The ARC Centre of Excellence for Climate Extremes has contributed to a new scientific study that reveals that extremely hot and cold temperatures, drought and heavy rainfall strongly affect the year-to-year variation in the total global yield of four important crops.
The seven-year funding for Centres of Excellence ostensibly supports focused research across existing scientific communities but, as the Consortium for Ocean-Sea Ice Modelling in Australia (COSIMA) shows, it can also help create entirely new scientific communities in a specific research area.
The CLEX node at University of Melbourne is offering several PhD scholarships on a competitive basis. Details of how to apply can be found on this page along with some example projects offered by our researchers.
Climate scientists testing a new mathematical and statistical method that converts projections of future climate outcomes in a warming world into reliable probabilities have found there is a significant chance the Arctic could be ice-free even if world leaders meet the Paris targets of 1.5°C and 2°C.
After some well deserved (and in many cases long overdue) summer holidays the Centre has seen a rapid ramp up of research in the last couple of months. Cross research program collaboration has intensified, focussed on improving our modelling systems, using our models to examine key phenomenon and in particularly how we can improve the representation of extreme events.
This PhD project will apply a state of the art, hierarchical Bayesian modelling framework to determine how past climatic conditions influence current responses to high CO2concentrations.
Weather and climate extremes occur on a wide range of time and space scales. Weather extremes occur on shorter timescales and are regionally or locally specific while climate extremes tend to be on longer timescales and can impact a region through to the whole globe. This note provides a statement on what we know about how weather and climate extremes might change in the future.
This research shows how to optimise the observational uncertainty description for data assimilation schemes in the special case of state dependent observational uncertainty.
New data assimilation method leads to large improvements in forecast accuracy when satellite observations of electromagnetic radiation emanating from the Earth were used to inform the data assimilation scheme.
Two papers by Centre of Excellence researchers are the first to systematically investigate and document hybrid cyclones in the Australian region.