Undergraduate Summer Research Scholarships

This summer, there are many opportunities for undergraduate students to work at the Climate Change Research Centre through a Summer Research Scholarships. If you are interested in any of the following projects, visit the Faculty of Science Summer Vacation Research Scholarships page and contact the supervisor(s) for more information. Importantly, please go here for the actual application for the summer scholarship program.

In addition to the science faculty vacation research scholarships, there is also the opportunity to apply for summer scholarships through the ARC Centre of Excellence for Climate System Science (ARCCSS). ARCCSS has projects available at its five universities and partner organisations, including CSIRO, Bureau of Meteorology and Department of Environment. Click here for more information.

 

UNSW Faculty of Science projects in the CCRC


Australian vegetation dynamics: the role of water

Supervised by: Dr Anna Ukkola and Dr Martin De Kauwe

Australia is the driest inhabited continent with marked inter-annual variability in rainfall. This variability in water availability is a key determinant for ecosystem function. To improve future projections of vegetation-climate interactions, it is crucial to understand the underlying mechanisms controlling vegetation responses to water availability. This project aims to develop a better quantitative understanding of how plants respond to varying water availability by contrasting satellite-derived observations with simulations from the Australian community land surface model, CABLE. Some programming experience in Python, R or similar is desirable.

Exploring the mid-Holocene Green Sahara

Supervised by: Professor Steve Sherwood and Dr Vishal Dixit

The African Sahara could be the largest art gallery on Earth, showcasing thousands of engravings and cave paintings.  Desert today, it was covered with plants around 5000 years ago.  Climatic shifts had tremendous impact on African civilization and continue to be a threat to the Sahel region south of the Sahara, which experienced a multi-decadal drought during the latter half of the 20th century. The explanation for these shifts remains an enigma.  One idea is that mid-level drying inhibits precipitating convection in the region. In this project the student will analyse the decadal co-variations of mid-level drying and convection to test this idea, using global observation-based datasets.  The student should have a basic understanding of atmospheric processes, and some knowledge of data manipulation software is helpful.

Physical drivers of extreme marine heat waves

Supervised by: Dr Alex Sen GuptaDr Angela Maharaj and Dr Markus Donat

Marine heat waves can have a dramatic effect on marine species with often important implications for fisheries and aquaculture. Yet compared to their terrestrial counterparts only a handful of marine heat waves have been examined in detail to understand the physical processes that generate these events. In this project we will use observations of sea surface temperature in combination with hybrid observation/model dats sets of the subsurface ocean to 1. identify a major marine heat wave that has not been investigated in detail, 2. identify the local process (both oceanographic and atmospheric) that generated the event and 3. examine how the heatwave is affected by large scale climate oscillations (like El Nino and La Nina).

Siting of instruments for urban climate and air quality research in Sydney

Supervised by: Dr Melissa HartDr Angela Maharaj and Dr Giovanni Di Virgilio

Sydney’s population is predicted to grow by 30% within twenty years, most of which is slated for the semi-rural fringes. The resulting urbanisation will adversely impact temperature and air quality in these areas of rapid population growth. Currently there are few meteorological and air quality observational sites to adequately monitor the effects of this increased urbanisation on local weather and air quality. The Sydney Schools Weather and Air Quality (SWAQ) network aims to place instruments in Sydney schools to fill these gaps. A student with GIS knowledge and interest in urban environmental monitoring is required to consolidate information on existing monitoring sites, identify keys areas of development and projected population growth to produce a list of optimal monitoring sites in the greater Sydney region and surrounds. 

Australian east coast lows in satellite wind data

Supervised by: Dr Alejandro Di Luca and Associate Professor Jason Evans

Extra-tropical cyclones can be identified using a variety of 2-dimensional fields including mean sea level pressure, relative vorticity (e.g. at 850 hPa) and/or geopotential heights (e.g. 925 hPa). While all these fields provide appropriate characteristics and yields qualitatively similar results, they are all poorly constrained by observations, particularly over the oceans. As a consequence, results are sometimes largely dependent on the specific model used by the reanalysis product. For example, Australian East Coast Lows (ECLs) spend much of their life-time over the ocean where measurements of sea level pressure do not exist and substantial variation between different reanalysis can occur.

This project will implement an algorithm to identify ECLs using only surface wind fields as derived from satellite measurements. These results can then be used to evaluate the representation of ECLs in reanalysis products and to compare with results obtained using other meteorological fields. A number of cyclones characteristics will be used in the evaluation process such as their frequency, size and translation speed.

Modes of variability in Southern Hemisphere climate and oceans

Supervised by: Dr Agus Santoso

This project will examine particular features of Southern Hemisphere climate and oceans variability using observations and climate models.   The student will have the option to focus on a particular aspect of interest, such as processes associated with the El Nino Southern Oscillation or the Indian Ocean Dipole, or their extreme behaviour, just to name a few.   There will also be scope to extend the analysis to future projections under greenhouse forcing.  Other than learning about climate dynamics, the student will also gain skill in processing large data sets, conducting statistical analysis, and programming with Matlab.   

Where's NEMO now? Dynamics of the East Australia Current

Supervised by: Dr Alejandro Di Luca and Dr Paul Spence

The East Australia Current (EAC), made famous by the movie Finding Nemo, runs southward along the east coast of Australia. It is a highly variable current that transports an enormous amount of heat from the tropics to the Tasman Sea, and shapes Australia's climate by influencing the location and intensity of storms. The aim of this project is to quantify the ability of ocean models with a varying level of complexity to simulate key characteristics of the EAC (e.g. volume transport, heat transport, nutrient transport). The student will learn to handle big data, develop valuable Python programming skills, and understand the role of the EAC in Australian climate.

Assessing future changes in extreme surface fire weather and atmospheric instability

Supervised by: Dr Giovanni Di Virgilio and Associate Professor Jason Evans

Extreme bushfires occur under conditions of extreme surface fire weather and atmospheric instability that facilitates coupling between the fire and atmosphere, often generating pyro-cumulonimbus events. Several studies have been performed that investigated future changes in surface fire weather (often using the Forest Fire Danger Index, FFDI) and generally find an increase particularly in the transition seasons. Few studies have investigated the occurrence of severe atmospheric instability (using the continuous Haines index – cHaines). This project will investigate coincident occurrence of extreme FFDI and cHaines, its relationship with large fires, and how it will change in the future.

Optimization:  Can land surface models benefit from adapting current practices in hydrological models?

Supervised by: Dr Mark Decker and Professor Andy Pitman

Land surface models (LSMs) comprise the terrestrial component of weather and climate prediction systems.  Based on simplifying assumptions and reduced complexity representations of the physical processes, LSMs simulate the storage water, energy, and carbon within the soil, snow, and vegetation, as well as the transfer between the land and the atmosphere.  The land surface plays a crucial role in initiating thunderstorms and clouds, determining the near surface air temperature, and governing the severity of droughts.  LSMs stand distinct from global hydrological models (GHMs) because LSMs emphasize the transfer of energy, water, and chemicals between the land and the atmosphere and GHMs emphasize the flow of water in soils, rivers, and lakes.  Despite different focusses both  LSMs and GHMs simulate the terrestrial hydrological cycle.  However LSMs and GHMs approach model calibration in fundamentally different ways.  GHMs explicitly recognize the unobservability and uncertainty of model parameters and combine complex optimization algorithms with limited observations to find the optimum parameter values.  In contrast, LSMs neglect formal optimization and rely on hand tuning unkown parameters.  The benefit of optimization for GHMs is readily apparent even though parameter optimization is limited to data rich regions.  The LSM community generally neglects optimization when data is available due to the lack of observations over much of the globe.

This study will examine the efficacy of optimizing a LSM at several sites, and determine the transferability of the optimum parameters to sites with similar vegetation and climatology.  The land surface component of the Australian climate model (ACCESS), CABLE, will by optimized at several sites using observed fluxes of water and energy.  The transferability of the optimum parameters to sites with similar vegetation and climatology will be evaluated by using the optimized parameters at sites not used during the optimization.  This study will demonstrate if the LSM community is correct in neglecting optimization where the data are available because the models are utilized globally.

The student will conduct model simulations using default, optimized, and random parameter values.  This project involves the use of Linux systems, computer models, and model output analysis.  The ideal student will have some experience or interest in programming and visualization, for example with Python, NCL,or R.  The chosen scholar will gain expertise in handling real world data, using the land component of weather and climate models, and model output analysis.

 

Estimating sensitvity in a variable climate

Supervised by: Dr Leela Frankcombe.

The amount by which our climate will warm depends on the amount of greenhouse gases we emit as well as how sensitive the climate system is to those greenhouse gases. This 'climate sensitivity' is estimated from climate models or from observations of the real climate (either from the distant past or from the more recent historical period). When using resent observations we have to take into account the role of natural climate variability in order to make accurate estimates of climate sensitivity.

This project will use a highly idealised framework to study the effect of different types and amplitudes of climate variability on the estimation of climate sensitivity. Using the results from this project we aim to learn the optimum method of estimating sensitivity in a variable climate as well as the errors associated with that estimation.

Prior experience with a programming language is not required, but potential students must be willing to learn programming skills for the project.