Articles | Volume 24, issue 18 
            
                
                    
            
            
            https://doi.org/10.5194/acp-24-10209-2024
                    © Author(s) 2024. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-10209-2024
                    © Author(s) 2024. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
Multi-scale variability of southeastern Australian wind resources
Claire L. Vincent
CORRESPONDING AUTHOR
                                            
                                    
                                            School of Geography, Earth and Atmospheric Sciences, The University of Melbourne, Melbourne, VIC, Australia
                                        
                                    
                                            ARC Centre of Excellence for Climate Extremes, The University of Melbourne, Melbourne, VIC, Australia
                                        
                                    Andrew J. Dowdy
                                            School of Geography, Earth and Atmospheric Sciences, The University of Melbourne, Melbourne, VIC, Australia
                                        
                                    
                                            ARC Centre of Excellence for Climate Extremes, The University of Melbourne, Melbourne, VIC, Australia
                                        
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Claire L. Vincent, Adam Nahar, and Kelvin Say
                                    Wind Energ. Sci., 10, 2435–2447, https://doi.org/10.5194/wes-10-2435-2025, https://doi.org/10.5194/wes-10-2435-2025, 2025
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                                                The most important days for wind energy to make a large contribution to the electricity supply are when electricity demand is high. We examined the wind resource of southeast Australia on these days. We found that most hot high-demand days are influenced by a similar weather pattern, while cold high-demand days can be cold, wet, and windy or associated with widespread light winds. These results are important when considering the types of weather that could influence future wind energy.
                                            
                                            
                                        Mathieu Pichault, Claire Vincent, Grant Skidmore, and Jason Monty
                                    Wind Energ. Sci., 6, 131–147, https://doi.org/10.5194/wes-6-131-2021, https://doi.org/10.5194/wes-6-131-2021, 2021
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                                                This paper assesses the behaviour and causality of sudden variations in wind power generation over a short period of time, also called "ramp events". It is shown, amongst other things, that ramps at the study site are mostly associated with frontal activity. Overall, the research contributes to a better understanding of the drivers and behaviours of wind power ramps at the wind farm scale, beneficial to ramp forecasting and ramp modelling.
                                            
                                            
                                        Claire L. Vincent, Adam Nahar, and Kelvin Say
                                    Wind Energ. Sci., 10, 2435–2447, https://doi.org/10.5194/wes-10-2435-2025, https://doi.org/10.5194/wes-10-2435-2025, 2025
                                    Short summary
                                    Short summary
                                            
                                                The most important days for wind energy to make a large contribution to the electricity supply are when electricity demand is high. We examined the wind resource of southeast Australia on these days. We found that most hot high-demand days are influenced by a similar weather pattern, while cold high-demand days can be cold, wet, and windy or associated with widespread light winds. These results are important when considering the types of weather that could influence future wind energy.
                                            
                                            
                                        Andrew Brown, Andrew Dowdy, and Todd P. Lane
                                    Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
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                                                A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
                                            
                                            
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                                                In response to flood risk, design flood estimation is a cornerstone of infrastructure design and emergency response planning, but design flood estimation guidance under climate change is still in its infancy. We perform the first published systematic review of the impact of climate change on design flood estimation and conduct a meta-analysis to provide quantitative estimates of possible future changes in extreme rainfall.
                                            
                                            
                                        Mathieu Pichault, Claire Vincent, Grant Skidmore, and Jason Monty
                                    Wind Energ. Sci., 6, 131–147, https://doi.org/10.5194/wes-6-131-2021, https://doi.org/10.5194/wes-6-131-2021, 2021
                                    Short summary
                                    Short summary
                                            
                                                This paper assesses the behaviour and causality of sudden variations in wind power generation over a short period of time, also called "ramp events". It is shown, amongst other things, that ramps at the study site are mostly associated with frontal activity. Overall, the research contributes to a better understanding of the drivers and behaviours of wind power ramps at the wind farm scale, beneficial to ramp forecasting and ramp modelling.
                                            
                                            
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                Short summary
                    We investigate how wind speed at the height of a wind turbine changes during El Niño and La Niña years and with season and time of day in southeastern Australia. We found that El Niño and La Niña can cause average wind speed differences of around 1 m s-1 in some regions. The highest wind speeds occur in the afternoon or evening around mountains or the coast and during the night for inland areas.  The results help show how placement of wind turbines can help balance electricity generation.
                    We investigate how wind speed at the height of a wind turbine changes during El Niño and La Niña...
                    
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