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.

The use of small grid-connected wind turbines in the built environment is increasing. The international wind turbine design standard is based on open terrain sites, but in the built environment, the turbulence intensity is much higher than in open terrain and can lead to premature fatigue of turbines This paper compares the turbulence power spectral densities from direct measurement on the rooftop of Bunning Group Ltd’s warehouse at Port Kennedy, Western Australia, with predictions from the von Karman and Kaimal spectra used by turbulence models in the design standard. Both model spectra under estimate the magnitude of the measured values for all wind components although the Kaimal spectra provides more realistic values in terms of predicting the turbulence power spectra of lateral and vertical wind components in the built-environment. A corrected Kaimal model is proposed that has good agreement with measured values and can be viewed as a first step towards upgrading the existing standard with a dedicated design model for the built environment.

Climate change and anthropogenic land use are increasingly affecting the resilience of natural ecosystems. In Mediterranean ecoregions, forests and woodlands have shown progressive declines in health. This study focuses on the decline of an endemic woodland tree species, Eucalyptus wandoo (wandoo), occurring in the biodiversity hotspot of southwest Western Australia. We determined the change in health of wandoo stands between 2002 and 2008 across its geographic and climatic range, and associated this change in health with non-biotic variables focusing on: (1) fragment metrics; (2) topography; (3) soil characteristics; and (4) climate. Only fragment metrics and climate variables were found to be significantly related to the observed change in health. Stands that were small with high perimeter/area ratios were found to be most sensitive to health declines. Recent increases in autumn temperatures and decreases in annual rainfall were negatively affecting health of wandoo most prominently in the low rainfall zone of its climatic range. Together, these results suggest the onset of range contraction for this ecologically important species, which is likely to be exacerbated by projected future changes in climate. Our results emphasize the importance of establishing monitoring programs to identify changes in health and decline trends early to inform management strategies, particularly in the sensitive Mediterranean ecoregions.

Extreme and persistent reductions in annual precipitation and an increase in the mean diurnal temperature range have resulted in patch scale forest mortality following the summer of 2010–2011 within the Forest study area near Perth, Western Australia. The impacts of 20 bioclimatic indicators derived from temperature, precipitation and of actual and potential evapotranspiration are quantified. We found that spatially aggregated seasonal climatologies across the study area show 2011 with an annual mean of 17.7 °C (± 5.3 °C) was 1.1 °C warmer than the mean over recent decades (1981–2011,- 16.6 °C ± 4.6 °C) and the mean has been increasing over the last decade. Compared to the same period, 2010–2011 summer maximum temperatures were 1.4 °C (31.6 °C ± 2.0 °C) higher and the annual mean diurnal temperature range (Tmax−Tmin) was 1.6 °C higher (14.7 °C ± 0.5 °C). In 2009, the year before the forest mortality began, annual precipitation across the study area was 69% less (301 mm ± 38 mm) than the mean of 1981–2010 (907 mm ± 69 mm). Using Système Pour l'Observation de la Terre mission 5 (SPOT-5) satellite imagery captured after the summer of 2010–2011 we map a broad scale forest mortality event across the Forested study area. This satellite-climatology based methodology provides a means of monitoring and mapping similar forest mortality events- a critical contribution to our understanding the dynamical bioclimatic drivers of forest mortality events.

Quantifying dieback in forests is useful for land managers and decision makers seeking to explain spatial disturbances and understand the cyclic nature of forest health. Crown condition is assessed as reference to dieback in terms of the density, transparency, extent and in-crown distribution of foliage. At 20 sites in the Yalgorup National Park, Western Australia, a total of 80 Eucalyptus gomphocephala crowns were assessed both in situ (2008) and using two acquisitions (2008 and 2010) of airborne imagery. Each tree was assessed using four crown-condition indices: Crown Density, Foliage Transparency, the Crown Dieback Ratio and Epicormic Index combined into a single index called the Total Crown Health Index (TCHI). The airborne imagery is like value calibrated then classified and modelled using in situ canopy condition assessments resulting in a quantification of crown-condition change over time. Comparison of Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI) and a novel Red-Edge Extrema Index (REEI) suggests that the latter is more suited to classification applications of this type.

Abstract. Individual crown condition of Eucalyptus gomphocephala was assessed using two classification models to understand changes in forest health through space and time. Using high resolution (0.5 m) digital multispectral imagery, predictor variables were derived from textural and spectral variance of all pixels inside the crown area. The results estimate crown condition as a surrogate for tree health against the total crown health index. Crown condition is derived from combining ground-based crown assessment techniques of density, transparency, dieback, and the regrowth of foliage. This object-based approach summarizes the pixel data into mean crown indices assigned to crown objects which became the carrier of information. Models performed above expectations, with a significant weighted Cohen’s kappa ( κ > 0.60 and p < 0.001 ) using 70% of available data. Using in situ data for model development, crown condition was predicted forwards (2010) and backwards (2007) in time, capturing trends in crown condition and identifying decline in the healthiest between 2008 and 2010. The results confirm that combining spectral and textural information increased model sensitivity to small variations in crown condition. The methodology provides a cost-effective means for monitoring crown condition of this or other eucalypt species in native and plantation forests.

Observations from near‐simultaneous atmospheric soundings released over contrasting land surfaces in the southwest of Western Australia during December 2005 (austral summer) and August 2007 (late austral winter or early spring) have shown higher planetary boundary layer (PBL) heights over native vegetation as compared to agricultural land. The large‐eddy simulation technique is used to investigate the drivers behind these observed differences in PBL, and sensitivity tests are carried out with modified soil moisture and vegetation cover. It is shown that the differences in PBL for the December case are mainly driven by the change in vegetation cover, while a soil moisture gradient also played a role for the August case. The mixing diagram approach is used to further quantify the relative contributions of surface and entrainment fluxes on the growth of the PBL and it is shown that, while dry‐air entrainment plays an important role in PBL development, it is the higher surface Bowen ratio which drives the more vigorous PBL development over the native vegetation. It is also shown that the enhanced PBL development over the native vegetation leads to the preferential formation of shallow convective clouds for the August case. Copyright © 2012 Royal Meteorological Society

Approximately 13 million hectares of native vegetation in southwest Australia has been replaced by non-native, rain-fed agricultural species over the last several decades. Prior studies link land use change to reduction in convective cloudiness and precipitation in this region. However, recent aircraft observations also show that land use change and associated effects on ground water hydrology impacts the atmospheric CCN distribution, with distinct differences found between adjacent areas of native vegetation and agriculture. Over the agricultural areas, substantially higher concentrations of very small aerosols were observed during the morning hours. Smaller concentrations of larger aerosols were found over the native vegetation area in the morning. Even though the smaller particles over the agricultural area grow and the size distribution is shifted to higher particle size ranges in the afternoon, they are smaller and more numerous compared to those on the native vegetation area. Aircraft observations also show differences in cloud particle size distribution consistent with differences in aerosols, with larger droplet sizes existing in higher concentrations over the native vegetation region. The source of the small particles in the agricultural area was traced to salt lakes. Shallow rooted vegetation in the agricultural area, causing the rise of the water table and altering the lake geochemistry is a potential reason for the enhanced aerosol emissions over the lakes in the agricultural area. The impact of differing atmospheric CCN on cloud precipitation is being explored using numerical modeling and results from this analysis will also be presented.

The importance of ecological management for reducing the vulnerability of biodiversity to climate change is increasingly recognized, yet frameworks to facilitate a structured approach to climate adaptation management are lacking. We developed a conceptual framework that can guide identification of climate change impacts and adaptive management options in a given region or biome. The framework focuses on potential points of early climate change impact, and organizes these along two main axes. First, it recognizes that climate change can act at a range of ecological scales. Secondly, it emphasizes that outcomes are dependent on two potentially interacting and countervailing forces: (1) changes to environmental parameters and ecological processes brought about by climate change, and (2) responses of component systems as determined by attributes of resistance and resilience. Through this structure, the framework draws together a broad range of ecological concepts, with a novel emphasis on attributes of resistance and resilience that can temper the response of species, ecosystems and landscapes to climate change. We applied the framework to the world's largest remaining Mediterranean-climate woodland, the 'Great Western Woodlands' of south-western Australia. In this relatively intact region, maintaining inherent resistance and resilience by preventing anthropogenic degradation is of highest priority and lowest risk. Limited, higher risk options such as fire management, protection of refugia and translocation of adaptive genes may be justifiable under more extreme change, hence our capacity to predict the extent of change strongly impinges on such management decisions. These conclusions may contrast with similar analyses in degraded landscapes, where natural integrity is already compromised, and existing investment in restoration may facilitate experimentation with higher risk options.

Land clearing for agricultural purposes in southwest Australia has created a landscape where a 750 km rabbit-proof fence separates 13 million hectares of croplands from the remnant native vegetation to the east. The Bunny Fence Experiment (BuFex) was conducted in the vicinity of the intended vermin-proof boundary in December 2005 and August 2007. The experiment examined the role of land cover change (LCC) on the preferential formation of clouds over the native vegetation that often terminates along the vermin-proof fence as well as the regional rainfall reduction observed in this region. Observations and numerical model analysis show that the formation and development of the west coast trough (WCT), which is a synoptic-scale feature that initiates spring and summertime convection, is impacted by land cover change and that the cloud fields induced by the WCT would extend further west in the absence of the LCC. The surface convergence patterns associated with the wintertime WCT circulation is substantially altered by LCC, due to changes in both WCT dynamics and surface aerodynamic roughness, leading to a rainfall decrease to the west of the rabbit fence. It is found that the LCC in southwest Australia is indeed responsible for preferential formation of clouds over native vegetation and contributes to the observed rainfall reduction in this region.”

The southwest of Western Australia (SWWA) is a region of significant cereal production, with the main crops being winter grown wheat and barley.The most important factors influencing wheat growth and production are temperature extremes and precipitation, and hence, it is critical to have an understanding of how these environmental factors have changed in the past, and how they are likely to change in the future.One method of addressing this important research question is by using regional climate models (RCMs) to dynamically downscale re-analysis products and/or output form Global Circulation Models to a fine resolution.One tool which is being increasingly used for this purpose is the Weather Research and Forecasting Model (WRF) Advanced Research (ARW).However, like any modeling system, WRF-ARW requires thorough testing before it is implemented to carry out long-term climate runs.This paper examines the influence of different input data sources, as well as model physics options on simulated precipitation and maximum and minimum temperatures in SWWA by comparing the simulations against an observational gridded dataset.It is found that running WRF3.3 with the 1.0 × 1.0 degree National Center for Environmental Prediction Final analysis (NCEP-FNL), as compared to the 2.5 × 2.5 degree NCEP / National Center for Atmospheric Research (NCEP/NCAR or NNRP) results in much improved simulations of precipitation and temperatures.Using the National Oceanic and Atmospheric Administration 1.0 × 1.0 degree resolution sea surface temperature (SST) dataset does not result in markedly different results as compared to using the NNRP surface skin temperatures as SSTs.Using the Betts-Miller-Jajic (BMJ) scheme for cumulus/convection parameterisation rather than the more widely used Kain-Fritsch (KF) scheme results in slightly higher errors for precipitation, and no marked change in temperatures.The latest version of the Rapid Radiative Transfer Model (RRTMG) is found to result in improved simulations of maximum and minimum temperatures, as compared to the RRTM, Community Atmosphere Model (CAM) 3.0, and Dudhia schemes.Use of the Asymmetric Convective Model as the planetary boundary-layer scheme rather than the more widely used Yonsei University scheme results in over-prediction of maximum and minimum temperatures.

Remote sensing of vegetation condition using high resolution digital multispectral imagery (DMSI) is an option for land managers interested in quantifying the distribution and extent of dieback in native forest. Crown condition is assessed as reference to the physical structure and foliage (i.e. density, transparency, extent and in-crown distribution) of a tree crown. At 20 sites in the Yalgorup National Park, Western Australia, a total of 80 (Eucalyptus gomphecephala) crowns are assessed both in-situ and using 2 acquisitions (2008 and 2010) of airborne DMSI. Each tree was assessed using four crown-condition indices: Crown Density, Foliage transparency, and the Crown Dieback Ratio and Epicormic Index. DMSI data is trained against canopy condition assessment data from 2008, crown condition is predicted using only spectral data. Comparison of DMSI derived Normalized Diプerence Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and a novel Red Edge Extrema Index (REEI) suggests the REEI is more suited to classification applications of this type.

The south-west of Western Australia has experienced significant land-cover change as well as a decline in rainfall. Given that most precipitation in the region results from frontal passages, the impact of land-cover change on the dynamics of cold fronts is explored using the Regional Atmospheric Modeling System version 6.0. Frontal simulations are evaluated against high resolution atmospheric soundings, station observations, and gridded rainfall analyses and shown to reproduce the qualitative features of cold fronts. Land-cover change results in a decrease in total frontal precipitation through a decrease in boundary-layer turbulent kinetic energy and vertically integrated moisture convergence, and an increase in wind speed within the lower boundary layer. Such processes contribute to reduced convective rainfall under current vegetation cover.

Agricultural extension evolved from, and has drawn on, the disciplines of social psychology, education and rural sociology. However, agricultural extension has not remained connected with developments in psychological, educational and sociological theory. This paper proposes that there are critical lessons to be learned by aligning extension practices to developments in social science theory and practice. The theory of planned behaviour (TPB) from social psychology proposes that behaviour is partly explained by: people's attitudes towards the expected results of changing behaviour and how highly valued this is; norms related to the behaviour and degree to which people want to comply with these norms; and the degree of perceived control people have about conducting the behaviour, i.e. their perceptions of their ability to do it. While current agricultural extension practice already focuses on some of these areas through attempts to influence attitudes and improve skills and knowledge, application of this theory to agricultural extension may provide more rigour, more direction on the types of attitudes to influence and the way in which to do this. This could lead to improved rates of behaviour change as a result of extension programs and has the potential to be incorporated into both planning and evaluating these programs. In addition, while adult learning theory is regularly applied in agricultural extension, self regulation of learning (SRL) theory has not been implemented or trialled. SRL theory has been applied in environmental education in order to successfully increase rates of behaviour change and there may be lessons for agricultural extension. This theory also has many similarities to adult learning theory as it relates to: active involvement of learners in setting their learning goals; choices in the way they will learn; self-monitoring of achievement; and maintaining motivation to achieve goals. Three key learnings are: the theory of planned behaviour may provide some rigour to attempts to influence behaviour change in farmers; self regulation of learning theory has been successfully applied to environmental education; and while there are similarities between SRL and adult learning theories, SRL theory needs to be tested in extension.