model experiments which incorporate these changes in historical fire-management practices, the sensitivity of rainfall trends to land-use changes will be investigated.

Requirements: Experience with Python, GitHub or other coding and programming tools is desirable.


Understanding decadal variations in monsoon-ENSO connections

Supervisor: Prof Julie Arblaster

Monsoons are known to be significantly impacted by the El Niño–Southern Oscillation (ENSO), yet monsoon-ENSO connections vary in strength on decadal timescales. Given half the world’s population live in a monsoon region, improved predictions of monsoon rains is of critical importance. In collaboration with researchers at the National Center for Atmospheric Research (USA), this project will explore the mechanisms by which these relationships vary in observations and climate models in the context of present day and future predictions.

Requirements: Experience with Python, GitHub or other coding and programming tools is desirable.


The semi-annual oscillation in high resolution climate models

Supervisor: Prof Julie Arblaster

The semi-annual oscillation (SAO) involves a twice-annual expansion and contraction of the circumpolar atmospheric trough over the Southern Ocean around Antarctica and can impact the development of El Niño events. This project will evaluate how the latest climate models reproduce the SAO and its interactions with the tropical regions. Recent studies have suggested changes in the winds and pressure over the Southern Ocean play a critical role in tropical sea surface temperature changes, hence understanding the simulation of the SAO could help elucidate the mechanisms through which the polar and tropical regions are connected.

Requirements: Experience with Python, GitHub or other coding and programming tools is desirable.


Investigating calm-wind events over the Pacific and Maritime Continent

Supervisor: Dr Julia Windmiller

The tropical “doldrums” are regions of persistently weak surface winds over the Pacific and Maritime Continent that remain surprisingly poorly understood, despite their importance for tropical rainfall and climate. This project will use ocean buoy observations to identify low-wind events and test a simple but fundamental question: when the winds die down, does it actually rain? Similar analyses in the tropical Atlantic have already revealed intriguing results, and climate models suggest these calm regions may play an important role in how tropical weather is represented. The project is data-analysis based, involving Python-based analysis of buoy and atmospheric datasets alongside background reading on the underlying science. Beyond its relevance to fundamental climate science, the project touches on questions relevant to renewable energy, particularly the mapping of regions prone to frequent low wind speeds, and will develop transferable skills in programming, data analysis, and working with large environmental datasets.

Requirements: Experience with Python, GitHub or other coding and programming tools is desirable.