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Anthropogenic climate change is changing the Earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose of investigating future hazards. BARPA-R, a limited-area model, has a 17 km horizontal grid spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA5 reanalysis. Here, an assessment of this evaluation experiment is provided. Performance-based evaluation results are benchmarked against ERA5, with comparable performance between the free-running BARPA-R simulations and observationally constrained reanalysis interpreted as a good result. First, an examination of BARPA-R's representation of Australia's surface air temperature, precipitation, and 10 m winds finds good performance overall, with biases including a 1 ∘ C cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm per month in inland Australia. Recent trends in daily maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in precipitation show underestimated wetting in northern Australia. Precipitation and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10 m winds are improved over ERA5 in six out of eight of the Australian regions considered. Secondly, the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the South Pacific Convergence Zone (SPCZ), the Northwest Cloudband, and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extratropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 global climate models (GCMs). [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is changing the earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose to investigate future hazards. BARPA-R, a limited area model, has a 17 km horizontal grid-spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA-5 reanalysis. Here, an assessment of this evaluation experiment is provided. First, an examination of BARPA-R's representation of Australia's surface air temperature, rainfall and 10-m winds finds good performance overall, with biases including a 1K cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm/month in inland Australia. Recent trends in diurnal maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in rainfall show underestimated wetting in northern Australia. Rainfall and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10-metre winds are improved over ERA5 in six out of eight of the Australian regions considered. The second section of the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the SPCZ, Northwest Cloud-Bands and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extra-tropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 GCMs. [ABSTRACT FROM AUTHOR]

Cadastre 2034 is a National Strategy developed by the Intergovernmental Committee on Surveying and Mapping (ICSM) for cadastral reform and innovation for Australia and one of the goals is to develop a federated cadastral system. It states to define governance and administration on a federal level by unifying the existing systems with uniform standards, policies, guidelines and legislation and to allow further work towards a global cadastre. The aim of this research paper is to explore the behaviours and attitudes of New South Wales (NSW) cadastre towards a federated cadastral system assessing the best practice of federated cadastre global cases that may be applied locally in Australia. Mixed Methods Research (MMR) methodology was used, involving both quantitative and qualitative research to understand, identify and frame the cadastral data to determine and analyse the key issues and factors in implementing a federated cadastral system in New South Wales (NSW). A literature review, a questionnaire survey and interviews were used to collect the quantitative and qualitative data. A sequential MMR design framework was used a questionnaire survey followed by interviews. The questionnaire was sent out to 215 industry and government participants and resulted 71 completed surveys. Semi-structured interviews were conducted with 9 participants. The linking of quantitative and qualitative data occurred at the design-level, where results from the first phase were used to build the second phase of research design.It was explored that strong historical foundations, regressive reaction of governments and institutions, and a lack of understanding of the significance of cadastral reform were the key hindering factors to develop a federated cadastral system in NSW. The resulting analysis could be contributed to a better implementation of a federated cadastral system in NSW benefitting private, and public institutions. [ABSTRACT FROM AUTHOR]

Recent decades have seen an exponential rise in the application of machine learning in geoscience. Fundamental differences distinguish geoscience data from most other data types. Geoscience datasets are typically multi-dimensional, and contain 1-D (drillholes), 2-D (maps or cross-sections), and 3-D volumetric and point data (models/voxels). Geoscience data quality is a product of its resolution and the precision of the methods used to acquire it. The dimensionality, resolution, and precision of each layer within a geoscience dataset translates to limitations in spatiality, scale and uncertainty of resulting interpretations. Historically, geoscience datasets were overlaid cartographically, to incorporate subjective, experience-driven knowledge, and variances in scale, and resolution. The nuances and limitations that underpin the reliability of automated interpretation are well understood by geoscientists, but are rarely appropriately transferred to data science. However, for true integration of geoscience data, such issues cannot be overlooked without consequence. To apply data analytics to complex geoscience data (e.g., hydrothermal mineral systems) effectively, methodologies must be used that characterise the system quantitatively, using collocated analyses, at a common scale. This paper provides research and exploration insights from an innovative district-wide, scale-integrated, geoscience data project, which analysed 1,590 samples from 23 mineral deposits and prospects across the Cloncurry District, Queensland, Australia. Ten different analytical techniques, including density, magnetic susceptibility, remanent magnetisation, anisotropy of magnetic susceptibility, radiometrics, conductivity, scanning electron microscopy (SEM)-based automated mineralogy, geochemistry, and short-wave infrared (SWIR) hyperspectral data with 561 columns of scale-integrated data (+2151 columns of SWIR). All data were collected on 2 cm x 2.5 cm sample cylinders; a scale at which the confidence in coupling of data from techniques can be high. These data are integrated by design, to eliminate the need to downscale coarser measurements via assumptions, inferences, inversions, and interpolations. This scale-consistent approach is critical to the quantitative characterisation of mineral systems and has numerous applications to mineral exploration, such as linking alteration paragenesis with structural controls and petrophysical zonation. [ABSTRACT FROM AUTHOR]

The Millennium Drought lasted more than a decade and is notable for causing persistent shifts in the relationship between rainfall and runoff in many southeastern Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanation for observed changes in catchment behaviour is still lacking. Originating from a large multi-disciplinary workshop, this paper presents and evaluates a range of hypothesised process explanations of flow response to the Millennium Drought. The hypotheses consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. The hypotheses are assessed against evidence both temporally (e.g. why was the Millennium Drought different to previous droughts?) and spatially (e.g. why did rainfall–runoff relationships shift in some catchments but not in others?). Thus, the strength of this work is a large-scale assessment of hydrologic changes and potential drivers. Of 24 hypotheses, 3 are considered plausible, 10 are considered inconsistent with evidence, and 11 are in a category in between, whereby they are plausible yet with reservations (e.g. applicable in some catchments but not others). The results point to the unprecedented length of the drought as the primary climatic driver, paired with interrelated groundwater processes, including declines in groundwater storage, altered recharge associated with vadose zone expansion, and reduced connection between subsurface and surface water processes. Other causes include increased evaporative demand and harvesting of runoff by small private dams. Finally, we discuss the need for long-term field monitoring, particularly targeting internal catchment processes and subsurface dynamics. We recommend continued investment in the understanding of hydrological shifts, particularly given their relevance to water planning under climate variability and change. [ABSTRACT FROM AUTHOR]

The current process of issuing planning permits mostly relies on checking Land-use Regulations (LuRs) against two-dimensional (2D) analogue or digital proposed development plans. Checking three-dimensional (3D) LuRs within 2D proposed development plans results in challenges for decision-makers to understand LuRs' limits and the impacts of the proposed developments on existing buildings in their surrounded proximity. Given the advancement of 3D geospatial technologies, to overcome such challenges and facilitate the process of issuing planning permits, 3D digital approaches should be developed for effective 3D storage, analysis, and visualisation of 3D LuRs and detection of their potential conflicts. This paper, as part of an internship project with Bentley systems, aims to design and develop a web-based 3D visualisation prototype called iTwin4PP for issuing planning permits using Bentley iTwin platform. This prototype first demonstrates how 3D LuRs related to planning approval can be modelled automatically in 3D and combined with an integrated BIM-GIS environment including BIM designs of the proposed developments and GIS models of planning/city-data. Then, the prototype considers the possibility of 3D spatial analyses (especially proximity analysis) for verifying 3D LuRs automatically to detect potential spatio-semantic conflicts that may arise between modelled LuRs and physical/planning objects. Five LuRs subject to planning approval in Victorian jurisdiction, in Australia, including height limits, energy efficiency protection, overshadowing open space, noise impacts, and overlooking are highlighted. While these LuRs are specific to Melbourne's planning scheme ordinance, we believe that the prototype and encountered challenges in integrating different sources of information especially BIM and GIS, modelling 3D LuRs, and detecting their potential conflicts are common and can be applied in other jurisdictions. [ABSTRACT FROM AUTHOR]

High-resolution bathymetry forms critical datasets for marine geoscientists. It can be used to characterize the seafloor and its marine habitats, to understand past sedimentary records, and even to support the development of offshore engineering projects. Most methods to acquire bathymetry data are costly and can only be practically deployed in relatively small areas. It is therefore critical to develop cost-effective and advanced techniques to produce regional-scale bathymetry datasets. This paper presents an integrated workflow that builds on satellites images and 3D seismic surveys, integrated with historical depth soundings, to generate regional high-resolution digital elevation models (DEMs). The method was applied to the southern half of Australia's North West Shelf and led to the creation of new high-resolution bathymetry grids, with a resolution of 10 × 10 m in nearshore areas and 30 × 30 m elsewhere. The vertical and spatial accuracy of the datasets have been assessed using open-source Laser Airborne Depth Sounder (LADS) and multibeam echosounder (MBES) surveys as a reference. The comparison of the datasets indicates that the seismic-derived bathymetry has a vertical accuracy better than 1 m + 2 % of the absolute water depth, while the satellite-derived bathymetry has a depth accuracy better than 1 m + 5 % of the absolute water depth. This 30 × 30 m dataset constitutes a significant improvement of the pre-existing regional 250 × 250 m grid and will support the onset of research projects on coastal morphologies, marine habitats, archaeology, and sedimentology. All source datasets are publicly available, and the methods are fully integrated into Python scripts, making them readily applicable elsewhere in Australia and around the world. The regional digital elevation model and the underlying datasets can be accessed at 10.26186/144600 (Lebrec et al., 2021). [ABSTRACT FROM AUTHOR]

This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS (Australia) comprises data for 222 unregulated catchments, combining hydrometeorological time series (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. The CAMELS-AUS catchments have been monitored for decades (more than 85 % have streamflow records longer than 40 years) and are relatively free of large-scale changes, such as significant changes in land use. Rating curve uncertainty estimates are provided for most (75 %) of the catchments, and multiple atmospheric datasets are included, offering insights into forcing uncertainty. This dataset allows users globally to freely access catchment data drawn from Australia's unique hydroclimatology, particularly notable for its large interannual variability. Combined with arid catchment data from the CAMELS datasets for the USA and Chile, CAMELS-AUS constitutes an unprecedented resource for the study of arid-zone hydrology. CAMELS-AUS is freely downloadable from 10.1594/PANGAEA.921850 (Fowler et al., 2020a). [ABSTRACT FROM AUTHOR]

Accurate estimation of terrestrial water storage (TWS) at a high spatiotemporal resolution is important for reliable assessments of regional water resources and climate variability. Individual components of TWS include soil moisture, snow, groundwater, and canopy storage and can be estimated from the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. The spatial resolution of CABLE is currently limited to 0.5 ∘ by the resolution of soil and vegetation data sets that underlie model parameterizations, posing a challenge to using CABLE for hydrological applications at a local scale. This study aims to improve the spatial detail (from 0.5 to 0.05 ∘) and time span (1981–2012) of CABLE TWS estimates using rederived model parameters and high-resolution meteorological forcing. In addition, TWS observations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are assimilated into CABLE to improve TWS accuracy. The success of the approach is demonstrated in Australia, where multiple ground observation networks are available for validation. The evaluation process is conducted using four different case studies that employ different model spatial resolutions and include or omit GRACE data assimilation (DA). We find that the CABLE 0.05 ∘ developed here improves TWS estimates in terms of accuracy, spatial resolution, and long-term water resource assessment reliability. The inclusion of GRACE DA increases the accuracy of groundwater storage (GWS) estimates and has little impact on surface soil moisture or evapotranspiration. Using improved model parameters and improved state estimations (via GRACE DA) together is recommended to achieve the best GWS accuracy. The workflow elaborated on in this paper relies only on publicly accessible global data sets, allowing the reproduction of the 0.05 ∘ TWS estimates in any study region. [ABSTRACT FROM AUTHOR]

The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S-5P) satellite, launched in 2017, measures the total column concentration of the trace gas Carbon Monoxide (CO) daily on a global scale and at a high spatial resolution of 7×7 km², improved to 5.5×7 km² in August 2019. The TROPOMI observations show plumes of CO due to localized CO emissions from industrial sources and biomass burning. In this paper, we quantify these CO emissions for biomass burning by an automated algorithm, APE, to detect plumes and quantify the CO emission rate using cross-sectional flux method. Furthermore, the influence of a constant and a varying plume height in downwind direction on emissions is investigated and algorithm uncertainties are quantified. The VIIRS active fire data in conjunction with the TROPOMI CO datasets is used to identify fires and the fire locations. Then, an automated plume detection algorithm using traditional image processing algorithms is developed and utilized to identify plumes. For these plumes, the emission rate is estimated by the cross10 section flux method at three different plume heights. The first two are constant plume heights at a 100 m and an IS4FIRES injection height from Global Fire Assimilation System. And the last one is a varying plume height in downwind direction. A 3D Lagrangian model is used to simulate tracer particles where the source locations for the simulation are based on the VIIRS fire counts and IS4FIRES injection height. 3D velocities at 137 model levels (ERA5) are utilized to simulate tracer particles. We demonstrate the quality and validity of our automated approach by investigating biomass burning events and their emissions for Australia on Oct 2019 and the US on Sept 2020. A total of 110 and 31 individual fire plumes in Australia and the US, respectively were detected and their emissions estimated. The emissions were severely under-predicted and negative for 11 cases when based on constant plume height of 100 m compared to emissions based on varying plume height. Furthermore, the effect of the changing plume height in downwind direction on the emission estimate compared to emissions from constant IS4FIRES plume height was minor as 124 cases are found to have emission variation less than 10%. However, we were able to identify several cases where the flux estimates become more reliable with varying plume height. Thus, the varying plume height in downwind direction is considered for the automated algorithm. The cross-section flux method is found to have an uncertainty of 38% in one of the idealized cases. However, overall uncertainty of the algorithm is difficult to quantify as conditions for each fire are unique. [ABSTRACT FROM AUTHOR]

Point clouds acquired through laser scanning techniques are applied in the three-dimensional modelling of vegetation. They provide the three-dimensional coordinates of geometric surfaces with attributes. However, raw point clouds are unstructured and do not provide semantic, geometric, or topological information about an object. Voxelisation is a method for structuring point clouds. It is a generalisation of point clouds and therefore the voxel size and the voxel neighbourhood play a critical role in the processing. This research explores the influence of voxelisation of point clouds acquired of heathland in Australia and how it influences the three-dimensional modelling and the representation of important heathland structure using different voxel sizes and voxel connectivities. Voxel sizes of 0.4 m, 0.6 m, 1.0 m, 1.2 m and 1.6 m with a voxel neighbourhood connectivity of 6, 18 and 26 are examined for three-dimensional modelling and segmentation of heathland vegetation in Australia. The results indicate that the choice of voxel size and the voxel connectivity influence the representation of important heathland parameters. A smaller voxel size of 0.4 m provides a detailed representation of mallee structure while the the processing time is longer compared to a larger voxel size. While a larger voxel size produces blobs while the processing speed is shorter. The results from the voxel neighbourhood connectivity represent a stronger voxel connectivity of 26-connected voxels suitable for heathland modelling rather than a 6-connected voxels. [ABSTRACT FROM AUTHOR]

The increasing number of aging infrastructures has drawn attention among the industry as the results caused by critical infrastructure failure could be destructive. It is essential to monitor the infrastructure assets and provide timely maintenance. However, one of the crucial problems is that the budget allocated to the maintenance stage is much less than that for the designing and construction stages. The cost of labor, equipment, and vehicles are significant. Therefore, it is impossible to perform a thorough inspection by human inspectors over each asset. A more efficient method will be needed to solve this problem. This paper aims to provide an automatic approach to detecting and measuring the dimensions of minor cracks that appear on concrete structures with a noisy background. This research also investigates the relationship between image pixel size, accuracy, detection rate of cracks, and shooting distance of images. The proposed method will be able to reduce the cost and increase accuracy. A case study was performed on a concrete sewer with cracks distributed on the surface in Sydney, New South Wales, Australia. [ABSTRACT FROM AUTHOR]

Cut-off lows (COLs) exhibit diverse structures and lifecycles, ranging from confined upper-tropospheric systems to deep, multi-level vortex structures. While COL climatologies are well documented, the mechanisms driving their deepening remain unclear. To bridge this gap, a novel track matching algorithm applied to ERA-Interim reanalysis investigates the vertical extent of Southern Hemisphere COLs. Composite analysis based on structure and eddy kinetic energy budget differentiates four COL categories: shallow, deep, weak, and strong, revealing similarities and disparities. Deep, strong COLs concentrate around Australia and the southwestern Pacific, peaking in autumn and spring, while shallow, weak COLs are more common in summer and closer to the Equator. Despite their differences, both contrasting types evolve energetically via anticyclonic Rossby wave breaking. The distinct roles of jet streams in affecting COL types are addressed: intense polar front jets correlate with more deep COLs, whereas stronger subtropical jets relate to fewer shallow COLs. The COL deepening typically occurs in the presence of a robust upstream polar front jet, which enhances ageostrophic flux convergence and baroclinic processes. The subtropical jet positively correlates with COL intensity but weakens when considering the seasonality, suggesting uncertainties in this relationship. Additionally, we highlight the significance of diabatic processes in COL deepening, addressing their misrepresentation in reanalysis and emphasizing the need for more observational and modelling studies to refine the energetic framework. [ABSTRACT FROM AUTHOR]

Numerous studies have demonstrated that significant global changes in wave and storm surge conditions have occurred over recent decades and are expected to continue out to at least 2100. This raises the question of whether the observed and projected changes in waves and storm surges will impact coastlines in the future. Previous global-scale analyses of these issues have been inconclusive. This study investigates the south-east coast of Australia over a period of 26 years (1988–2013). Over this period, this area has experienced some of the largest changes in wave climate of any coastal region globally. The analysis uses high-resolution hindcast data of waves and storm surge together with satellite observations of shoreline change. All datasets have been previously extensively validated against in situ measurements. The data are analysed to determine trends in each of these quantities over this period. The coastline is partitioned into regions and spatial consistency between trends in each of the quantities investigated. The results show that beaches along this region appear to have responded to the increases in wave energy flux and changes in wave direction. This has enhanced non-equilibrium longshore drift. Long sections of the coastline show small but measurable recession before sediment transported along the coast is intercepted by prominent headlands. The recession is largest where there are strong trends in increasing wave energy flux and/or changes in wave direction, with recession rates of up to 1 myr-1. Although this is a regional study, this finding has global implications for shoreline stability in a changing climate. [ABSTRACT FROM AUTHOR]

Describing and classifying a landscape for environmental impact and risk assessment purposes is a non-trivial challenge because this requires region-specific landscape classifications that cater for region-specific impacts. Assessing impacts on ecosystems from the extraction of water resources across large regions requires a causal link between landscape features and their water requirements. We present the rationale and implementation of an ecohydrological classification for regions where coal mine and coal seam gas developments may impact on water. Our classification provides the essential framework for modelling the potential impact of hydrological changes from future coal resource developments at the landscape level. We develop an attribute-based system that provides representations of the ecohydrological entities and their connection to landscape features and make use of existing broad-level classification schemes into an attribute-based system. We incorporate a rule set with prioritisation, which underpins risk modelling and makes the scheme resource efficient, where spatial landscape or ecosystem classification schemes, developed for other purposes, already exist. A consistent rule set and conceptualised landscape processes and functions allow for the combination of diverse data with existing classification schemes. This makes the classification transparent, repeatable and adjustable, should new data become available. We apply the approach in three geographically different regions, with widely disparate information sources, for the classification, and provide a detailed example of its application. We propose that it is widely applicable around the world for linking ecohydrology to environmental impacts. [ABSTRACT FROM AUTHOR]

Floods are the most common and destructive disasters around the globe, which becomes more challenging in coastal areas due to higher population density and catchment areas relative to floods in an inland area. For effective coastal flood management to reduce flood adverse impacts it is necessary to investigate the flooding processes and their joint interaction in a coastal area. This paper selected the Brisbane River Estuary, Australia as an example, and the MIKE 21 model is applied to investigate the effects of mesh resolution on the flood discharge and to explores compound flooding by computing variances in coastal flood assessments resulting from a separation of tidal and riverine processes. The statistical results showed that the Nash-Sutcliffe coefficient, E of water level are varied from 0.84 to 0.95 and the model simulated the 2011 flood extent results agreed with 90 % accuracy with the observed flood extent. Five mesh resolutions cases were analyzed and the result found that the finer mesh resolution Case 5 was more appropriate for calculating the peak discharge with 2.7 % with estimated discharge. Compound flood event simulation results emphasized that not considering the interaction of various flooding drivers caused 0.62 m and 0.12 m reduction in the flood levels at Jindalee and Brisbane city gauges, and uncertainties in flood extent. Simulated results of flood at Brisbane city gauge, showed that 2011 and 2013 floods with storm surge scenario 4 demonstrate, the increase in flood level to be 12 % and 34 % respectively. The results recommend flooding assessment by using mesh convergence with joint probability of compound flood under future storm surge for planning and management of coastal projects. [ABSTRACT FROM AUTHOR]

The Australian Bureau of Meteorology has developed a national hydrological projections (NHP) service for Australia. The NHP aimed to provide nationally consistent hydrological projections across jurisdictional boundaries to support planning of water-dependent industries. NHP is complementary to those previously produced by federal and state governments, universities, and other organisations for limited geographical domains. The projections comprise an ensemble of application-ready bias-corrected climate model data, derived hydrological projections at daily temporal and 0.05° × 0.05° spatial resolution for the period 1960–2099, and two emission scenarios (Representative Concentration Pathway (RCP) 4.5 and RCP8.5). The spatial resolution of the projections matches that of gridded historical reference data used to perform the bias correction and the Bureau of Meteorology's operational gridded hydrological model. Three bias correction techniques were applied to four CMIP5 global climate models (GCMs), and one method was applied to a regional climate model (RCM) forced by the same four GCMs, resulting in a 16-member ensemble of bias-corrected GCM data for each emission scenario. The bias correction was applied to fields of precipitation, minimum and maximum temperature, downwelling shortwave radiation, and surface winds. These variables are required inputs to the Bureau of Meteorology's landscape water balance hydrological model (AWRA-L), which was forced using the bias-corrected GCM and RCM data to produce a 16-member ensemble of hydrological output. The hydrological output variables include root zone soil moisture (moisture in the top 1 m soil layer), potential evapotranspiration, and runoff. Here we present an overview of the production of the hydrological projections, including GCM selection, bias correction methods and their evaluation, technical aspects of their implementation, and examples of analysis performed to construct the NHP service. The data are publicly available on the National Computing Infrastructure (10.25914/6130680dc5a51, Bureau of Meteorology, 2021), and a user interface is accessible at https://awo.bom.gov.au/products/projection/ (last access: 24 November 2023). [ABSTRACT FROM AUTHOR]

Spatial and temporal variations in the level of dust activity can provide valuable information for policymaking and climate research. Recently, Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products have been successfully used for retrieving dust aerosol optical depth (DAOD), especially over bright dust source areas, and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) aerosol reanalysis provides DAOD and additionally other dust-aerosol-related parameters. In this study, spatial and temporal variations in dust activity in Australia were analyzed using MODIS and MERRA-2 combined (M&M) DAOD and MERRA-2 near-surface dust concentrations and estimated PM 10 for the period 1980–2020. Validation results show that M&M DAOD has an expected error of ±(0.016+0.15τ) compared to the ground observations at the AErosol RObotic NETwork (AERONET) dust storms on populated areas sites. MERRA-2 near-surface dust concentrations show a power-law relationship with visibility data collected at meteorological stations with an r2 value from 0.18 to 0.44, and the estimated MERRA-2 PM 10 shows similar temporal variations and correlates with ground-based PM 10 data with an r2 value from 0.14 to 0.44 at six selected stations in Australia. Moreover, MERRA-2 horizontal dust flux shows the same major dust pathways as those in previous studies and similar dust emissions and deposition areas identified using ground-based observations. Dust events based on DAOD over eastern Australia are concentrated in the north in December, are concentrated in the south in February, and can occur anywhere in January. Near-surface dust concentration was found to be the highest (over 200 µ g m -3) over the center of Lake Eyre basin in central Australia and radially decreased toward the coast to below 20 µ g m -3 via the two main pathways in the southwest and northeast. The ratio of near-surface dust concentration to PM 10 shows a similar spatial pattern. Total dust emission was estimated to be 40 Mt (megatonnes) per year over the period 1980–2020, of which nearly 50 % was deposited on land and the rest exported away from the Australian continent. [ABSTRACT FROM AUTHOR]

Estimating groundwater recharge rates is important to understand and manage groundwater. Numerous studies have used collated recharge datasets to understand and project regional- or global-scale groundwater recharge rates. However, recharge estimation methods all have distinct assumptions, quantify different recharge components and operate over different temporal scales. We use over 200 000 groundwater chloride measurements to estimate groundwater recharge rates using an improved chloride mass balance (CMB) method across Australia. Groundwater recharge rates were produced stochastically using gridded chloride deposition, runoff and precipitation datasets. After filtering out groundwater recharge rates where the assumptions of the method may have been compromised, 98 568 estimates of recharge were produced. The resulting groundwater recharge rates and 17 spatial datasets were integrated into a random forest regression algorithm, generating a high-resolution (0.05°) model of groundwater recharge rates across Australia. The regression reveals that climate-related variables, including precipitation, rainfall seasonality and potential evapotranspiration, exert the most significant influence on groundwater recharge rates, with vegetation (the normalised difference vegetation index or NDVI) also contributing significantly. Importantly, the mean values of both the recharge point dataset (43.5 mm yr -1) and the spatial recharge model (22.7 mm yr -1) are notably lower than those reported in previous studies, underscoring the prolonged timescale of the CMB method, the potential disparities arising from distinct recharge estimation methodologies and limited averaging across climate zones. This study presents a robust and automated approach to estimate recharge using the CMB method, offering a unified model based on a single estimation method. The resulting datasets, the Python script for recharge rate calculation and the spatial recharge models collectively provide valuable insights for water resource management across the Australian continent, and similar approaches can be applied globally. [ABSTRACT FROM AUTHOR]

In drought-prone Australia, multi-year droughts have detrimental impacts on both the natural environment and human societies. For responsible water management, we need a thorough understanding of the full range of variability in multi-year droughts and how this might change in a warming world. But research into the long-term frequency, persistence, and severity of Australian droughts is limited. This is partly due to the length of the observational record, which is short relative to the timescales of hydroclimatic variability and hence may not capture the range of possible variability. Using simulations of Australian precipitation over the full past millennium (850–2000), we characterise the nature of multi-year meteorological droughts across Australia and include a particular focus on the Murray–Darling Basin (MDB), the largest agricultural region in Australia. We find that simulated Australian droughts in the 20th century (1900–2000) are within the bounds of pre-industrial natural variability in terms of drought intensity, severity, and frequency. A tendency for droughts to last longer in southwestern and eastern Australia (including the MDB) in the 20th century, compared with the pre-industrial period, suggests an emerging anthropogenic influence, consistent with projected rainfall changes in these regions. Large volcanic eruptions tend to promote drought-free intervals in the MDB. Model simulations of droughts over the last millennium suggest that future droughts across Australia could be much longer than what was experienced in the 20th century, even without any human influence. With the addition of anthropogenic climate change, which favours drought conditions across much of southern Australia due to reduced cool-season rainfall, it is likely that future droughts in Australia will exceed recent historical experience. [ABSTRACT FROM AUTHOR]

We present the first national-scale lead (Pb) isotope maps of Australia based on surface regolith for five isotope ratios, 206Pb/204Pb , 207Pb/204Pb , 208Pb/204Pb , 207Pb/206Pb , and 208Pb/206Pb , determined by single-collector sector field inductively coupled plasma mass spectrometry after an ammonium acetate leach followed by aqua regia digestion. The dataset is underpinned principally by the National Geochemical Survey of Australia (NGSA) archived floodplain sediment samples. We analysed 1219 samples (0–10 cm depth, <2 mm grain size), collected near the outlet of 1119 large catchments covering 5.647×106 km 2 (∼75% of Australia). The samples consist of mixtures of the dominant soils and rocks weathering in their respective catchments (and possibly those upstream) and are therefore assumed to form a reasonable representation of the average isotopic signature of those catchments. This assumption was tested in one of the NGSA catchments, within which 12 similar samples were also taken; results show that the Pb isotope ratios of the NGSA catchment outlet sediment sample are close to the average of the 12 upstream sub-catchment samples. National minimum, median, and maximum values were 15.56, 18.84, and 30.64 for 206Pb/204Pb ; 14.36, 15.69, and 18.01 for 207Pb/204Pb ; 33.56, 38.99, and 48.87 for 208Pb/204Pb ; 0.5880, 0.8318, and 0.9847 for 207Pb/206Pb ; and 1.4149, 2.0665, and 2.3002 for 208Pb/206Pb , respectively. The new dataset was compared with published bedrock and ore Pb isotope data, and it was found to dependably represent crustal elements of various ages from Archaean to Phanerozoic. This suggests that floodplain sediment samples are a suitable proxy for basement and basin geology at this scale, despite various degrees of transport, mixing, and weathering experienced in the regolith environment, locally over protracted periods of time. An example of atmospheric Pb contamination around Port Pirie, South Australia, where a Pb smelter has operated since the 1890s, is shown to illustrate potential environmental applications of this new dataset. Other applications may include elucidating details of Australian crustal evolution and mineralisation-related investigations. The new regolith Pb isotope dataset for Australia is publicly available (Desem et al., 2023; 10.26186/5ea8f6fd3de64). [ABSTRACT FROM AUTHOR]

Wildfires can have a significant impact on air quality in Australia during severe burning seasons, but incomplete knowledge of the injection heights of smoke plumes poses a challenge for quantifying smoke exposure. In this study, we use two approaches to quantify the fractions of fire emissions injected above the planetary boundary layer (PBL), and we further investigate the impact of plume injection fractions on daily mean surface concentrations of fine particulate matter (PM 2.5) from wildfire smoke in key cities over northern and southeastern Australia from 2009 to 2020. For the first method, we rely on climatological, monthly mean vertical profiles of smoke emissions from the Integrated Monitoring and Modelling System for wildland fires (IS4FIRES) together with assimilated PBL heights from NASA Modern-Era Retrospective Analysis for Research and Application (MERRA) version 2. For the second method, we develop a novel approach based on the Multi-angle Imaging SpectroRadiometer (MISR) observations and a random forest, machine learning model that allows us to directly predict the daily plume injection fractions above the PBL in each grid cell. We apply the resulting plume injection fractions quantified by the two methods to smoke PM 2.5 concentrations simulated by the Stochastic Time-Inverted Lagrangian Transport (STILT) model in target cities. We find that characterization of the plume injection heights greatly affects estimates of surface daily smoke PM 2.5 , especially during severe wildfire seasons, when intense heat from fires can loft smoke high in the troposphere. However, using climatological injection profiles cannot capture well the spatiotemporal variability in plume injection fractions, resulting in a 63 % underestimation of daily fire emission fluxes injected above the PBL in comparison with those fluxes derived from MISR injection fractions. Our random forest model successfully reproduces the daily injected fire emission fluxes against MISR observations (R2=0.88 , normalized mean bias = 10 %) and predicts that 27 % and 45 % of total fire emissions rise above the PBL in northern and southeastern Australia, respectively, from 2009 to 2020. Using the plume behavior predicted by the random forest method also leads to better model agreement with observed surface PM 2.5 in several key cities near the wildfire source regions, with smoke PM 2.5 accounting for 5 %–52 % of total PM 2.5 during fire seasons from 2009 to 2020. [ABSTRACT FROM AUTHOR]

The new mckelveyite group mineral, alicewilsonite-(YLa), Na 2 Sr 2 YLa(CO 3) 6 ⋅ 3H 2 O, was found together with kamphaugite-(Y), paratooite-(Y), bastnäsite-(La), and decrespignyite-(Y) coating along fractures in dolomite at the Paratoo copper mine, South Australia, Australia. It occurs as pale pink to colourless pseudohexagonal tabular crystals up to 150 µ m in size. The streak is white; the lustre is vitreous. The mineral has no cleavage. Dcalc is 3.37 g cm -3. Alicewilsonite-(YLa) is optically biaxial (-), α = 1.556(2), β= 1.582(2), γ= 1.592(2), 2V (meas.) = 60(2)°, 2V (calc.) = 63° (589 nm). The IR spectrum is reported. The composition (wt %, average of seven analyses) is Na 2 O 7.43, CaO 2.00, SrO 18.43, BaO 1.64, Y 2 O 3 9.59, La 2 O 3 11.74, Pr 2 O 3 1.29, Nd 2 O 3 5.74, Sm 2 O 3 0.44, Eu 2 O 3 0.09, Gd 2 O 3 0.95, Dy 2 O 3 1.15, Ho 2 O 3 0.25, Er 2 O 3 0.89, Yb 2 O 3 0.29, CO 2 29.78, H 2 O 6.18, total 97.88. The empirical formula calculated on the basis of six cations with 3 H 2 O molecules is as follows: Na 2.10 Ca 0.31 Sr 1.56 Ba 0.10 Y 0.74 La 0.63 Pr 0.07 Nd 0.30 Sm 0.03 Eu 0.01 Gd 0.04 Dy 0.05 Ho 0.01 Er 0.04 Yb 0.01 (CO 3) 5.92 (H 2 O) 3. The mineral is triclinic, P 1, a= 8.9839(2), b= 8.9728(3), c= 6.7441(2) Å, α= 102.812(2)°, β= 116.424(2)°, γ= 60.128(2)°, and V= 422.17(2) Å 3 and Z= 1. The strongest reflections of the powder X-ray diffraction pattern [ d ,Å(I)(hkl)] are 6.03(43)(001), 4.355(100)(1 1‾ 0, 2‾1‾ 1, 120), 4.020(30)(1‾ 11, 210, 1‾2‾ 1), 3.188(29)(2‾1‾ 2, 1 1‾ 1, 121), 2.819(96)(002, 1‾ 12, 211, 1‾2‾ 2), 2.592(40)(3‾ 01, 030, 3‾3‾ 1), 2.228(33)(2‾ 21, 4‾2‾ 1, 2‾4‾ 1). 2.011(36)(2‾ 22, 003, 420, 2‾4‾ 2), 1.9671(32)(3‾ 03, 301, 0 3‾ 2, 032, 3‾3‾ 3, 331). The crystal structure was solved and refined from single-crystal X-ray diffraction data (R1= 0.058). [ABSTRACT FROM AUTHOR]

A deep learning model designed for time series predictions, the long short-term memory (LSTM) architecture, is regularly producing reliable results in local and regional rainfall–runoff applications around the world. Recent large-sample hydrology studies in North America and Europe have shown the LSTM model to successfully match conceptual model performance at a daily time step over hundreds of catchments. Here we investigate how these models perform in producing monthly runoff predictions in the relatively dry and variable conditions of the Australian continent. The monthly time step matches historic data availability and is also important for future water resources planning; however, it provides significantly smaller training datasets than daily time series. In this study, a continental-scale comparison of monthly deep learning (LSTM) predictions to conceptual rainfall–runoff (WAPABA model) predictions is performed on almost 500 catchments across Australia with performance results aggregated over a variety of catchment sizes, flow conditions, and hydrological record lengths. The study period covers a wet phase followed by a prolonged drought, introducing challenges for making predictions outside of known conditions – challenges that will intensify as climate change progresses. The results show that LSTM models matched or exceeded WAPABA prediction performance for more than two-thirds of the study catchments, the largest performance gains of LSTM versus WAPABA occurred in large catchments, the LSTMs struggled less to generalise than the WAPABA models (e.g. making predictions under new conditions), and catchments with few training observations due to the monthly time step did not demonstrate a clear benefit with either WAPABA or LSTM. [ABSTRACT FROM AUTHOR]

The intensity and frequency of extreme ocean temperature events, such as marine heatwaves (MHWs) and marine cold spells (MCSs), are expected to change as our oceans warm. Little is known about marine extremes in Australian coastal waters, particularly below the surface. Here we introduce a multi-decadal observational record of extreme ocean temperature events starting in the 1940s and 1950s between the surface and the bottom (50–100 m) at four long-term coastal sites around Australia: the Australian Multi-Decadal Ocean Time Series EXTreme (AMDOT-EXT) data products (10.26198/wbc7-8h24,). The data products include indices indicating the timing of extreme warm and cold temperature events, their intensity and the corresponding temperature time series and climatology thresholds. We include MHWs, MCSs and shorter-duration heat spikes and cold spikes. For MHWs and MCSs, which are defined as anomalies above the daily varying 90th and 10th percentiles, respectively, and lasting more than 5 d, we also provide further event information, such as their category and onset and decline rates. The four data products are provided as CF-compliant NetCDF files, and it is our intention that they be updated periodically. It is advised that data users seek the latest data product version. Using these multi-decadal data products, we show the most intense and longest extreme temperature events at these sites, which have occurred below the surface. These data records highlight the value of long-term full water column ocean data for the identification of extreme temperature events below the surface. [ABSTRACT FROM AUTHOR]

The Last Glacial Maximum (LGM; ∼21 kyr ago) was the most recent time that the Earth experienced global maximum ice volume and minimum eustatic sea level. The climate changes over the Australian region at the LGM remain uncertain, including the extent of cooling in the arid interior, changes in the regional atmospheric circulations such as the tropical monsoon and mid-latitude westerlies, and changes in the balance between precipitation and evaporation. In this study, 13 climate model simulations that were included in the Paleoclimate Modelling Intercomparison Project (PMIP) Phases 3 and 4 are used to investigate regional climate (temperature, precipitation, and wind) over Australia at the LGM. The model simulations are compared with existing proxy records and other modelling studies. All models simulate consistent annual and seasonal cooling over the Australian region (defined as 0–45° S, 110–160° E) at the LGM compared to pre-industrial, with a multi-model mean 2.9 °C decrease in annual average surface air temperature over land at the LGM compared to pre-industrial. Models simulate a range of LGM precipitation anomalies over the region. Simulated precipitation changes over tropical Australasia appear to be driven by changes in circulation and moisture transport, which vary greatly between models. Surface moisture balance calculated from precipitation minus evaporation shows little change over much of the Australian land area at the LGM. Changes in the strength and position of the mid-latitude westerlies are uncertain, with wide model disagreement. These results indicate that climate model simulations do not show a robust response in either tropical or mid-latitude circulation to LGM boundary conditions, suggesting that caution is required when interpreting model output in this region. Further analysis based on model evaluation and quantitative model–proxy comparison is required to better understand the drivers of LGM climate and atmospheric circulation changes in this region. [ABSTRACT FROM AUTHOR]

The inter-dataset agreement of trends in subweekly near-surface (850 hPa) temperature variability over Southern Hemisphere midlatitude land masses is assessed among 12 global atmospheric reanalysis datasets. A comparison of the climatological temperature variance and dominant sources and sinks of the variance reveals that, except for NCEP-NCAR (R1) and NCEP-DOE (R2), there is a relatively good agreement for their magnitudes and spatial distributions during the satellite era (1980–2022), which indicates that the key features of subweekly variability are sufficiently well represented. A good agreement is noted for the positive trends found in subweekly variability over the satellite era affecting South Africa in September–October–November (SON) and South America in December–January–February (DJF). Although there is agreement in most of the reanalyses concerning the positive trend affecting Australia in SON, this has not yet emerged from the noise associated with interannual variability when considering only the satellite era. It is significant, however, when the period is extended (1954–2022) or limited to the most recent decades (1990–2022). The trends are explained primarily by a more efficient generation of subweekly temperature variance by horizontal temperature advection. This generation is also identified as a source of biases among the datasets. The trends are found to be reproduced even in those reanalyses that do not assimilate satellite data (JRA-55C) or that assimilate surface observations only (ERA-20C, 20CRv2c, and 20CRv3). [ABSTRACT FROM AUTHOR]

Record-breaking wildfires ravaged south-eastern Australia during the fire season 2019–2020. The intensity of the fires reached its paroxysmal phase at the turn of the year 2019–2020, when large pyro-cumulonimbi developed. Pyro-convective activity injected biomass burning aerosols and gases in the upper-troposphere–lower-stratosphere (UTLS), producing a long-lasting perturbation to the atmospheric composition and the stratospheric aerosol layer. The large absorptivity of the biomass burning plume produced self-lofting of the plume and thus modified its vertical dynamics and horizontal dispersion. Another effect of the in-plume absorption was the generation of compact smoke-charged anticyclonic vortices which ascended up to 35 km altitude due to diabatic heating. We use observational and modelling description of this event to isolate the main vortex from the dominant Southern Hemispheric biomass burning aerosol plume. Entering this information into an offline radiative transfer model, and with hypotheses on the absorptivity and the angular scattering properties of the aerosol layer, we estimate the radiative heating rates (HRs) in the plume and the vortex. We found that the hemispheric-scale plume produced a HR of 0.08±0.05 K d -1 (from 0.01 to 0.15 K d -1 , depending on the assumption on the aerosol optical properties), as a monthly average value for February 2020, which is strongly dependent on the assumptions on the aerosol optical properties and therefore on the plume ageing. We also found in-vortex HRs as large as 15–20 K d -1 in the denser sections of the main vortex (8.4±6.1 K d -1 on average in the vortex). Our results suggest that radiatively heated ascending isolated vortices are likely dominated by small-sized strongly absorbing black carbon particles. The hemispheric-scale and in-vortex HR estimates are consistent with the observed ensemble self-lofting (a few kilometres in 4 months) and the main isolated vortex rise (∼ 20 km in 2 months). Our results also show evidence of the importance of longwave emission in the net HR of biomass burning plumes. [ABSTRACT FROM AUTHOR]

The difficulties in using conventional mitigation techniques to maintain global-mean temperatures well below 2 ∘ C compared with pre-industrial levels have been well documented, leading to so-called "climate intervention" or "geoengineering" research whereby the planetary albedo is increased to counterbalance global warming and ameliorate some impacts of climate change. In the scientific literature, the most prominent climate intervention proposal is that of stratospheric aerosol injection (SAI), although proposals for marine cloud brightening (MCB) have also received considerable attention. In this study, we design a new MCB experiment (G6MCB) for the UKESM1 Earth-system model which follows the same baseline and cooling scenarios as the well-documented G6sulfur SAI scenario developed by the Geoengineering Model Intercomparison Project (GeoMIP), and we compare the results from G6MCB with those from G6sulfur. The deployment strategy used in G6MCB injects sea-salt aerosol into four cloudy areas of the eastern Pacific. This deployment strategy appears capable of delivering a radiative forcing of up to -1 W m -2 from MCB, but at higher injection rates, much of the radiative effect in G6MCB is found to derive from the direct interaction of the injected sea-salt aerosols with solar radiation, i.e. marine sky brightening (MSB). The results show that while G6MCB can achieve its target in terms of reducing high-end global warming to moderate levels, there are several side effects. Some are common to SAI, including overcooling of the tropics and residual warming of middle and high latitudes. Other side effects specific to the choice of the targeted MCB regions include changes in monsoon precipitation, year-round increases in precipitation over Australia and the maritime continent, and increased sea-level rise around western Australia and the maritime continent; these results are all consistent with a permanent and very strong La Niña-like response being induced in G6MCB. The results emphasize that considerable attention needs to be given to oceanic feedbacks for spatially inhomogeneous MCB radiative forcings. It should be stressed that the results are extremely dependent upon the strategy chosen for MCB deployment. As demonstrated by the development of SAI strategies which can achieve multiple temperature targets and ameliorate some of the residual impacts of climate change, much further work is required in multiple models to obtain a robust understanding of the practical scope, limitations, and pitfalls of any proposed MCB deployment. [ABSTRACT FROM AUTHOR]

Weather radars are increasingly being used to study the interaction between wildfires and the atmosphere, owing to the enhanced spatio-temporal resolution of radar data compared to conventional measurements, such as satellite imagery and in situ sensing. An important requirement for the continued proliferation of radar data for this application is the automatic identification of fire-generated particle returns (pyrometeors) from a scene containing a diverse range of echo sources, including clear air, ground and sea clutter, and precipitation. The classification of such particles is a challenging problem for common image segmentation approaches (e.g. fuzzy logic or unsupervised machine learning) due to the strong overlap in radar variable distributions between each echo type. Here, we propose the following two-step method to address these challenges: (1) the introduction of secondary, texture-based fields, calculated using statistical properties of gray-level co-occurrence matrices (GLCMs), and (2) a Gaussian mixture model (GMM), used to classify echo sources by combining radar variables with texture-based fields from (1). Importantly, we retain all information from the original measurements by performing calculations in the radar's native spherical coordinate system and introduce a range-varying-window methodology for our GLCM calculations to avoid range-dependent biases. We show that our method can accurately classify pyrometeors' plumes, clear air, sea clutter, and precipitation using radar data from recent wildfire events in Australia and find that the contrast of the radar correlation coefficient is the most skilful variable for the classification. The technique we propose enables the automated detection of pyrometeors' plumes from operational weather radar networks, which may be used by fire agencies for emergency management purposes or by scientists for case study analyses or historical-event identification. [ABSTRACT FROM AUTHOR]

At the end of December 2019 and beginning of 2020, massive firestorms in Australia formed pyrocumulonimbus clouds (pyroCbs) that acted like enormous smokestacks, pumping smoke to the upper troposphere and stratosphere. We study the smoke with data from four satellite-based sensors: the aerosol observation platforms CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), OMPS-LP (Ozone Mapping and Profiler Suite Limb Profiler), and OMPS-NM (Ozone Mapping and Profiler Suite Nadir Mapper) and water vapor retrievals from MLS (Microwave Limb Sounder). Smoke was lofted to the upper troposphere and stratosphere during two events and spread almost exclusively within the extratropics. Smoke from the first event, starting 29 December, was injected directly into the stratosphere by pyroCbs, causing a rapid initial increase in AOD (aerosol optical depth). CALIOP identifies a rapid decline in this stratospheric smoke (half-life: 10 d), not captured in previous studies of the Australian fires, indicating photochemical processing of organic aerosol. This decay rate is in line with model predictions of mid-tropospheric organic aerosol loss by photolytic removal and is in agreement with our estimates of decay rates after the North American fires in August 2017. PyroCbs from the second event, 4 January, injected small amounts of smoke directly into the stratosphere. Large amounts of smoke were injected to the upper troposphere, from where it ascended into the stratosphere during several weeks, forming a second peak in the aerosol load. Hence, we find that pyroCbs can impact the stratospheric aerosol load both via direct injection to the stratosphere and through injection of smoke to the upper troposphere from where the smoke ascends into the stratosphere. The stratospheric AOD from the second-event fires decreased more slowly than the AOD from the first event, likely due to a combination of photolytic loss starting already in the troposphere and continued supply of smoke from the upper troposphere offsetting the loss rate. Together these injections yielded a major increase in the aerosol load for almost 1 year. [ABSTRACT FROM AUTHOR]

We develop high-resolution (1 km) estimates of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) over the Australian continent for the period January 2003 to June 2022 by empirical upscaling of flux tower measurements. We compare our estimates with nine other products that cover the three broad categories that define current methods for estimating the terrestrial carbon cycle and assess if consiliences between datasets can point to the correct dynamics of Australia's carbon cycle. Our results indicate that regional empirical upscaling greatly improves upon the existing global empirical upscaling efforts, outperforms process-based models, and agrees much better with the dynamics of CO 2 flux over Australia as estimated by two regional atmospheric inversions. Our nearly 20-year estimates of terrestrial carbon fluxes revealed that Australia is a strong net carbon sink of -0.44 PgC yr -1 (interquartile range, IQR = 0.42 PgC yr -1) on average, with an inter-annual variability of 0.18 PgC yr -1 and an average seasonal amplitude of 0.85 PgC yr -1. Annual mean carbon uptake estimated from other methods ranged considerably, while carbon flux anomalies showed much better agreement between methods. NEE anomalies were predominately driven by cumulative rainfall deficits and surpluses, resulting in larger anomalous responses from GPP than ER. In contrast, we show that the long-term average seasonal cycle is dictated more by the variability in ER than GPP, resulting in peak carbon uptake typically occurring during the cooler, drier austral autumn and winter months. This new estimate of Australia's terrestrial carbon cycle provides a benchmark for assessment against land surface model simulations and a means for monitoring of Australia's terrestrial carbon cycle at an unprecedented high resolution. We call this new estimate of Australia's terrestrial carbon cycle "AusEFlux" (Australian Empirical Fluxes). [ABSTRACT FROM AUTHOR]

The El Niño–Southern Oscillation (ENSO) is a crucial driver of fire weather in Australia, with the correlation between ENSO and Australian fire weather having intensified over the past 2 decades. However, the underlying causes for this change have not been thoroughly investigated. In this study, we utilize reanalysis datasets and numerical model simulations to demonstrate that the Atlantic Multidecadal Oscillation (AMO) could potentially modulate the ENSO–Australian fire weather relationship. The correlation between ENSO and the Australian Fire Weather Index (FWI) increases from 0.17 to 0.70 as the AMO transitions from its negative to positive phase. This strengthening effect can be attributed to atmospheric teleconnection mechanisms. Specifically, the positive AMO phase, characterized by warming in the northern and tropical Atlantic, generates Rossby wave trains, leading to high-pressure systems over Australia. Consequently, local temperature and wind speed increase, while precipitation decreases. This signal, superimposed on ENSO, serves to amplify the ENSO effect on Australian fire weather. [ABSTRACT FROM AUTHOR]

Photosystem II (PS II) pesticides, recognized as a threat to ecological health, were targeted for reduction in sugarcane farming in Great Barrier Reef (GBR) catchments. Alternative herbicides, the non-PS II herbicides (including glyphosate, paraquat, 2,4-D, imazapic, isoxaflutole, metolachlor, and S-metolachlor), continue to be used in these catchments. However, the potential ecological fate, transport, and off-site environmental effects of non-PS II herbicides, with respect to their usage scheme, local rainfall patterns, and infiltration dynamics, have not been investigated previously. A vadose zone monitoring system, instrumented beneath sugarcane land in a GBR catchment, was applied for real-time tracing of pesticide migration across the unsaturated zone, past the root zone during 2017–2019. The regularly applied pesticides (fluroxypyr and isoxaflutole) exhibited substantial migration through the unsaturated zone. Within 1 month of application of fluroxypyr, it leached to 2.87 m depth in the vadose zone, with declining concentrations with depth. Isoxaflutole, which was applied yearly, was found only once, in November 2018, at 3.28 m depth in the soil profile. Other pesticides (imazapic, metolachlor, glyphosate, and haloxyfop) applied during the same period were not detected in the vadose zone. However, imidacloprid, which was not applied at the site during the monitored period, was detected across the entire vadose zone, revealing substantial resistance to degradation. The results show no evidence of any regularly applied pesticides in the site bores at the end of the study, indicating their ultimate degradation within the vadose zone before reaching the groundwater. [ABSTRACT FROM AUTHOR]

Multi-centennial records of past hydroclimate change are essential for understanding the resilience of ecosystems to climatic events in addition to guiding conservation and restoration efforts. Such data are also crucial for examining the long-term controls over regional hydroclimate and the inherent variability in extreme droughts and floods. Here, we present a 1750-year record of hydroclimate variability in the Coorong South Lagoon, South Australia, part of an internationally significant wetland system at the mouth of Australia's largest river, the Murray River. Oxygen isotope ratios were measured from Arthriticahelmsi bivalve shells preserved in sediments. The oxygen isotope record shows periods of persistent low and high moisture balance, from ∼500 to 1050 years and from ∼1300 to 1800 years, respectively, which is consistent with other hydroclimate reconstructions from the region. The range of oxygen isotope values in the sedimentary shells does not differ significantly from the estimated range of modern specimens from the present-day lagoon. These data suggest that the restricted and highly evaporated modern-day conditions are not markedly different to the pre-impacted state over the last 1750 years, although the absence of A. helmsi in the contemporary lagoon is likely a response to increased salinity, nutrient loading, and anoxia during the last century. These insights are potentially useful both in guiding management efforts to conserve and restore the Coorong Lagoon and for understanding long-term water resource availability in the region. [ABSTRACT FROM AUTHOR]

With a higher demand for lithium (Li), a better understanding of its concentration and spatial distribution is important to delineate potential anomalous areas. This study uses a digital soil mapping framework to combine data from recent geochemical surveys and environmental covariates that affect soil formation to predict and map aqua-regia-extractable Li content across the 7.6×106 km2 area of Australia. Catchment outlet sediment samples (i.e. soils formed on alluvial parent material) were collected by the National Geochemical Survey of Australia at 1315 sites, with both top (0–10 cm depth) and bottom (on average ∼60 –80 cm depth) catchment outlet sediments sampled. We developed 50 bootstrap models using a cubist regression tree algorithm for each depth. The spatial prediction models were validated on an independent Northern Australia Geochemical Survey dataset, showing a good prediction with a root mean square error of 3.32 mgkg-1 (which is 44.2 % of the interquartile range) for the top depth. The model for the bottom depth has yet to be validated. The variables of importance for the models indicated that the first three Landsat 30+ Barest Earth bands (red, green, blue) and gamma radiometric dose have a strong impact on the development of regression-based Li prediction. The bootstrapped models were then used to generate digital soil Li prediction maps for both depths, which could identify and delineate areas with anomalously high Li concentrations in the regolith. The predicted maps show high Li concentration around existing mines and other potentially anomalous Li areas that have yet to be verified. The same mapping principles can potentially be applied to other elements. The Li geochemical data for calibration and validation are available from de Caritat and Cooper (2011b; 10.11636/Record.2011.020) and Main et al. (2019; 10.11636/Record.2019.002), respectively. The covariate data used for this study were sourced from the Terrestrial Ecosystem Research Network (TERN) infrastructure, which is enabled by the Australian Government's National Collaborative Research Infrastructure Strategy (NCRIS; https://esoil.io/TERNLandscapes/Public/Products/TERN/Covariates/Mosaics/90m/ , last access: 6 December 2022; TERN, 2019). The final predictive map is available at 10.5281/zenodo.7895482 (Ng et al., 2023). [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) is the largest terrestrial carbon pool. SOC is composed of a continuous set of compounds with different chemical compositions, origins, and susceptibilities to decomposition that are commonly separated into pools characterised by different responses to anthropogenic and environmental disturbance. Here we map the contribution of three SOC fractions to the total SOC content of Australia's soils. The three SOC fractions, mineral-associated organic carbon (MAOC), particulate organic carbon (POC), and pyrogenic organic carbon (PyOC), represent SOC composition with distinct turnover rates, chemistry, and pathway formation. Data for MAOC, POC, and PyOC were obtained with near- and mid-infrared spectral models calibrated with measured SOC fractions. We transformed the data using an isometric-log-ratio (ilr) transformation to account for the closed compositional nature of SOC fractions. The resulting back-transformed ilr components were mapped across Australia. SOC fraction stocks for 0–30 cm were derived with maps of total organic carbon concentration, bulk density, coarse fragments, and soil thickness. Mapping was done by a quantile regression forest fitted with the ilr-transformed data and a large set of environmental variables as predictors. The resulting maps along with the quantified uncertainty show the unique spatial pattern of SOC fractions in Australia. MAOC dominated the total SOC with an average of 59 % ± 17 %, whereas 28 % ± 17 % was PyOC and 13 % ± 11 % was POC. The allocation of total organic carbon (TOC) to the MAOC fractions increased with depth. SOC vulnerability (i.e. POC/[MAOC+PyOC]) was greater in areas with Mediterranean and temperate climates. TOC and the distribution among fractions were the most influential variables in SOC fraction uncertainty. Further, the diversity of climatic and pedological conditions suggests that different mechanisms will control SOC stabilisation and dynamics across the continent, as shown by the model covariates' importance metric. We estimated the total SOC stocks (0–30 cm) to be 13 Pg MAOC, 2 Pg POC, and 5 Pg PyOC, which is consistent with previous estimates. The maps of SOC fractions and their stocks can be used for modelling SOC dynamics and forecasting changes in SOC stocks as a response to land use change, management, and climate change. [ABSTRACT FROM AUTHOR]

Strontium isotopes (87Sr/86Sr) are useful to trace processes in the Earth sciences as well as in forensic, archaeological, palaeontological, and ecological sciences. As very few large-scale Sr isoscapes exist in Australia, we have identified an opportunity to determine 87Sr/86Sr ratios on archived fluvial sediment samples from the low-density National Geochemical Survey of Australia. The present study targeted the northern parts of Western Australia, the Northern Territory, and Queensland, north of 21.5 ∘ S. The samples were taken mostly from a depth of ∼60 –80 cm in floodplain deposits at or near the outlet of large catchments (drainage basins). A coarse (<2 mm) grain-size fraction was air-dried, sieved, milled, and digested (hydrofluoric acid + nitric acid followed by aqua regia) to release total Sr. The Sr was then separated by chromatography, and the 87Sr/86Sr ratio was determined by multicollector inductively coupled plasma mass spectrometry. The results demonstrate a wide range of Sr isotopic values (0.7048 to 1.0330) over the survey area, reflecting a large diversity of source rock lithologies, geological processes, and bedrock ages. The spatial distribution of 87Sr/86Sr shows coherent (multi-point anomalies and smooth gradients), large-scale (>100 km) patterns that appear to be broadly consistent with surface geology, regolith/soil type, and/or nearby outcropping bedrock. For instance, the extensive black clay soils of the Barkly Tableland define a >500 km long northwest–southeast-trending unradiogenic anomaly (87Sr/86Sr <0.7182). Where sedimentary carbonate or mafic/ultramafic igneous rocks dominate, low to moderate 87Sr/86Sr values are generally recorded (medians of 0.7387 and 0.7422, respectively). Conversely, In proximity to the outcropping Proterozoic metamorphic basement of the Tennant, McArthur, Murphy, and Mount Isa geological regions, radiogenic 87Sr/86Sr values (>0.7655) are observed. A potential correlation between mineralization and elevated 87Sr/86Sr values in these regions needs to be investigated in greater detail. Our results to date indicate that incorporating soil/regolith Sr isotopes in regional, exploratory geoscience investigations can help identify basement rock types under (shallow) cover, constrain surface processes (e.g. weathering and dispersion), and, potentially, recognize components of mineral systems. Furthermore, the resulting Sr isoscape and future models derived therefrom can also be utilized in forensic, archaeological, palaeontological, and ecological studies that aim to investigate, for example, past and modern animal (including humans) dietary habits and migrations. The new spatial Sr isotope dataset for the northern Australia region is publicly available (de Caritat et al., 2022a; 10.26186/147473). [ABSTRACT FROM AUTHOR]

Streamflow forecasts have the potential to improve water resource decision-making, but their economic value has not been widely evaluated, since current forecast value methods have critical limitations. The ubiquitous measure for forecast value, the relative economic value (REV) metric, is limited to binary decisions, the cost–loss economic model, and risk-neutral decision-makers (users). Expected utility theory can flexibly model more real-world decisions, but its application in forecasting has been limited and the findings are difficult to compare with those from REV. In this study, a new metric for evaluating forecast value, relative utility value (RUV), is developed using expected utility theory. RUV has the same interpretation as REV, which enables a systematic comparison of results, but RUV is more flexible and better represents real-world decisions because more aspects of the decision context are user-defined. In addition, when specific assumptions are imposed, it is shown that REV and RUV are equivalent, hence REV can be considered a special case of the more general RUV. The key differences and similarities between REV and RUV are highlighted, with a set of experiments performed to explore the sensitivity of RUV to different decision contexts, such as different decision types (binary, multi-categorical, and continuous-flow decisions), various levels of user risk aversion, and varying the relative expense of mitigation. These experiments use an illustrative case study of probabilistic subseasonal streamflow forecasts (with lead times up to 30 d) in a catchment in the southern Murray–Darling Basin of Australia. The key outcomes of the experiments are (i) choice of decision type has an impact on forecast value, hence it is critically important to match the decision type with the real-world decision; (ii) forecasts are typically more valuable for risk averse users, but the impact varies depending on the decision context; and (iii) risk aversion impact is mediated by how large the potential damages are for a given decision. All outcomes were found to critically depend on the relative expense of mitigation (i.e. the cost of action to mitigate damages relative to the magnitude of damages). In particular, for users with relatively high expense of mitigation, using an unrealistic binary decision to approximate a multi-categorical or continuous-flow decision gives a misleading measure of forecast value for forecasts longer than 1 week lead time. These findings highlight the importance of the flexibility of RUV, which enable evaluation of forecast value to be tailored to specific decisions/users and hence better capture real-world decision-making. RUV complements forecast verification and enables assessment of forecast systems through the lens of user impact. [ABSTRACT FROM AUTHOR]

Persistent surface water pools along non-perennial rivers represent an important water resource for plants, animals, and humans. While ecological studies of these features are not uncommon, these are rarely accompanied by a rigorous examination of the hydrological and hydrogeological characteristics that create or support persistent river pools. Here we present an overarching framework for understanding the hydrology of persistent pools. Perched surface water, alluvial water throughflow, and groundwater discharge are the key hydraulic mechanisms that control the persistence of pools along river channels. Groundwater discharge can be further categorized into that controlled by a geological contact or barrier and discharge controlled by topography. Emphasis is put on clearly defining throughflow of alluvial water and the different drivers of groundwater discharge. The suite of regional-scale and pool-scale diagnostic tools available for elucidating these hydraulic mechanisms are summarized and critiqued. Water fluxes to pools supported by throughflow alluvial and groundwater discharge can vary spatially and temporally, and quantitatively resolving pool water balance components is commonly non-trivial. This framework allows for the evaluation of the susceptibility of persistent pools along river channels to changes in climate or groundwater withdrawals. Finally, we demonstrate the application of this framework using a suite of the available tools to conduct a regional and pool-scale assessment of the hydrology of persistent river pools in the Hamersley Basin of north-western Australia. [ABSTRACT FROM AUTHOR]

Twenty years of daily MODIS-Aqua ocean color observations (2002–2022) are used to identify periodic variability of near-surface chlorophyll (Chl a) in the Indonesian seas. The frequency spectrum of Chl a is dominated by the mean and low-frequency monsoonal variability; however, a prominent peak around the fortnightly tidal period, MS f , is present. Harmonic analysis is used to quantify and map the fortnightly Chl a signal, which is discovered to be significant along the continental shelves of NW Australia and at several sites associated with narrow passages between the Lesser Sunda Islands, within the Sulu Archipelago, and at a few other sites in the Philippines Archipelago. Fortnightly variability at the shallow coastal sites is attributed to the spring–neap cycle of barotropic ocean currents, while we hypothesize that the variability in deeper water near the island passages is due to the modulation of vertical nutrient fluxes by baroclinic tidal mixing. The results document the significance of tidal mixing and highlight the heterogeneous character of biophysical processes within the Indonesian seas. [ABSTRACT FROM AUTHOR]

The bushfires that occurred in Australia in late 2019 and early 2020 were unprecedented in terms of their scale, intensity, and impacts. Using nitrogen dioxide (NO2) and carbon monoxide (CO) data measured by the Tropospheric Monitoring Instrument (TROPOMI), together with fire counts and fire radiative power (FRP) from MODIS, we analyzed the temporal and spatial variation of NO2 and CO column densities over three selected areas covering savanna and temperate forest vegetation. The ΔNO2/ΔCO emission ratio and emission factor were also estimated. The ΔNO2/ΔCO emission ratio was found to be 1.57 ± 1.71 for temperate forest fire and ranged from 2.0 ± 2.36 to 2.6 ± 1.92 for savanna fire. For savanna and temperate forest fires, satellite-derived NOx emission factors were found to be 1.48 and 2.39 gkg-1 , respectively, whereas the CO emission factors are 107.39 and 126.32 gkg-1 , respectively. This study demonstrates that the large-scale emission ratio from the TROPOMI satellite for different biomass burnings can help identify the relative contribution of smoldering and flaming activities in a large region and their impacts on the regional atmospheric composition and air quality. This method can be applied to study the emissions from other large fires, or even the burning of fossil fuel in megacities, and their impact on air quality. [ABSTRACT FROM AUTHOR]

The Hydrologic Reference Stations is a network of 467 high-quality streamflow gauging stations across Australia that is developed and maintained by the Bureau of Meteorology as part of an ongoing responsibility under the Water Act 2007. The main objectives of the service are to observe and detect climate-driven changes in observed streamflow and to provide a quality-controlled dataset for research. We investigate trends and step changes in streamflow across Australia in data from all 467 streamflow gauging stations. Data from 30 to 69 years in duration ending in February 2019 were examined. We analysed data in terms of water-year totals and for the four seasons. The commencement of the water year varies across the country – mainly from February–March in the south to September–October in the north. We summarized our findings for each of the 12 drainage divisions defined by Australian Hydrological Geospatial Fabric (Geofabric) and for continental Australia as a whole. We used statistical tests to detect and analyse linear and step changes in seasonal and annual streamflow. Monotonic trends were detected using modified Mann–Kendall (MK) tests, including a variance correction approach (MK3), a block bootstrap approach (MK3bs) and a long-term persistence approach (MK4). A nonparametric Pettitt test was used for step-change detection and identification. The regional significance of these changes at the drainage division scale was analysed and synthesized using a Walker test. The Murray–Darling Basin, home to Australia's largest river system, showed statistically significant decreasing trends for the region with respect to the annual total and all four seasons. Drainage divisions in New South Wales, Victoria and Tasmania showed significant annual and seasonal decreasing trends. Similar results were found in south-western Western Australia, South Australia and north-eastern Queensland. There was no significant spatial pattern observed in central nor mid-west Western Australia, with one possible explanation for this being the sparse density of streamflow stations and/or the length of the datasets available. Only the Tanami–Timor Sea Coast drainage division in northern Australia showed increasing trends and step changes in annual and seasonal streamflow that were regionally significant. Most of the step changes occurred during 1970–1999. In the south-eastern part of Australia, the majority of the step changes occurred in the 1990s, before the onset of the "Millennium Drought". Long-term monotonic trends in observed streamflow and its regional significance are consistent with observed changes in climate experienced across Australia. The findings of this study will assist water managers with long-term infrastructure planning and management of water resources under climate variability and change across Australia. [ABSTRACT FROM AUTHOR]

Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship. But whether this change can occur in catchments that have also experienced vegetation change and whether it invalidates the most widely used methods for estimating impacts of vegetation change – i.e., the paired-catchment method (PCM), the time–trend method (TTM), and the sensitivity-based method (SBM) – on runoff is still unknown and rarely discussed. Estimated inconsistent afforestation impacts were 32.8 %, 93.5 %, and 76.1 % of total runoff changes in the Red Hill paired experimental catchments in Australia during the period of 1990–2015 by the PCM, TTM, and SBM, respectively. In addition to afforestation, the Red Hill paired experimental catchments have experienced a 10-year drought (2000–2009) and have been demonstrated to lead to non-stationary rainfall–runoff relationships of paired catchments. Estimated impacts of vegetation change by the PCM (32.8 %) is still reliable and is not invalided by multiyear drought-induced non-stationarity, because the PCM can eliminate all impacts by different factors on paired catchments (multiyear drought and climate variability), except the purposed treatment (afforestation). For the TTM and SBM, traditional application did not further differentiate different drivers of non-stationary rainfall–runoff relationship (i.e., multiyear drought and vegetation change), which led to significant overestimation of afforestation effects. A new framework was further proposed to separate the effects of three factors on runoff changes, including vegetation change, climate variability, and hydroclimatic non-stationarity (i.e., multiyear drought). Based on the new framework, impacts of multiyear drought and climate variability on runoff of the control catchment (Kileys Run) were 87.2 % and 12.8 %, respectively. Impacts of afforestation, multiyear drought, and climate variability on runoff of the treated catchment (Red Hill) were 32.8 %, 54.7 %, and 23.9 %, respectively. Impacts of afforestation on runoff were 38.8 % by the TTM and 21.4 % by the SBM, agreeing well with that by the PCM (32.8 %). This study not only demonstrated that multiyear drought can induce non-stationary rainfall–runoff relationship using field observations, but also proposed a new framework to better separate the impact of vegetation change on runoff under climate-induced non-stationary condition. More importantly, it is shown that non-stationarity induced by multiyear drought does not invalidate the PCM, and PCM is still the most reliable method even though the control catchment experienced climate-induced shift in the rainfall–runoff relationship. [ABSTRACT FROM AUTHOR]

Studies on the hydrological response to continuous extreme and asymptotic climate change can improve our ability to cope with intensified water-related problems. Most of the literature focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change. First, the time-varying parameter is derived to reflect the ACWSC periodic and abrupt variations in both drought and non-drought periods. Second, the change points and varying patterns of the ACWSC are analyzed based on the Bayesian change point analysis with multiple evaluation criteria. Finally, various catchment properties and climate characteristics are used to explore the possible relationship between these variables and the temporal variation characteristics of the ACWSC. The catchments that suffered from a prolonged meteorological drought in southeast Australia were selected as the case study. Results indicate that: (1) the increase in amplitude change in the ACWSC is observed in 83/92 catchments during the prolonged drought period, and significant shifts in the mean value of the ACWSC are detected in 77/92 catchments; (2) the average response time of the ACWSC for all 92 catchments with significant changes is 641.3 d; (3) the values of the ACWSC changed significantly in the catchments with small areas, low elevations, small slope ranges, large forest coverage, and high soil water-holding capacities. This study could enhance our understanding of the variations in catchment property under climate change. [ABSTRACT FROM AUTHOR]

Reliable streamflow forecasts with associated uncertainty estimates are essential to manage and make better use of Australia's scarce surface water resources. Here we present the development of an operational 7 d ensemble streamflow forecasting service for Australia to meet the growing needs of users, primarily water and river managers, for probabilistic forecasts to support their decision making. We test the modelling methodology for 100 catchments to learn the characteristics of different rainfall forecasts from Numerical Weather Prediction (NWP) models, the effect of statistical processing on streamflow forecasts, the optimal ensemble size, and parameters of a bootstrapping technique for calculating forecast skill. A conceptual rainfall–runoff model, GR4H (hourly), and lag and route channel routing model that are in-built in the Short-term Water Information Forecasting Tools (SWIFT) hydrologic modelling package are used to simulate streamflow from input rainfall and potential evaporation. The statistical catchment hydrologic pre-processor (CHyPP) is used for calibrating rainfall forecasts, and the error reduction and representation in stages (ERRIS) model is used to reduce hydrological errors and quantify hydrological uncertainty. Calibrating raw forecast rainfall with CHyPP is an efficient method to significantly reduce bias and improve reliability for up to 7 lead days. We demonstrate that ERRIS significantly improves forecast skill up to 7 lead days. Forecast skills are highest in temperate perennially flowing rivers, while it is lowest in intermittently flowing rivers. A sensitivity analysis for optimising the number of streamflow ensemble members for the operational service shows that more than 200 members are needed to represent the forecast uncertainty. We show that the bootstrapping block size is sensitive to the forecast skill calculation. A bootstrapping block size of 1 month is recommended to capture maximum possible uncertainty. We present benchmark criteria for accepting forecast locations for the public service. Based on the criteria, 209 forecast locations out of a possible 283 are selected in different hydro-climatic regions across Australia for the public service. The service, which has been operational since 2019, provides daily updates of graphical and tabular products of ensemble streamflow forecasts along with performance information, for up to 7 lead days. [ABSTRACT FROM AUTHOR]

Determining the mean transit times (MTTs) and water sources in catchments at different flow conditions helps better understand river functioning, and manage river health and water resources. Despite being common in a range of environments, the MTTs and water sources in intermittent streams are much less well understood compared to perennial streams. Major ion geochemistry, stable isotopes, 14 C, and 3 H were used in this study to identify water sources and MTTs of the periodically intermittent upper Wimmera River from southeast Australia at different flow conditions, including zero-flow periods. The disconnected pool waters during the zero-flow period in the summer months of 2019 had 3 H activities of 0.64 to 3.29 TU. These and the variations in total dissolved solids and stable isotopes imply that these pools contained a mixture of older groundwater and younger stream water impacted by evaporation. 3 H activities during the high-flow period in July 2019 were 1.85 to 3.00 TU, yielding MTTs of up to 17 years. The 3 H activities at moderate and low-flow conditions in September and November 2019 ranged from 2.26 to 2.88 TU, implying MTTs of 1.6 to 7.8 years. Regional groundwater near the Wimmera River had 3 H activities of < 0.02 to 0.45 TU and 14 C activities of 57 to 103 pMC, and was not recharged by the river at high flows. The Wimmera River and other intermittent streams in southeast Australia are sustained by younger catchment waters from relatively small near-river stores than comparable perennial streams, which have older deeper regional groundwater inputs. This results in these intermittent streams being more susceptible to short-term changes in climate and necessitates the protection of near-river corridors to maintain the health of the riverine systems. [ABSTRACT FROM AUTHOR]

While the calibration-free complementary relationship (CR) has performed excellently in predicting terrestrial evapotranspiration (ET a) , how to determine the Priestley–Taylor coefficient (αe) is a remaining question. In this work, we evaluated this highly utilizable method, which only requires atmospheric data, with in situ flux observations and basin-scale water-balance estimates (ET wb) in Australia, proposing how to constrain it with a traditional Budyko equation for ungauged locations. We found that the CR method with a constant αe transferred from fractional wet areas performed poorly in reproducing the mean annual ET wb in unregulated river basins, and it underperformed advanced physical, machine-learning, and land surface models in closing grid-scale water balance. This problem was remedied by linking the CR method with a traditional Budyko equation that allowed for an upscaling of the optimal αe from gauged basins to ungauged locations. The combined CR–Budyko framework enabled us to reflect climate conditions in αe , leading to more plausible ET a estimates in ungauged areas. The spatially varying αe conditioned by local climates enabled the CR method to outperform the three ET a models in reproducing the grid-scale ET wb across the Australian continent. We argued here that the polynomial CR with a constant αe could result in biased ET a , and it can be constrained by a traditional Budyko equation for improvement. [ABSTRACT FROM AUTHOR]

High-resolution palaeoclimate proxies are fundamental to our understanding of the diverse climatic history of the Australian mainland, particularly given the deficiency in instrumental datasets spanning more than a century. Annually resolved, tree-ring-based proxies play a unique role in addressing limitations in our knowledge of interannual to multi-decadal temperature and hydroclimatic variability prior to the instrumental period. Here we present cross-dated ring-width (RW) and minimum blue-intensity (BI) chronologies spanning 70 years (1929–1998) for Podocarpus lawrencei Hook.f., the Australian mainland's only alpine conifer, based on nine full-disc cross-sections from Mount Loch in the Victorian Alps. Correlations with climate variables from observation stations and gridded data across the 1929–1998 period reveal a significant positive relationship between RW and mean monthly maximum temperatures in winter throughout central Victoria (r=0.62 , p<0.001) and a significant negative correlation to winter precipitation (r=-0.51 , p<0.001). We also found significant negative correlations between RW and monthly snow depth at Spencer Creek in New South Wales (r=-0.60 , p<0.001). Of the assessed BI parameters, delta blue intensity (Δ BI; the difference between early- and late-wood BI) displayed the greatest sensitivity to climate, with robust spatial correlations with mean October to December maximum and minimum monthly temperatures (r=-0.43 , p<0.001 ; r=-0.51 , p<0.001) and July precipitation (r=0.44 , p<0.001), across large areas of northern Victoria. These promising findings highlight the utility of this species for future work. With the very limited availability of suitable long-lived and cross-datable species on the Australian mainland, these results have significant implications for advancing high-resolution palaeoclimate science in southeastern Australia and for improving our understanding of past climate in the region. [ABSTRACT FROM AUTHOR]