ORCID Profile
0000-0001-9825-8082
Current Organisation
University of Tasmania
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Publisher: Wiley
Date: 12-12-2007
Publisher: Elsevier BV
Date: 12-2022
Publisher: Wiley
Date: 12-2004
Publisher: MDPI AG
Date: 12-09-2022
Abstract: Australia experiences a variety of climate extremes that result in loss of life and economic and environmental damage. This paper provides a first evaluation of the performance of state-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCMs) in simulating climate extremes over Australia. Here, we evaluate how well 37 in idual CMIP6 GCMs simulate the spatiotemporal patterns of 12 climate extremes over Australia by comparing the GCMs against gridded observations (Australian Gridded Climate Dataset). This evaluation is crucial for informing, interpreting, and constructing multimodel ensemble future projections of climate extremes over Australia, climate-resilience planning, and GCM selection while conducting exercises like dynamical downscaling via GCMs. We find that temperature extremes (maximum-maximum temperature -TXx, number of summer days -SU, and number of days when maximum temperature is greater than 35 °C -Txge35) are reasonably well-simulated in comparison to precipitation extremes. However, GCMs tend to overestimate (underestimate) minimum (maximum) temperature extremes. GCMs also typically struggle to capture both extremely dry (consecutive dry days -CDD) and wet (99th percentile of precipitation -R99p) precipitation extremes, thus highlighting the underlying uncertainty of GCMs in capturing regional drought and flood conditions. Typically for both precipitation and temperature extremes, UKESM1-0-LL, FGOALS-g3, and GCMs from Met office Hadley Centre (HadGEM3-GC31-MM and HadGEM3-GC31-LL) and NOAA (GFDL-ESM4 and GFDL-CM4) consistently tend to show good performance. Our results also show that GCMs from the same modelling group and GCMs sharing key modelling components tend to have similar biases and thus are not highly independent.
Publisher: MDPI AG
Date: 14-10-2022
Abstract: The Australian Alps are the highest mountain range in Australia, which are important for bio ersity, energy generation and winter tourism. Significant increases in temperature in the past decades has had a huge impact on bio ersity and ecosystem in this region. In this study, observed temperature is used to assess how temperature changed over the Australian Alps and surrounding areas. We also use outputs from two generations of NARCliM (NSW and Australian Regional Climate Modelling) to investigate spatial and temporal variation of future changes in temperature and its extremes. The results show temperature increases faster for the Australian Alps than the surrounding areas, with clear spatial and temporal variation. The changes in temperature and its extremes are found to be strongly correlated with changes in albedo, which suggests faster warming in cool season might be dominated by decrease in albedo resulting from future changes in natural snowfall and snowpack. The warming induced reduction in future snow cover in the Australian Alps will have a significant impact on this region.
Publisher: American Geophysical Union (AGU)
Date: 04-2022
DOI: 10.1029/2021EF002625
Abstract: Global climate models (GCMs) are essential for investigating climate change, but their coarse scale limits their efficacy for climate adaptation planning at the regional scales where climate impacts manifest. Dynamical downscaling of GCM outputs better resolves regional climate and thus provides improved guidance for climate policy at regional scales. Being expensive to run, downscaling uses a subset of GCMs, necessitating careful GCM selection. This evaluation identifies a suitable subset of CMIP6 GCMs for downscaling over Australia by assessing in idual GCMs against three criteria: (a) performance simulating daily climate variable distributions, climate means, extremes, and modes (b) model independence and (c) climate change signal ersity. Over Australia, GCMs are generally biased cold (warm) for maximum (minimum) temperature, with larger biases for minimum temperature. GCMs are generally wet biased, especially over the monsoonal north, but dry biased over eastern regions. Most GCMs show larger biases for temperature and precipitation over geographically complex, heavily populated eastern regions, relative to other regions. Evaluations identify a distinct group of 11 GCMs that perform consistently poorly across climate variables, statistics, and timescales with widespread, statistically significant biases, versus 13 GCMs that show consistent adequate‐to‐good performance with substantially reduced errors. Assessment of model independence highlights the lack of independence between several high‐performing GCMs, particularly from allied modeling groups, demonstrating the importance of careful ensemble selection when making selective s les of climate space. Once GCM climate signal ersity is considered, 6–8 mid‐to‐high‐performing, independent GCMs occupy the full range of the future climate space and, thus, are suitable for dynamical downscaling over CORDEX‐Australasia.
Publisher: Elsevier BV
Date: 08-2022
Publisher: Springer Science and Business Media LLC
Date: 27-03-2019
Publisher: Elsevier BV
Date: 08-2010
Publisher: Wiley
Date: 12-2005
Publisher: MDPI AG
Date: 31-05-2020
Abstract: Biomass burnings either due to Hazards Reduction Burnings (HRBs) in late autumn and early winter or bushfires during summer periods in various part of the world (e.g., CA, USA or New South Wales, Australia) emit large amount of gaseous pollutants and aerosols. The emissions, under favourable meteorological conditions, can cause elevated atmospheric particulate concentrations in metropolitan areas and beyond. One of the pollutants of concern is black carbon (BC), which is a component of aerosol particles. BC is harmful to health and acts as a radiative forcing agent in increasing the global warming due to its light absorption properties. Remote sensing data from satellites have becoming increasingly available for research, and these provide rich datasets available on global and local scale as well as in situ aethalometer measurements allow researchers to study the emission and dispersion pattern of BC from anthropogenic and natural sources. The Department of Planning, Industry and Environment (DPIE) in New South Wales (NSW) has installed recently from 2014 to 2019 a total of nine aethalometers to measure BC in its state-wide air quality network to determine the source contribution of BC and PM2.5 (particulate Matter less than 2.5 μm in diameter) in ambient air from biomass burning and anthropogenic combustion sources. This study analysed the characteristics of spatial and temporal patterns of black carbon (BC) in New South Wales and in the Greater Metropolitan Region (GMR) of Sydney, Australia, by using these data sources as well as the trajectory HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) modelling tool to determine the source of high BC concentration detected at these sites. The emission characteristics of BC in relation to PM2.5 is dependent on the emission source and is analysed using regression analysis of BC with PM2.5 time series at the receptor site for winter and summer periods. The results show that, during the winter, correlation between BC and PM2.5 is found at nearly all sites while little or no correlation is detected during the summer period. Traffic vehicle emission is the main BC emission source identified in the urban areas but was less so in the regional sites where biomass burnings/wood heating is the dominant source in winter. The BC diurnal patterns at all sites were strongly influenced by meteorology.
Publisher: American Geophysical Union (AGU)
Date: 07-2021
DOI: 10.1029/2020EF001833
Abstract: The NARCliM project contributes to the CORDEX initiative for Australasia. The first generation of NARCliM (N1.0) used CMIP3 global climate models (GCMs) and provided near and far future estimates of climate change across Australasia at 50‐km and southeast Australia at 10‐km resolution under a business‐as‐usual climate scenario. However, multiple sets of 20‐year periods in N1.0 did not permit analysis of long‐term, inter‐annual to decadal trends across the 21st century. Feedback on user needs for regional climate information revealed the desire for multiple emission scenarios and use of newer CMIP5 GCMs for dynamical downscaling. These limitations led to development of the second iteration of NARCliM, namely NARCliM1.5 (N1.5). The N1.5 downscaling exercise uses CMIP5 GCMs and is temporally expanded to cover 150 years (1950–2100) for two future Representative Concentration Pathways (RCP4.5 and RCP8.5). N1.5 simulations remain at the 50‐km and 10 km resolutions over the same domains as N1.0, thus producing an expanded and complementary data set for regional climate change. N1.5 simulations substantially improve over N1.0 in capturing the seasonal patterns and magnitudes of precipitation, including improvements in overall bias. Conversely, N1.5 shows similar results to N1.0 for maximum and minimum temperature, with no substantial improvement in overall bias. N1.5 projections project a hotter and drier future relative to N1.0. The combined N1.0 and N1.5 ensemble provides a wider spread of future climates more representative of that found in the full CMIP5 ensemble. Together, N1.0 and N1.5 ensembles provide an improved, more comprehensive data set for studying climate change.
Publisher: Wiley
Date: 12-2005
Publisher: Wiley
Date: 2009
DOI: 10.1111/J.1095-8649.2008.02121.X
Abstract: To assess the spatial variability in external morphology of non-native populations of topmouth gudgeon Pseudorasbora parva within an ontogenetic context, triple regression analysis (distance-based measurements) was applied to data from eight European populations (two Slovak, four Romanian, one English and one French). The data from Slovakia were also subjected to geometrical analysis (co-ordinates-based measurements) to obtain a more complex picture of the species' overall morphology. Great phenotypic variability was observed, being expressed not only in the formation of different definite phenotypes but also in the manner by which the phenotypes are achieved. Thus, both the definite phenotype and the patterns of development in invasive P. parva may be highly influenced by environmental conditions. Such great morphological (phenotypic) variability is likely to be one of the attributes that make this species such a successful invader.
Publisher: IOP Publishing
Date: 2021
Abstract: Most studies evaluating future changes in climate extremes over Australia have examined events that occur once or more each year. However, it is extremes that occur less frequently than this that generally have the largest impacts on sectors such as infrastructure, health and finance. Here we use an ensemble of high resolution (∼10 km) climate projections from the NSW and ACT Regional Climate Modelling (NARCliM) project to provide insight into how such rare events may change over southeast Australia in the future. We examine changes in the frequency of extremes of heat, rainfall, bushfire weather, meteorological drought and thunderstorm energy by the late 21st century, focusing on events that currently occur once every 20 years (those with a 5% Annual Exceedance Probability). Overall the ensemble suggests increases in the frequency of all five extremes. Heat extremes exhibit the largest change in frequency and the greatest ensemble agreement, with current 1-in-20 year events projected to occur every year in central Australia and at least every 5 years across most of southeast Australia, by the late 21st century. The five capital cities included in our model domain are projected to experience multiple climate extremes more than twice as frequently in the late 21st century, with some cities projected to experience 1-in-20 year events more than six times as frequently. Although in idual simulations show decreases in some extremes in some locations, there is no strong ensemble agreement for a decrease in any of the climate extremes over any part of southeast Australia. These results can support adaptation planning and should motivate further research into how extremely rare events will change over Australia in the future.
Publisher: Hindawi Limited
Date: 28-02-2012
Publisher: Schweizerbart
Date: 14-10-2008
Publisher: The Sax Institute
Date: 2018
DOI: 10.17061/PHRP2841826
Abstract: Changes in natural hazards related to climate change are evident in New South Wales (NSW), Australia, and are projected to become more frequent and intense. The impacts of climate change may adversely affect health and wellbeing, directly via extreme weather events such as heatwaves, storms and floods, and indirectly via impacts on food security, air and water quality, and other environmental amenities. The NSW Government's Climate Change Policy Framework recognises the need to reduce the effects of climate change on health and wellbeing. A conceptual framework can support the aims and objectives of the policy framework by depicting the effects of climate change on health, and in idual and social wellbeing, and areas for policy actions and responses. A proposed conceptual framework has been developed, modelled on the Driving force, Pressure, State, Exposure, Effect and Action (DPSEEA) framework of the World Health Organization - a framework which shows the link between exposures and health effects as well as entry points for interventions. The proposed framework presented in this paper was developed in consultation with researchers and policy makers. The framework is guiding current research examining vulnerabilities to climate change and the effects of a range of exposures on health and wellbeing.
Publisher: Springer Science and Business Media LLC
Date: 18-08-2022
Publisher: IOP Publishing
Date: 27-05-2022
Abstract: Heatwaves are Australia’s deadliest natural hazard. Anthropogenic climate change has increased the intensity, frequency and duration of heatwaves over Australia in the past several decades and these trends are projected to worsen in the future. Despite the strong knowledge of heatwave characteristics and their projected changes, there remains a gap in understanding how the Australian population will be exposed to future heatwaves. This study estimates changes in future exposure to heatwaves over Australia. We find that both for continental Australia and its capital cities, the trends in exposure are not projected to increase, but accelerate in the future. For RCP4.5-SSP2 and RCP8.5-SSP5 scenarios, the mean exposure to heatwaves in Australia is projected to increase by ∼29 and ∼42 times by the end of 21st century. Sydney, Melbourne, and Adelaide are the major cities where the population is most exposed to future heatwaves, with this exposure projected to increase by 52, 61, and 56 times respectively under the RCP8.5-SSP5 scenario. The results demonstrate that anthropogenic climate change is the key contributor (over 95%) in enhancing future heatwave exposure and population change on its own plays a relatively minor role (less than 5%). The results of this study are crucial for planning where adaptation measures might be necessary to protect large group of vulnerable Australians to future heatwave exposure.
Publisher: Wiley
Date: 16-03-2017
DOI: 10.1111/FME.12205
Publisher: Wiley
Date: 29-10-2010
Publisher: Springer Science and Business Media LLC
Date: 30-07-2020
Publisher: Wiley
Date: 29-08-2019
DOI: 10.1002/JOC.5820
Location: Australia
No related grants have been discovered for Kathleen Beyer.