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With climate change, heat waves are becoming increasingly frequent, intense and broader in spatial extent. However, while the lethal effects of heat waves on humans are well documented, the impacts on flora are less well understood, perhaps except for crops. We summarize recent findings related to heat wave impacts including: sublethal and lethal effects at leaf and plant scales, secondary ecosystem effects, and more complex impacts such as increased heat wave frequency across all seasons, and interactions with other disturbances. We propose generalizable practical trials to quantify the critical bounding conditions of vulnerability to heat waves. Collectively, plant vulnerabilities to heat waves appear to be underappreciated and understudied, particularly with respect to understanding heat wave driven plant die-off and ecosystem tipping points.

Regional climate models (RCMs) are used to dynamically downscale global climate models (GCMs) to provide high-resolution projections of future climate change to better inform policy and decision making at the regional scale. However, biases from GCMs are transferred to RCMs and this can limit the usefulness of the regional climate projections. This paper investigates the influence of bias correcting 4 GCMs from the Coupled Model Intercomparison Project 3, for regional climate simulations over the CORDEX-Australasia domain using Weather Research and Forecasting. The GCM outputs are bias corrected against ERA-Interim reanalysis as a surrogate truth. Results show that over decadal time scales bias correction removes large systematic precipitation and temperature biases. However, bias correction also introduced biases where there were none, introduced biases of the opposite sign, or enhanced existing biases in other regions in some instances. The dynamical mechanisms driving the changes in the biases are explored.

Increasing atmospheric CO2 is both leading to climate change and providing a potential fertilisation effect on plant growth. However, southern Australia has also experienced a significant decline in rainfall over the last 30 years, resulting in increased vegetative water stress. To better understand the dynamics and responses of Australian forest ecosystems to drought and elevated CO2, the magnitude and trend in water use efficiency (WUE) of forests, and their response to drought and elevated CO2 from 1982 to 2014 were analysed, using the best available model estimates constrained by observed fluxes from simulations with fixed and time-varying CO2. The ratio of gross primary productivity (GPP) to evapotranspiration (ET) (WUEe) was used to identify the ecosystem scale WUE, while the ratio of GPP to transpiration (Tr) (WUEc) was used as a measure of canopy scale WUE. WUE increased significantly in northern Australia (p < 0.001) for woody savannas (WSA), whereas there was a slight decline in the WUE of evergreen broadleaf forests (EBF) in the southeast and southwest of Australia. The lag of WUEc to drought was consistent and relatively short and stable between biomes (≤3 months), but notably varied for WUEe, with a long time-lag (mean of 10 months). The dissimilar responses of WUEe and WUEc to climate change for different geographical areas result from the different proportion of Tr in ET. CO2 fertilization and a wetter climate enhanced WUE in northern Australia, whereas drought offset the CO2 fertilization effect in southern Australia.

The Community Atmosphere Biosphere Land Exchange (CABLE) model is a third‐generation land surface model (LSM). CABLE is commonly used as a stand‐alone LSM, coupled to the Australian Community Climate and Earth Systems Simulator global climate model and coupled to the Weather Research and Forecasting (WRF) model for regional applications. Here, we evaluate an updated version of CABLE within a WRF physics ensemble over the COordinated Regional Downscaling EXperiment (CORDEX) AustralAsia domain. The ensemble consists of different cumulus, radiation and planetary boundary layer (PBL) schemes. Simulations are carried out within the NASA Unified WRF modeling framework, NU‐WRF. Our analysis did not identify one configuration that consistently performed the best for all diagnostics and regions. Of the cumulus parameterizations the Grell‐Freitas cumulus scheme consistently overpredicted precipitation, while the new Tiedtke scheme was the best in simulating the timing of precipitation events. For the radiation schemes, the RRTMG radiation scheme had a general warm bias. For the PBL schemes, the YSU scheme had a warm bias, and the MYJ PBL scheme a cool bias. Results are strongly dependent on the region of interest, with the northern tropics and southwest Western Australia being more sensitive to the choice of physics options compared to southeastern Australia which showed less overall variation and overall better performance across the ensemble. Comparisons with simulations using the Unified Noah LSM showed that CABLE in NU‐WRF has a more realistic simulation of evapotranspiration when compared to GLEAM estimates.

The city of Melbourne in southeast Australia is planning to expand urban areas substantially by the year 2050 and this expansion has the potential to alter the Urban Heat Island (UHI), that is, higher temperatures in urban areas as compared to surrounding rural areas. Moreover, Melbourne has been experiencing more frequent heatwaves for last two decades, and the intensity and duration of heatwaves is expected to increase in the future, which could exacerbate the UHI. This study evaluates the potential impacts of future urban expansion on the urban meteorology in Melbourne city during four of the most severe heatwave events during the period 2000–2009. Urban expansion is implemented as high‐density urban with a high urban fraction of 0.9 to investigate the maximum possible impact. Simulations are carried out using the Weather Research and Forecasting model coupled with the Single‐Layer Urban Canopy Model with current land‐use and future urban expansion scenarios. Urban expansion increases the near‐surface (2‐m) UHI (UHI2) by 0.75 to 2.80 °C and the skin‐surface UHI (UHIsk) by 1.9 to 5.4 °C over the expanded urban areas during the night, with no changes in existing urban areas. No substantial changes in UHI2 and UHIsk occur during the day over both existing and expanded urban areas. This is largely driven by changes in the storage heat flux, with an increase in storage heat at night and a decrease during the day; that is, excess storage heat accumulated during the day is released at night, which causes a slower decrease of near‐surface temperature and increase in the UHI. Urban expansion did not affect human thermal comfort (HTC) in existing urban areas and there were no marked differences in HTC between existing and expanded urban areas.

Climate observations and projections for Australia show an increase in warm temperature extremes, including the frequency, duration and intensity of heatwaves. Recent global scale studies have suggested that agricultural land-use management options, such as increasing crop albedo, could reducing local warming. Australia has approximately 3,727,210 km2 of cropland agricultural land-use, the majority of which is in southwest Western Australia and southeast Australia. This presents a potential opportunity to reduce regional warming via crop albedo enhancement. We use a regional climate model at 10 km resolution, to show that crop albedo enhancement of up to 0.1 could reduce monthly mean daily maximum temperatures by −1.0 °C to −1.2 °C, and monthly highest maximum temperatures by up to −1.4 °C to −1.6 °C during the cropping season. This cooling is approximately 3 times higher over Australia than global climate models predict. We highlight stronger cooling over southwest Western Australia as compared to southeast Australia, the opposite to global model studies which poorly resolve southwestern agricultural regions. The regional cooling was driven by a reduction in surface net shortwave radiation leading to a decrease in both sensible and latent heat flux of up to 50 W m−2 and 20 W m−2 respectively, when albedo is increased by up to 0.1. There were no cloud feedbacks or effects on precipitation. Our results highlight the importance of using regional climate models at a sufficiently high spatial resolution when investigating agricultural land-use management to reduce regional warming.

Ecosystems in shallow, micro-tidal lagoons are particularly sensitive to hydrologic changes. Lagoons are also highly complex transitional ecosystems between land and sea, and the signals of direct human disturbance to the lagoon can be confounded by variability of the climate system, but from an effective estuary management perspective the effects of climate versus direct human engineering interventions need to be identified separately. Although many estuarine lagoons have undergone substantial human interventions, such as artificial channels, the effects from the interaction of climate change with engineering interventions have not been well evaluated. This study developed a 3D finite-volume hydrodynamic model to assess changes in hydrodynamics of the Peel-Harvey Estuary, a large chocked-type lagoon, considering how attributes such as water retention time, salinity and stratification have responded to a range of factors, focusing on the drying climate trend and the opening of a large artificial channel over the period from 1970 to 2016, and how they will evolve under current climate projections. The results show that the drying climate has fundamentally changed the hydrology by comparable magnitudes to that of the opening of the artificial channel, and also highlight the complexity of their interacting impacts. Firstly, the artificial channel successfully improved the estuary flushing by reducing average water ages by 20–110 days; while in contrast the reduced precipitation and catchment inflow had a gradual opposite effect on the water ages, and during the wet season this has almost counteracted the reduction brought about by the channel. Secondly, the drying climate caused an increase in the salinity of the lagoon by 10–30 PSU; whilst the artificial channel increased the salinity during the wet season, it has reduced the likelihood of hypersalinity (> 40 PSU) during the dry season in some areas. The impacts also varied spatially in this large lagoon. The southern estuary, which has the least connection with ocean through the natural channel, is the most sensitive to climate change and the opening of the artificial channel. The projected future drying climate is shown to slightly increase the retention time and salinity in the lagoon, and increase the hypersalinity risk in the rivers. The significance of these changes for nutrient retention and estuary ecology are discussed, highlighting the importance of these factors when setting up monitoring programs, environmental flow strategies and nutrient load reduction targets.

This study evaluates the effectiveness of green and cool roofs as potential Urban Heat Island (UHI) mitigation strategies, and the impacts of these strategies on human thermal comfort during one of the most extreme heatwave events (27th - 30th January 2009) in the city of Melbourne in southeast Australia. The Weather Research and Forecasting model coupled with the Single Layer Urban Canopy Model including different physical parameterization for various types of roofs (conventional, green and cool roofs) is used to investigate the impacts of green and cool roofs. Results show that the maximum roof surface UHI is reduced during the day by 1 °C–3.8 °C by increasing green roof fractions from 30% to 90%, and by 2.2 °C–5.2 °C by increasing the albedo of cool roofs from 0.50 to 0.85. Cool roofs are more efficient than the green roofs in reducing the UHI with maximum differences of up to 1.4 °C. The reductions of the UHI vary linearly with the increasing green roof fractions, but slightly non-linearly with the increasing albedo of cool roofs. The maximum reductions in wind speed are 1.25 m s−1 and 1.75 m s−1 with 90% green and cool roofs (albedo 0.85) respectively. While previous studies report that the advection of moist air from rural areas is a key mechanism, this study shows that this is not the case for the extreme heatwave event due to the very dry and warm conditions, and instead, convective rolls play a more important role. This study also shows that initial soil moisture for green roofs does not have a substantial impact on the UHI. Finally, green roofs improve human thermal comfort by reducing the Universal Thermal Comfort Index by up to 1.5 °C and 5.7 °C for pedestrian and roof surface levels respectively, and by 2.4 °C and 8 °C for cool roofs for the same levels.

The negative impacts of climate extremes on socioeconomic sectors in Australia makes understanding their behaviour under future climate change necessary for regional planning. Providing robust and actionable climate information at regional scales relies on the downscaling of global climate model data and its translation into impact-relevant information. The New South Wales/Australian Capital Territory Regional Climate Modelling (NARCliM) project contains downscaled climate data over all of Australia at a 50 km resolution, with ensembles of simulations for the recent past (1990–2009), near future (2020–2039) and far future (2060–2079). Here we calculate and examine sector-relevant indices of climate extremes recommended by the Expert Team on Sector-specific Climate Indices (ET-SCI). We demonstrate the utility of NARCliM and the ET-SCI indices in understanding how future changes in climate extremes could impact aspects of the health and agricultural sectors in Australia. Consistent with previous climate projections, our results indicate that increases in heat and drought related extremes throughout the 21st century will occur. In the far future, maximum day time temperatures are projected to increase by up to 3.5 °C depending on season and location. The number of heatwaves and the duration of the most intense heatwaves will increase significantly in the near and far future, with greater increases in the north than south. All capital cities are projected to experience at least a tripling of heatwave days each year by the far future, compared to the recent past. Applying published heat-health relationships to projected changes in temperature shows that increases in mortality due to high temperatures for all cities examined would occur if projected future climates occurred today. Drought and the number of days above 30 °C are also projected to increase over the major wheat-growing regions of the country, particularly during spring when sensitivity of wheat to heat stress is greatest. Assuming no adaptation or acclimatisation, published statistical relationships between drought and national wheat yield suggest that national yields will have a less than one quarter chance of exceeding the annual historical average under far future precipitation change (excluding impacts of future temperature change and CO2 fertilization). The NARCliM data examined here, along with the ET-SCI indices calculated, provide a powerful and publicly available dataset for regional planning against future changes in climate extremes.

WaSSI-C is an ecohydrological model which couples water and carbon cycles with water use efficiency (WUE) derived from global eddy flux observations. However, a significant limitation of the WaSSI-C model is that it only runs serially. High resolution simulations at a large scale are therefore computationally expensive and cause a run-time memory burden. Using distributed (MPI) and shared (OpenMP) memory parallelism techniques, we revised the original model as dWaSSI-C. We showed that using MPI was effective in reducing the computational run-time and memory use. Two experiments were carried out to simulate water and carbon fluxes over the Australian continent to test the sensitivity of the parallelized model to input data-sets of different spatial resolutions, as well as to WUE parameters for different vegetation types. These simulations were completed within minutes using dWaSSI-C, whereas they would not have been possible with the serial version. The dWaSSI-C model was able to simulate the seasonal dynamics of gross ecosystem productivity (GEP) reasonably well when compared to observations at four eddy flux sites. Sensitivity analysis showed that simulated GEP was more sensitive to WUE during the summer compared to winter in Australia, and woody savannas and grasslands showed higher sensitivity than evergreen broadleaf forests and shrublands. Although our results are model-specific, the parallelization approach can be adopted in other similar ecosystem models for large scale applications.

The Weather Research and Forecasting (WRF) Model is evaluated as a regional climate model for the simulation of climate indices that are relevant to viticulture in Western Australia’s wine regions at a 5-km resolution under current and future climate. WRF is driven with ERA-Interim reanalysis for the current climate and three global climate models (GCMs) for both current and future climate. The focus of the analysis is on a selection of climate indices that are commonly used in climate–viticulture research. Simulations of current climate are evaluated against an observational dataset to quantify model errors over the 1981–2010 period. Changes to the indices under future climate based on the SRES A2 emissions scenario are then assessed through an analysis of future (2030–59) minus present (1970–99) climate. Results show that when WRF is driven with ERA-Interim there is generally good agreement with observations for all of the indices although there is a noticeable negative bias for the simulation of precipitation. The results for the GCM-forced simulations were less consistent. Namely, while the GCM-forced simulations performed reasonably well for the temperature indices, all simulations performed inconsistently for the precipitation index. Climate projections showed significant warming for both of the temperature indices and indicated potential risks to Western Australia’s wine growing regions under future climate, particularly in the north. There was disagreement between simulations with regard to the projections of the precipitation indices and hence greater uncertainty as to how these will be characterized under future climate.

Appropriate choice of physics options among many physics parameterizations is important when using the Weather Research and Forecasting (WRF) model. The responses of different physics parameterizations of the WRF model may vary due to geographical locations, the application of interest, and the temporal and spatial scales being investigated. Several studies have evaluated the performance of the WRF model in simulating the mean climate and extreme rainfall events for various regions in Australia. However, no study has explicitly evaluated the sensitivity of the WRF model in simulating heatwaves. Therefore, this study evaluates the performance of a WRF multi-physics ensemble that comprises 27 model configurations for a series of heatwave events in Melbourne, Australia. Unlike most previous studies, we not only evaluate temperature, but also wind speed and relative humidity, which are key factors influencing heatwave dynamics. No specific ensemble member for all events explicitly showed the best performance, for all the variables, considering all evaluation metrics. This study also found that the choice of planetary boundary layer (PBL) scheme had largest influence, the radiation scheme had moderate influence, and the microphysics scheme had the least influence on temperature simulations. The PBL and microphysics schemes were found to be more sensitive than the radiation scheme for wind speed and relative humidity. Additionally, the study tested the role of Urban Canopy Model (UCM) and three Land Surface Models (LSMs). Although the UCM did not play significant role, the Noah-LSM showed better performance than the CLM4 and NOAH-MP LSMs in simulating the heatwave events. The study finally identifies an optimal configuration of WRF that will be a useful modelling tool for further investigations of heatwaves in Melbourne. Although our results are invariably region-specific, our results will be useful to WRF users investigating heatwave dynamics elsewhere.

Increasing atmospheric CO

The ability of regional climate models (RCMs) to accurately simulate current and future climate is increasingly important for impact assessment. This is the first evaluation of all reanalysis-driven RCMs within the CORDEX Australasia framework [four configurations of the Weather Forecasting and Research (WRF) model, and single configurations of COSMO-CLM (CCLM) and the Conformal-Cubic Atmospheric Model (CCAM)] to simulate the historical climate of Australia (1981–2010) at 50 km resolution. Simulations of near-surface maximum and minimum temperature and precipitation were compared with gridded observations at annual, seasonal, and daily time scales. The spatial extent, sign, and statistical significance of biases varied markedly between the RCMs. However, all RCMs showed widespread, statistically significant cold biases in maximum temperature which were the largest during winter. This bias exceeded − 5 K for some WRF configurations, and was the lowest for CCLM at ± 2 K. Most WRF configurations and CCAM simulated minimum temperatures more accurately than maximum temperatures, with biases in the range of ± 1.5 K. RCMs overestimated precipitation, especially over Australia’s populous eastern seaboard. Strong negative correlations between mean monthly biases in precipitation and maximum temperature suggest that the maximum temperature cold bias is linked to precipitation overestimation. This analysis shows that the CORDEX Australasia ensemble is a valuable dataset for future impact studies, but improving the representation of land surface processes, and subsequently of surface temperatures, will improve RCM performance. The varying RCM capabilities identified here serve as a foundation for the development of future regional climate projections and impact assessments for Australia.

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.

Projections of future climate change (1970–1999 compared to 2030–2059) for southwest Western Australia (SWWA) are analysed for a regional climate model (RCM) ensemble using the Weather Research and Forecasting Model with boundary conditions from three CMIP3 general circulation models (GCMs); CCSM3, CSIROmk3.5 and ECHAM5. We show that the RCM adds value to the GCM and we suggest that this is through improved representation of regional scale topography and enhanced land–atmosphere interactions. Our results show that the mean daytime temperature increase is larger than the nighttime increase, attributed to reduced soil moisture and hence increased surface sensible heat flux in the model, and there is statistically significant evidence that the variance of minimum temperatures will increase. Changes in summer rainfall are uncertain, with some models showing rainfall increases and others projecting reductions. All models show very large fluctuations in summer rainfall intensity which has important implications because of the increased risk of flash flooding and erosion of arable land. There is model consensus indicating a decline in winter rainfall and the spatial distribution of this rainfall decline is influenced by regional scale topography in two of the three simulations. Winter rainfall reduction is consistent with the historical trend of declining rainfall in SWWA, which has been attributed in previous research to a reduction in the number of fronts passing over the region. The continuation of this trend is evident in all models by an increase in winter mean sea level pressure in SWWA, and a reduced number of winter front days. Winter rainfall does not show any marked variations in daily intensity.

The onset of green-up of plants has advanced in response to climate change. This advance has the potential to affect heat waves via biogeochemical and biophysical processes. Here a climate model was used to investigate only the biophysical feedbacks of earlier green-up on climate as the biogeochemical feedbacks have been well addressed. Earlier green-up by 5 to 30 days amplifies spring warming in Europe, especially heat waves, but makes few differences to heat waves in summer. This spring warming is most noticeable within 30 days of advanced green-up and is associated with a decrease in low- and middle-layer clouds and associated increases of downward short wave and net radiation. We find negligible differences in the Southern Hemisphere and low latitudes of the Northern Hemisphere. Our results provide an estimate of the level of skill necessary in phenology models to avoid introducing biases in climate simulations.

A high resolution (5 km), single initialization, 30 year (1970–1999) Weather Research and Forecast regional climate model (RCM) ensemble for southwest Western Australia (SWWA) is evaluated. The article focuses on the ability of the RCM to simulate winter cold fronts, which are the main source of rainfall for the region, and assesses the spatial and temporal characteristics of climate extremes within the region's cereal crop growing season. To explore uncertainty, a four-member ensemble was run, using lateral boundary conditions from general circulation models (GCMs) of the Coupled Model Intercomparison Project Phase 3; ECHAM5, Model for Interdisciplinary Research on Climate 3.2 (MIROC 3.2), Community Climate System Model version 3 (CCSM3) and Commonwealth Scientific and Industrial Research Organisation (CSIRO) mk3.5. Simulations are evaluated against gridded observations of temperature and precipitation and atmospheric conditions are compared to a simulation using ERA-Interim reanalysis boundary conditions, which is used as a surrogate truth. Results show that generally, the RCM simulations were able to represent the climatology of SWWA well, however differences in the positioning of the subtropical high pressure belt were apparent which influenced the number of fronts traversing the region and hence winter precipitation biases. Systematic temperature biases were present in some ensemble members and the RCM was found to be colder than the driving GCM in all simulations. Biases impacted model skill in representing temperature extremes and this was particularly apparent in the MIROC-forced simulation, which was the worst performing RCM for both temperature and precipitation. The dynamical causes of the biases are explored and findings show that nonetheless, the RCM provides added value, particularly in the spatio-temporal representation of wet season rainfall.

We implement a new stomatal conductance scheme, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLEv2.0.1) land surface model. Coupled land–atmosphere simulations are then performed using CABLEv2.0.1 within the Australian Community Climate and Earth Systems Simulator (ACCESSv1.3b) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5–1.0 mm day−1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology of warm extremes and improve existing biases by 10–20 %. The bias in minimum temperatures is however degraded but, overall, this is outweighed by the improvement in maximum temperatures as there is a net improvement in the diurnal temperature range in this region. In other regions such as parts of South and North America where ACCESSv1.3b has known large positive biases in both maximum and minimum temperatures (~ 5 to 10 °C), the new scheme degrades this bias by up to 1 °C. We conclude that, although several large biases remain in ACCESSv1.3b for temperature extremes, the improvements in the global climate model over large parts of the boreal forests during the Northern Hemisphere summer which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system.

The Weather Research and Forecasting (WRF) model was used to simulate fire weather for the south-west of Western Australia (SWWA) over multiple decades at a 5-km resolution using lateral boundary conditions from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA)-Interim reanalysis. Simulations were compared with observations at Australian Bureau of Meteorology meteorological stations and the McArthur Forest Fire Danger Index (FFDI) was used to quantify fire weather. Results showed that, overall, the WRF reproduced the annual cumulative FFDI at most stations reasonably well, with most biases in the FFDI ranging between –600 and 600. Biases were highest at stations within the metropolitan region. The WRF simulated the geographical gradients in the FFDI across the domain well. The source of errors in the FFDI varied markedly between the different stations, with no one particular variable able to account for the errors at all stations. Overall, this study shows that the WRF is a useful model for simulating fire weather for SWWA, one of the most fire-prone regions in Australia.

Due to an oversight in the production process, the article “Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia” was published with a mistake in the affiliations. The affiliation of co-authors C. B. Schaaf and Q. Sun should be School for the Environment, University of Massachusetts Boston, Boston, MA, USA, and of coauthor D. Mocko should be Science Applications International Corporation at NASA Goddard Space Flight Center, NASA, Greenbelt, MD, USA.

Heat waves have profoundly impacted biota globally over the past decade, especially where their ecological impacts are rapid, diverse, and broad-scale. Although usually considered in isolation for either terrestrial or marine ecosystems, heat waves can straddle ecosystems of both types at subcontinental scales, potentially impacting larger areas and taxonomic breadth than previously envisioned. Using climatic and multi-species demographic data collected in Western Australia, we show that a massive heat wave event straddling terrestrial and maritime ecosystems triggered abrupt, synchronous, and multi-trophic ecological disruptions, including mortality, demographic shifts and altered species distributions. Tree die-off and coral bleaching occurred concurrently in response to the heat wave, and were accompanied by terrestrial plant mortality, seagrass and kelp loss, population crash of an endangered terrestrial bird species, plummeting breeding success in marine penguins, and outbreaks of terrestrial wood-boring insects. These multiple taxa and trophic-level impacts spanned >300,000 km2—comparable to the size of California—encompassing one terrestrial Global Biodiversity Hotspot and two marine World Heritage Areas. The subcontinental multi-taxa context documented here reveals that terrestrial and marine biotic responses to heat waves do not occur in isolation, implying that the extent of ecological vulnerability to projected increases in heat waves is underestimated.

The role of land–atmosphere coupling in modulating the impact of land-use change (LUC) on regional climate extremes remains uncertain. Using the Weather and Research Forecasting Model, this study combines the Global Land–Atmosphere Coupling Experiment with regional LUC to assess the combined impact of land–atmosphere coupling and LUC on simulated temperature extremes. The experiment is applied to an ensemble of planetary boundary layer (PBL) and cumulus parameterizations to determine the sensitivity of the results to model physics. Results show a consistent weakening in the soil moisture–maximum temperature coupling strength with LUC irrespective of the model physics. In contrast, temperature extremes show an asymmetric response to LUC dependent on the choice of PBL scheme, which is linked to differences in the parameterization of vertical transport. This influences convective precipitation, contributing a positive feedback on soil moisture and consequently on the partitioning of the surface turbulent fluxes. The results suggest that the impact of LUC on temperature extremes depends on the land–atmosphere coupling that in turn depends on the choice of PBL. Indeed, the sign of the temperature change in hot extremes resulting from LUC can be changed simply by altering the choice of PBL. The authors also note concerns over the metrics used to measure coupling strength that reflect changes in variance but may not respond to LUC-type perturbations.

The dynamics and large-scale drivers of heat wave (HW) events in Australia are well documented. However, the influence of soil moisture in modulating HWs is largely unexplored. We focus here on a recent significant HW event in southeast Australia that preceded the Black Saturday bushfires (3-7 February 2009). During this period, the southeast of Australia experienced unprecedented warm conditions, which, in conjunction with high fuel load and mesoscale weather conditions, led to devastating bushfires. We examine how different initial soil moisture conditions with lead times of 5, 10, and 15 days prior to the event would have altered its overall dynamics at the continental scale. We show that at short lead times (5 days), the influence of perturbing soil moisture is mostly linear. Decreasing (increasing) soil moisture increases (decreases) maximum temperatures, associated with an intensification of the upper-level anticyclone. The effect of increasing soil moisture is more nonlinear than decreasing soil moisture with increasing lead time; namely, increasing soil moisture can also lead to an increase in maximum temperature over some parts of the domain, rather than a decrease everywhere. At lead times of up to 15 days, the imposed perturbation in soil moisture, mostly confined to the Tropics, is essentially lost such that the impact on maximum temperatures on the day of the event cannot be related to the sign of the imposed perturbation in soil moisture. Our results highlight the importance of accurate soil moisture estimates in capturing the intensity and spatial extent of HW events in southeast Australia, but only at relatively short lead times.

Stomatal conductance (gs) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We constrained the key model parameter "g1", which represents plant water use strategy, by PFT, based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960–1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal model, in conjunction with PFT parameterisations, resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance against upscaled data products was not degraded, but did not noticeably reduce existing model–data biases. We identified assumptions relating to the coupling of the vegetation to the atmosphere and the parameterisation of the minimum stomatal conductance as areas requiring further investigation in both CABLE and potentially other LSMs. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.

The authors evaluate a 30-yr (1981–2010) Weather Research and Forecast (WRF) Model regional climate simulation over the southwest of Western Australia (SWWA), a region with a Mediterranean climate, using ERA-Interim boundary conditions. The analysis assesses the spatial and temporal characteristics of climate extremes, using a selection of climate indices, with an emphasis on metrics that are relevant for forestry and agricultural applications. Two nested domains at 10- and 5-km resolution are examined, with the higher-resolution simulation resolving convection explicitly. Simulation results are compared with a high-resolution, gridded observational dataset that provides daily rainfall, minimum temperatures, and maximum temperatures. Results show that, at both resolutions, the model is able to simulate the daily, seasonal, and annual variation of temperature and precipitation well, including extreme events. The higher-resolution domain displayed significant performance gains in simulating dry-season convective precipitation, rainfall around complex terrain, and the spatial distribution of frost conditions. The high-resolution domain was, however, influenced by grid-edge effects in the southwestern margin, which reduced the ability of the domain to represent frontal rainfall along the coastal region. On the basis of these results, the authors feel confident in using the WRF Model for regional climate simulations for the SWWA, including studies that focus on the spatial and temporal representation of climate extremes. This study provides a baseline climatological description at a high resolution that can be used for impact studies and will also provide a benchmark for climate simulations driven by general circulation models.

Land surface albedo, the fraction of incoming solar radiation reflected by the land surface, is a key component of the Earth system. This study evaluates snow-free surface albedo simulations by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Satellite Pour L'Observation de la Terre (SPOT) albedo. We compare results from offline simulations over the Australian continent. The control simulation has prescribed background snow-free and vegetation-free soil albedo derived from MODIS whilst the experiments use a simple parameterisation based on soil moisture and colour, originally from the Biosphere Atmosphere Transfer Scheme (BATS), and adopted in the Common Land Model (CLM). The control simulation, with prescribed soil albedo, shows that CABLE simulates overall albedo over Australia reasonably well, with differences compared to MODIS and SPOT albedos within ±0.1. Application of the original BATS scheme, which uses an eight-class soil classification, resulted in large differences of up to −0.25 for the near-infrared (NIR) albedo over large parts of the desert regions of central Australia. The use of a recalibrated 20-class soil colour classification from the CLM, which includes a higher range for saturated and VIS (visible) and NIR soil albedos, reduced the underestimation of the NIR albedo. However, this soil colour mapping is tuned to CLM soil moisture, a quantity which is not necessarily transferrable between land surface models. We therefore recalibrated the soil color map using CABLE's climatological soil moisture, which further reduced the underestimation of the NIR albedo to within ±0.15 over most of the continent as compared to MODIS and SPOT albedos. Small areas of larger differences of up to −0.25 remained within the central arid parts of the continent during summer; however, the spatial extent of these large differences is substantially reduced as compared to the simulation using the default eight-class uncalibrated soil colour map. It is now possible to use CABLE coupled to atmospheric models to investigate soil-moisture–albedo feedbacks, an important enhancement of the model.

The severity of recent droughts and heat waves have been linked to land-atmosphere feedbacks. However, investigations of how these feedbacks are influenced by land use and land cover change (LULCC) are limited. Using the Weather and Research Forecasting model with an ensemble framework of planetary boundary layer and cumulus parameterization schemes, we combine the Global Land Atmosphere Coupling Experiment methodology with LULCC to assess how LULCC affects land-atmosphere coupling strength for maximum temperature over Australia. We find a statistically significant decrease in soil moisture-temperature coupling over regions where forest changes to crops, which was consistent across the implemented model physics and background climate. This was associated with a decrease in the ensemble mean variance suggesting that LULCC influences regional climate variability via changes in the regional scale hydrology and surface energy balance. Our results highlight the need to consider land surface changes and coupling strength in combination, rather than in isolation.

Regional climate models are sensitive to the forcing data used, as well as different model physics options. Additionally, the behaviour of physics parameterisations may vary depending on the location of the domain due to different climatic regimes. In this study, we carry out a sensitivity analysis of the weather research and forecasting model to different driving data and model physics options over a 10-km resolution domain in the southwest of Western Australia, a region with Mediterranean climate. Simulations are carried out on a seasonal time-scale, in order to better inform future long-term regional climate simulations for this region. We show that the choice of radiation scheme had a strong influence on both temperature and precipitation; the choice of planetary boundary layer scheme has a particularly large influence on minimum temperatures; and, the choice of cumulus scheme or more complex micro-physics did not strongly influence precipitation simulations. More importantly, we show that the same radiation scheme, when used with different driving data, can lead to different results.

Climate extremes, such as heat waves and heavy precipitation events, have large impacts on ecosystems and societies. Climate models provide useful tools for studying underlying processes and amplifying effects associated with extremes. The Australian Community Climate and Earth System Simulator (ACCESS) has recently been coupled to the Community Atmosphere Biosphere Land Exchange (CABLE) model. We examine how this model represents climate extremes derived by the Expert Team on Climate Change Detection and Indices (ETCCDI) and compare them to observational data sets using the AMIP framework. We find that the patterns of extreme indices are generally well represented. Indices based on percentiles are particularly well represented and capture the trends over the last 60 years shown by the observations remarkably well. The diurnal temperature range is underestimated, minimum temperatures (TMIN) during nights are generally too warm and daily maximum temperatures (TMAX) too low in the model. The number of consecutive wet days is overestimated, while consecutive dry days are underestimated. The maximum consecutive 1-day precipitation amount is underestimated on the global scale. Biases in TMIN correlate well with biases in incoming longwave radiation, suggesting a relationship with biases in cloud cover. Biases in TMAX depend on biases in net shortwave radiation as well as evapotranspiration. The regions and season where the bias in evapotranspiration plays a role for the TMAX bias correspond to regions and seasons where soil moisture availability is limited. Our analysis provides the foundation for future experiments that will examine how land-surface processes contribute to these systematic biases in the ACCESS modelling system.

Leaf area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. The authors investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange version 1.4b (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI dataset is generated using the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980–2008) are carried out at 25-km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly varying LAI datasets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes, but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from −90% to 60%. Plant function types (PFTs) with high absolute LAI and low interannual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, while those with lower absolute LAI and higher interannual variability, such as croplands, were more sensitive. The authors show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of terrestrial carbon fluxes, especially for PFTs with high interannual variability. The study highlights that accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence, this will become critical in quantifying the uncertainty in future changes in primary production.

The authors use a sophisticated coupled land–atmosphere modeling system for a Southern Hemisphere subdomain centered over southeastern Australia to evaluate differences in simulation skill from two different land surface initialization approaches. The first approach uses equilibrated land surface states obtained from offline simulations of the land surface model, and the second uses land surface states obtained from reanalyses. The authors find that land surface initialization using prior offline simulations contribute to relative gains in subseasonal forecast skill. In particular, relative gains in forecast skill for temperature of 10%–20% within the first 30 days of the forecast can be attributed to the land surface initialization method using offline states. For precipitation there is no distinct preference for the land surface initialization method, with limited gains in forecast skill irrespective of the lead time. The authors evaluated the asymmetry between maximum and minimum temperatures and found that maximum temperatures had the largest gains in relative forecast skill, exceeding 20% in some regions. These results were statistically significant at the 98% confidence level at up to 60 days into the forecast period. For minimum temperature, using reanalyses to initialize the land surface contributed to relative gains in forecast skill, reaching 40% in parts of the domain that were statistically significant at the 98% confidence level. The contrasting impact of the land surface initialization method between maximum and minimum temperature was associated with different soil moisture coupling mechanisms. Therefore, land surface initialization from prior offline simulations does improve predictability for temperature, particularly maximum temperature, but with less obvious improvements for precipitation and minimum temperature over southeastern Australia.

The city of Melbourne in southeast Australia experiences frequent heatwaves and their frequency, intensity and duration are expected to increase in the future. In addition, Melbourne is the fastest growing city in Australia and experiencing rapid urban expansion. Heatwaves and urbanization contribute in intensifying the Urban Heat Island (UHI) effect, i.e., higher temperatures in urban areas as compared to surrounding rural areas. The combined effects of UHI and heatwaves have substantial impacts on the urban environment, meteorology and human health, and there is, therefore, a pressing need to investigate the effectiveness of different mitigation options. This study evaluates the effectiveness of urban vegetation patches such as mixed forest (MF), combination of mixed forest and grasslands (MFAG), and combination of mixed shrublands and grasslands (MSAG) in reducing UHI effects in the city of Melbourne during one of the most severe heatwave events. Simulations are carried out by using the Weather Research and Forecasting (WRF) model coupled with the Single Layer Urban Canopy Model (SLUCM). The fractions of vegetated patches per grid cell are increased by 20%, 30%, 40% and 50% using the mosaic method of the WRF model. Results show that by increasing fractions from 20 to 50%, MF reduces near surface (2 m) UHI (UHI2) by 0.6–3.4 °C, MSAG by 0.4–3.0 °C, and MFAG by 0.6–3.7 °C during the night, but there was no cooling effect for near surface temperature during the hottest part of the day. The night-time cooling was driven by a reduction in storage heat. Vegetated patches partitioned more net radiation into latent heat flux via evapotranspiration, with little to no change in sensible heat flux, but rather, a reduction in the storage heat flux during the day. Since the UHI is driven by the release of stored heat during the night, the reduced storage heat flux results in reductions in the UHI. The reductions of the UHI2 varied non-linearly with the increasing vegetated fractions, with lager fractions of up to 50% resulting in substantially larger reductions. MF and MFAG were more effective in reducing UHI2 as compared to MSAG. Vegetated patches were not effective in improving HTC during the day, but a substantial improvement of HTC was obtained between the evening and early morning particularly at 2100 local time, when the thermal stress changes from strong to moderate. Although limited to a single heatwave event and city, this study highlights the maximum potential benefits of using vegetated patches in mitigating the UHI during heatwaves and the overall principles are applicable elsewhere. Keywords: UHI mitigation, Urban vegetation, Green Infrastructure, Heatwave, WRF-SLUCM

Stomatal conductance links plant water use and carbon uptake and is a critical process for the land surface component of climate models. However, stomatal conductance schemes commonly assume that all vegetation with the same photosynthetic pathway use identical plant water use strategies whereas observations indicate otherwise. Here, we implement a new stomatal scheme derived from optimal stomatal theory and constrained by a recent global synthesis of stomatal conductance measurements from 314 species, across 56 field sites. Using this new stomatal scheme, within a global climate model, subtantially increases the intensity of future heatwaves across Northern Eurasia. This indicates that our climate model has previously been under-predicting heatwave intensity. Our results have widespread implications for other climate models, many of which do not account for differences in stomatal water-use across different plant functional types and hence, are also likely under projecting heatwave intensity in the future.