• Energy Research

Abstract Australia has experienced regional climate trends over recent decades with consequences for agriculture and water management. We investigate the statistical significance of these trends at annual and seasonal scales using the concept of stationarity. Using long-term high quality regional-scale observations of temperature, precipitation and pan evaporation (a measure of atmospheric evaporative demand), we find that despite highly significant increases in temperature that are non-stationary, few regions of Australia have experienced annual or seasonal changes in precipitation or pan evaporation that are outside the range of observed variability over the last century. Despite a common assumption of increasing water demand under a warming climate, atmospheric evaporative demand (as measured by pan evaporation) largely remains unchanged. This is because evaporative demand depends strongly on factors other than temperature. Similarly, seasonal and annual precipitation over the last century is found to be stationary in most (but not all) regions. These findings suggest that the Australian precipitation has largely remained within the bounds of observed variability to date and emphasises the need to better account for variability in water resource management.

Australia allocates less than 0.1% of health funding to research on health and climate change. This Perspective highlights the country's strength in the individual disciplines of climate science and health research and calls for bringing these areas together. A major Australian government report published 25 years ago called for urgent investment in research on the impacts of climate change on human health. Since that report's release, less than 0.1% of Australian health funding has been allocated to this area. As the world continues on a high emissions pathway, the health impacts from climate change are increasing in size and complexity. While Australia has established leadership roles in climate science and health research, it must now link these two strengths. Doing so would boost regional understanding of how climate change will affect health and what adaptation strategies are needed to reduce these threats. Such research would support better health planning and decision-making in partnership with other regional countries.

Abstract Social, technological and climatic changes will transform the way energy is consumed over the 21st century, with important implications for energy networks and greenhouse gas emissions. Here, we develop a method to efficiently explore climate-energy interactions under various scenarios of climate, urban infrastructure and technological change. We couple the Urban Climate and Energy Model with the Conformal Cubic Atmospheric Model as a full-height single column driven with a series of global climate model simulations in an ensemble approach. The framework is evaluated against observations, then a series of century-scale simulations are undertaken to examine projected climate change impacts on electricity and gas demand in the temperate/ oceanic climate of Melbourne, Australia. With air-conditioning ownership remaining at early 21st century levels, and in the absence of other changes, climate change under radiative forcing RCP 8.5 increases peak electricity demand by 10%, and decreases peak gas demand by 22% between 2000 and 2100. However, if projected increases in air-conditioning ownership are considered, peak electricity demand increases by 84%, surpassing peak gas demand in the second half of the century. These findings highlight the complex nature of changes facing energy networks. Changes will be location and scenario dependent.

AbstractStrong regional differences exist in how hot temperature extremes increase under global warming. Using an ensemble of coupled climate models, we examine the regional warming rates of hot extremes relative to annual average warming rates in the same regions. We identify hot spots of accelerated warming of model‐simulated hot extremes in Europe, North America, South America, and Southeast China. These hot spots indicate where the warm tail of a distribution of temperatures increases faster than the average and are robust across most Coupled Model Intercomparison Project Phase 5 models. Exploring the conditions on the specific day when the hot extreme occurs demonstrates that the hot spots are explained by changes in the surface energy fluxes consistent with drying soils. However, the model‐simulated accelerated warming of hot extremes appears inconsistent with observations, except over Europe. The simulated acceleration of hot extremes may therefore be unreliable, a result that necessitates a reevaluation of how climate models resolve the relevant terrestrial processes.

We examine the joint contribution of urban expansion and climate change on heat stress over the Sydney region. A Regional Climate Model was used to downscale present (1990-2009) and future (2040-2059) simulations from a Global Climate Model. The effects of urban surfaces on local temperature and vapor pressure were included. The role of urban expansion in modulating the climate change signal at local scales was investigated using a human heat-stress index combining temperature and vapor pressure. Urban expansion and climate change leads to increased risk of heat-stress conditions in the Sydney region, with substantially more frequent adverse conditions in urban areas. Impacts are particularly obvious in extreme values; daytime heat-stress impacts are more noticeable in the higher percentiles than in the mean values and the impact at night is more obvious in the lower percentiles than in the mean. Urban expansion enhances heat-stress increases due to climate change at night, but partly compensates its effects during the day. These differences are due to a stronger contribution from vapor pressure deficit during the day and from temperature increases during the night induced by urban surfaces. Our results highlight the inappropriateness of assessing human comfort determined using temperature changes alone and point to the likelihood that impacts of climate change assessed using models that lack urban surfaces probably underestimate future changes in terms of human comfort.

We present an assessment of the impact of future climate change on two key drivers of fire risk in Australia, fire weather and fuel load. Fire weather conditions are represented by the McArthur Forest Fire Danger Index (FFDI), calculated from a 12-member regional climate model ensemble. Fuel load is predicted from net primary production, simulated using a land surface model forced by the same regional climate model ensemble. Mean annual fine litter is projected to increase across all ensemble members, by 1.2 to 1.7 t ha−1 in temperate areas, 0.3 to 0.5 t ha−1 in grassland areas and 0.7 to 1.1 t ha−1 in subtropical areas. Ensemble changes in annual cumulative FFDI vary widely, from 57 to 550 in temperate areas, −186 to 1372 in grassland areas and −231 to 907 in subtropical areas. These results suggest that uncertainty in FFDI projections will be underestimated if only a single driving model is used. The largest increases in fuel load and fire weather are projected to occur in spring. Deriving fuel load from a land surface model may be possible in other regions, when this information is not directly available from climate model outputs.

AbstractSouth‐East Australia has recently been subjected to two of the worst droughts in the historical record (Millennium Drought, 2000–2009 and Big Dry, 2017–2019). Unfortunately, a lack of forest monitoring has made it difficult to determine whether widespread tree mortality has resulted from these droughts. Anecdotal observations suggest the Big Dry may have led to more significant tree mortality than the Millennium drought. Critically, to be able to robustly project future expected climate change effects on Australian vegetation, we need to assess the vulnerability of Australian trees to drought. Here we implemented a model of plant hydraulics into the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterized the drought response behaviour of five broad vegetation types, based on a common garden dry‐down experiment with species originating across a rainfall gradient (188–1,125 mm/year) across South‐East Australia. The new hydraulics model significantly improved (~35%–45% reduction in root mean square error) CABLE’s previous predictions of latent heat fluxes during periods of water stress at two eddy covariance sites in Australia. Landscape‐scale predictions of the greatest percentage loss of hydraulic conductivity (PLC) of about 40%–60%, were broadly consistent with satellite estimates of regions of the greatest change in both droughts. In neither drought did CABLE predict that trees would have reached critical PLC in widespread areas (i.e. it projected a low mortality risk), although the model highlighted critical levels near the desert regions of South‐East Australia where few trees live. Overall, our experimentally constrained model results imply significant resilience to drought conferred by hydraulic function, but also highlight critical data and scientific gaps. Our approach presents a promising avenue to integrate experimental data and make regional‐scale predictions of potential drought‐induced hydraulic failure.