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The dataset consists of ocean surface wind speed and direction at 10 m height and 1 km spatial resolution around the wider Australian coastal areas, spanning 4 years (2017 to 2021) of measurements from Sentinel-1 A and B imaging Synthetic Aperture Radar (SAR) platforms. The winds have been derived using a consistent SAR wind retrieval algorithm, processing the full Sentinel-1 archive in this region. The data are appropriately quality controlled, flagged, and archived as NetCDF files representing SAR wind field maps aligned with satellite along-track direction. The data have been calibrated against Metop-A/B Scatterometer buoy-calibrated, wind measurements and examined for potential changes in calibration over the duration of the data. The calibrated data are further validated by comparisons against independent Altimeter (Cryosat-2, Jason-2, Jason-3, and SARAL) wind speeds. Several methods for data access are also listed. The database is potentially useful for offshore industries (oil and gas, fisheries, shipping, offshore wind energy), public recreational activities (fishing, sailing, surfing), and protection and management of coasts and natural habitats. [ABSTRACT FROM AUTHOR]

While the variations of tidal range are large and fairly well known across Australia (less than 1 m near Perth but more than 14 m in King Sound), the properties of the tidal currents are not. We describe a new regional model of Australian tides and assess it against a validation dataset comprising tidal height and velocity constituents at 615 tide gauge sites and 95 current meter sites. The model is a barotropic implementation of COMPAS, an unstructured-grid primitive-equation model that is forced at the open boundaries by TPXO9v1. The mean absolute error (MAE) of the modelled M2 height amplitude is 8.8 cm , or 12 % of the 73 cm mean observed amplitude. The MAE of phase (10 ∘), however, is significant, so the M2 mean magnitude of vector error (MMVE, 18.2 cm) is significantly greater. The root sum square over the eight major constituents is 26 % of the observed amplitude. We conclude that while the model has skill at height in all regions, there is definitely room for improvement (especially at some specific locations). For the M2 major axis velocity amplitude, the MAE across the 95 current meter sites, where the observed amplitude ranges from 0.1 to 156 cms-1 , is 6.9 cms-1 , or 22 % of the 31.7 cms-1 observed mean. This nationwide average result is encouraging, but it conceals a very large regional variation. Relative errors of the tidal current amplitudes on the narrow shelves of New South Wales (NSW) and Western Australia exceed 100 %, but tidal currents are weak and negligible there compared to non-tidal currents, so the tidal errors are of little practical significance. Looking nationwide, we show that the model has predictive value for much of the 79 % of Australia's shelf seas where tides are a major component of the total velocity variability. In descending order this includes the Bass Strait, the Kimberley to Arnhem Land, and southern Great Barrier Reef regions. There is limited observational evidence to confirm that the model is also valuable for currents in other regions across northern Australia. We plan to commence publishing "unofficial" tidal current predictions for chosen regions in the near future based on both our COMPAS model and the validation dataset we have assembled. [ABSTRACT FROM AUTHOR]

In some shelf sea regions of the world, the tidal range is sufficient to convert the potential energy of the tides into electricity via tidal range power plants. As an island continent, Australia is one such region – a previous study estimated that Australia hosts up to 30% of the world's resource. Here, we make use of a gridded tidal dataset (TPXO9) to characterize the tidal range resource of Australia. We examine the theoretical resource, and we also investigate the technical resource through 0D modelling with tidal range power plant operation. We find that the tidal range resource of Australia is 2004 TWh/yr, or about 22% of the global resource. This exceeds Australia's total energy consumption for 2018/2019 (1721 TWh/yr), suggesting tidal range energy has the potential to make a substantial contribution to Australia's electricity generation (265 TWh/yr in 2018/2019). Due to local resonance, the resource is concentrated in the sparsely populated Kimberley region of Western Australia. However, the tidal range resource in this region presents a renewable energy export opportunity, connecting to markets in southeast Asia. Combining the electricity from two complementary sites, with some degree of optimization tidal range schemes in this region can produce electricity for 45% of the year. ● The tidal range resource of Australia is 2004 TWh/yr – around 22% of the global resource. ● The resource is primarily concentrated in the Kimberley region of Western Australia. ● Although this region is remote, it represents an export opportunity to SE Asia. ● We optimize the operation of two complementary sites in this region. ● Variability is reduced at both diurnal and semi-diurnal scales. [ABSTRACT FROM AUTHOR]

Wind‐wave hindcast data have many applications including climatology assessments for renewable energy projects, maritime engineering design, event‐based impact assessments, generating boundary conditions for further downscaling, amongst others. Here, we present a global wave hindcast with nested high‐resolution grids for the Exclusive Economic Zones of Australia and south west Pacific Island Countries, that is extended in time monthly. The model employs strategic methods to incorporate the effects of subgrid sized features such as small islands and islets. Various bulk wave parameters are available hourly from January 1979 to present, along with the full wave spectra at a set of 3,683 predetermined points distributed globally. [ABSTRACT FROM AUTHOR]

While the variations of tidal range are large and fairly well known across Australia (less than 1 m near Perth but more than 14 m in King Sound), the properties of the tidal currents are not. We describe a new regional model of Australian tides and assess it against a validation dataset comprising tidal height and velocity constituents at 615 tide gauge sites and 95 current meter sites. The model is a barotropic implementation of COMPAS, an unstructured-grid primitive-equation model that is forced at the open boundaries by TPXO9v1. The Mean Absolute value of the Error (MAE) of the modelled M2 height amplitude is 9.3 cm, or 13 % of the 73 cm mean observed amplitude. The MAE of phase (11°), however, is significant, so the M2 Mean Magnitude of Vector Error (MMVE, 20 cm) is significantly greater. Results for 5 other major constituents are similar. We conclude that while the model has skill at height in all regions, there is definitely room for improvement (especially at some specific locations) before harmonic predictions based on observations are rendered obsolete. For the M2 major-axis velocity amplitude, the MAE across the 95 current meter sites, where the observed amplitude ranges from 0.1 cm s-1 to 144 cm s-1, is 6.5 cm s-1, or 20 % of the 31.7 cm s-1 observed mean. This nationwide average result is not much greater than the equivalent for height, but it conceals a larger regional variation. Relative errors on the narrow shelves of NSW and Western Australia exceed 100 %, but tidal currents are weak and negligible there compared to non-tidal currents. We show that the model has predictive value for much of the 79 % of Australia's shelf seas where tides are a major component of the total velocity variability. In descending order this includes the Bass Strait, Kimberley to Arnhem Land and Southern Great Barrier Reef regions. There is limited evidence the model is also valuable for currents in other regions across northern Australia. We plan to commence publishing unofficial tidal current predictions for chosen regions in the near future, based on both the limited number of observations, and the COMPAS model. [ABSTRACT FROM AUTHOR]

The Australian coastal zone encompasses tropical, sub- and extra-tropical climates and accommodates about 80 % of Australia's population. Sea level extremes and their physical impacts in the coastal zone arise from a complex set of atmospheric, oceanic and terrestrial processes that interact on a range of spatial and temporal scales and will be modified by a changing climate, including sea level rise. This review details significant progress over recent years in understanding the causes of past and projections of future changes in sea level and coastal extremes, yet a number of research questions, knowledge gaps and challenges remain. These include efforts to improve knowledge on past sea level extremes, integrate a wider range of processes in projections of future changes to sea level extremes, and focus efforts on understanding long-term coastline response from the combination of contributing factors. [ABSTRACT FROM AUTHOR]

Climate models are increasingly being used to force dynamical wind wave models in order to assess the potential climate change-driven variations in wave climate. In this study, an ensemble of wave model simulations have been used to assess the ability of climate model winds to reproduce the present-day (1981-2000) mean wave climate and its seasonal variability for the southeast coast of Australia. Surface wind forcing was obtained from three dynamically downscaled Coupled Model Intercomparison Project (CMIP-3) global climate model (GCM) simulations (CSIRO Mk3.5, GFDLcm2.0 and GFDLcm2.1). The downscaling was performed using CSIRO's cubic conformal atmospheric model (CCAM) over the Australian region at approximately 60-km resolution. The wind climates derived from the CCAM downscaled GCMs were assessed against observations (QuikSCAT and NCEP Re-analysis 2 (NRA-2) reanalyses) over the 1981-2000 period and were found to exhibit both bias in mean wind conditions (climate bias) as well as bias in the variance of wind conditions (variability bias). Comparison of the modelled wave climate with over 20 years of wave data from six wave buoys in the study area indicates that direct forcing of the wave models with uncorrected CCAM winds result in suboptimal wave hindcast. CCAM winds were subsequently adjusted for climate and variability bias using a bivariate quantile adjustment which corrects both directional wind components to align in distribution to the NRA-2 winds. Forcing of the wave models with bias-adjusted winds leads to a significant improvement of the hindcast mean annual wave climate and its seasonal variability. However, bias adjustment of the CCAM winds does not improve the ability of the model to reproduce the storm wave climate. This is likely due to a combination of storm systems tracking too quickly through the wave generation zone and the performance of the NRA-2 winds used as a benchmark in this study. [ABSTRACT FROM AUTHOR]

Abstract: Seabed sediments comprise a full distribution of grain sizes. Previous models describing sediment mobility on the Australian continental shelf have ignored the distribution of grain sizes, presenting results for one size class only — the mean grain size. A simple model is presented which determines the probability of sediment entrainment which accounts for the full grain size distribution. The model is applied to the wave dominated New South Wales (NSW) continental shelf, south-eastern Australia, using observed grain size distribution data. Wave data from the Port Kembla waverider buoy are used to calculate sediment mobility in response to waves via two methods: a simple empirical approach where maximum bed orbital velocity must exceed a critical bottom velocity, and a more theoretically based approach where skin-friction shear stresses must exceed a Shields curve determined threshold for sediment entrainment. Results from the two methods compare to within 10%. The effects of a variable sea are investigated by comparing sediment mobility in response to both significant and maximum waves. Maximum waves are found to mobilise medium-fine sand fraction sediments on the mid shelf, whereas significant waves mobilise medium-fine sand fraction sediments on the inner shelf, and only rarely the mid shelf. Maximum waves are capable of mobilising mud fraction size sediments (if non-cohesive) beyond the shelf break. Combined wave — wind-generated current bed shear stresses were determined, and indicate that waves dominate mobilisation on the inner and mid shelf, but only wind-driven currents are capable of mobilising sediments on the outer shelf during extreme wind events. The distribution of bed shear stresses is consistent with the previously reported observed sediment distribution on the continental shelf. Determination of the sediment mobility of grain size distributions on the continental shelf is limited to available grain size distribution data. Consolidation of existing grain size datasets, and newly collected data, will allow for rapid extension of the method on a large scale. [Copyright &y& Elsevier]

The influence of ocean surface currents on the global wind-wave field is revisited. State-of-the-art numerical spectral wave model simulations with and without surface currents taken from an eddy resolving global ocean reanalysis were compared. As a global average, simulations forced with currents display significantly better agreement with altimeter derived wave heights. The bias and root mean square error in significant wave heights are mostly reduced when including current forcing, especially in the Southern Ocean. An overall improvement in wave periods and wave direction is also seen when comparing model outputs with the Australian and United States buoy network observations. Including surface ocean current forcing in wave simulations reduces the simulated wave heights in most areas of the world, due to a decreased relative wind given by co-flowing winds and currents. Current-induced refraction generates important changes in wave direction in western boundary current and tropical regions. Furthermore, large and broad changes in friction velocity, atmosphere-to-ocean energy flux, whitecap cover and Stokes drift velocities are observed in equatorial regions. Finally, the importance of the wave model resolution for representing wave–current interactions was tested by comparing results from eddy-permitting (lower resolution) and eddy-resolving (higher resolution) configurations. We conclude that the main patterns of current-induced refraction are well represented in both cases, albeit that the higher resolution simulation represents these in a more detailed manner. Finally, the implications that the observed wave–current interactions have on several ocean processes are discussed. • Wave model performance improves significantly by including surface currents forcing. • Equatorial and Western Boundary Current areas show great changes in wave direction. • Wave–current interactions help to better model intense wave events in East Australia. • There are great changes in friction velocity and whitecap cover in Tropical areas. • Eddy-permitting simulations properly depict the current-induced refraction patterns. [ABSTRACT FROM AUTHOR]

As the tidal energy industry looks to expand into commercial-scale array installations, uncertainty in methodology and outcome for environmental impact assessments can encumber tidal energy developments. Incorporating environmental monitoring measures into site characterisation campaigns can provide baseline information about biophysical relationships and help recognise potential impacts to the marine environment early in the development process. Concurrent measurements of fish and tidal currents were taken at a tidal energy candidate site in Australia over ∼ 2.5 months during its tidal resource assessment. Fish aggregation metrics (density, abundance, centre-of-mass (CM), dispersion, %-water column occupied, evenness, and relative aggregation) were investigated for their relation to environmental conditions (current speed, shear, temperature, diel stage, and tidal stage). Diel stage was the most significant indicator for fish density, abundance, and %-water column occupied. Fish density and abundance were elevated during strong currents, with vertical fish distribution (CM and dispersion) also influenced by current speed. Environmental conditions were able to explain up to 25% of variation in fish aggregation metrics using linear models. This study shows that early-stage environmental monitoring can successfully provide baseline information about fish aggregation responses to prevailing environmental conditions, thus reducing uncertainty risks for stakeholders of tidal energy developments. • Environmental impact assessment was coupled with tidal resource characterisation in Australia. • Fish were more abundant, higher in the water column, and more dispersed at peak flows. • Fish were most influenced by diel stage with densities nearly two-times higher at night vs. day. • At high temperatures, fish were more abundant and closer to the bottom. • Environmental conditions explained 25% of variance in fish density using linear models. [ABSTRACT FROM AUTHOR]

Abstract: Wave energy is particularly abundant along the Australian southern coastline. Harvesting wave energy using a converter could provide a sustainable alternative for electricity generation for Australia. In this paper, the performance of three different types of wave energy converter (WEC) has been evaluated spatially for Australian coastal regions using Australian Renewable Energy Atlas wave energy data. It was found one of the WECs operated with a capacity factor greater than 54.3% for a large portion of the Tasmanian western coastline, while being located close to transmission infrastructure. The levelised cost of electricity (LCOE) for the WECs for these regions was in the order of $78/MWh. [Copyright &y& Elsevier]

Offshore wind energy and wave energy are two exploitable sources of renewable energy available in the same marine environment. A co-located energy harvesting system of these two resources has the potential to play a leading role in the recent renewable energy mix mandate. A co-located system of mature offshore wind technology and a nascent wave energy technology can exploit the synergies of the two technologies, including the reduced cost, the easy operation and maintenance, and more importantly the potential of decreased power variability. This paper deals with a multi-site analysis of wind and wave power resources, and the estimation of exploitable energy through different wind turbines and wave energy converters (WECs). Results are presented for NSW Australia, but the devised strategy is generic and can be implemented in any region. Ten WECs, with different operating principles, are used for the estimation of the exploitable wave power, and the best performing converter is considered for the co-located wind-wave farm. A power fluctuation factor is introduced to quantify the reduction in power variability of the co-located wind-wave farm. Different percentage mixes of wind and wave energy are evaluated for the co-located wind-wave farm in the multi-site analysis. •A multi-site analysis of wind and wave for estimation of exploitable energy. •Performance evaluation of wind and wave energy conversion technologies. •Power variability representation with power fluctuation factor for a co-located farm. •Characterization of percentage share of wind and wave in a co-located farm. [ABSTRACT FROM AUTHOR]

Australia has significant offshore wind resources that can support ever-increasing power demand and hence provide a long-term contribution to the net-zero target by 2050. Although some offshore wind farm projects are proposed in Australia, the industry is not mature enough to justify the benefits and display economic opportunities. More specifically, the techno-economic analysis of offshore wind energy has not been systematically mapped in Australia. Therefore, the investigation of the spatial variation of technical feasibility and economic potential of offshore wind is vital to identify the potential regions and to develop strategies for future offshore wind farm developments in Australia. This paper presents detailed mappings of the techno-economic potential of offshore wind energy in Victoria-Tasmania's exclusive economic zone. Offshore wind energy resources are assessed in the paper in terms of energy availability and variability and the feasibility of various offshore wind technologies is investigated, including turbines, foundation types and transmission topologies. In addition, the high-fidelity life-cycle cost models and two innovative evaluation matrices are developed to assess the economic potential of offshore energy farms in South-eastern Australia. The impact of local power system regulation costs and future carbon prices on the viability of offshore wind is also investigated in this paper. It is concluded that the detailed mapping approach and analysis in the paper can provide a systematic tool for industry partners, investors and policymakers at the pre-planning stage of developing offshore renewable energy systems. • The technical feasibility of offshore wind is mapped under various constraints. • The novel LACE and high-fidelity LCC assessment models are developed. • The techno-economic potential is systemically mapped in South-eastern Australia. • The impacts of electricity market regulation and future carbon prices are studied. [ABSTRACT FROM AUTHOR]

In this study, a long-term assessment of the wave energy resource potential for the Australian southeast shelf is performed from deep to shallow water, based on a 31-year wave hindcast. The hindcast, covering the period from 1979 to 2010, has been performed at high spatio-temporal resolution with the wave energy transformation model SWAN using calibrated source-term parameters. The model has been applied with a variable spatial resolution of up to approximately 500 m and at 1 h temporal resolution and driven with high-resolution, non-stationary CFSR wind fields and full 2D spectral boundary conditions from WaveWatch III model. Model validation was conducted against wave measurements from multiple buoy sites covering 10–31 years and showed a relatively high correlation between hindcast and measured significant wave height ( H s ) and mean wave direction ( θ m ). Maps of wave power resource distribution for annual and seasonal mean potential were generated along with the maps of resource reliability and variability. The high resolution allowed us to perform in-depth analysis of wave power characteristics, providing resource knowledge on seasonal and longer-term variability necessary for reliable and optimal design of wave technology. The most promising area for wave power exploitation was found to be the central coast of New South Wales, where various high-energy hotspots were selected for a further analysis. For each of the considered hotspots, the wave power magnitude, variability and consistency were carefully assessed and characterized by means of sea state parameters and mean wave directions. Finally, estimates of electric power outputs from different types of pre-commercial wave energy converter devices were drawn for each hotspot based on the wave data hindcast and discussed. [ABSTRACT FROM AUTHOR]

Offshore wind and wave power are abundant energy sources and could provide long term contributions to our future energy supply. The combined exploration of wind and wave power has been proposed as an effective way to mitigate the non-negligible power intermittency and variability of offshore renewables. However, the assessments of wind and wave resources have been developed separately in Australia, and the potential of diversified wind and wave power has not been studied systematically. This study investigates offshore wind and wave energy sources in multiple locations around the Australian coastline and their potentials for integration in terms of energy availability, power variability, coherence and correlation, and annual and seasonal variability over the last seven years. In addition, wind and wave mixed energy farms are studied using commercial wind turbine models and various wave energy converter prototype models. The energy availability, power smoothing effect, capacity factor and downtime of these mixed energy farms are also discussed. Moreover, this paper proposes an effective matrix for assessing the potential of hybrid energy farms in multiple sites in terms of power availability, power variability and combination performance and the sensitivity of selecting various wave energy converter (WEC) models is also investigated to provide a general guideline for future work. The regional comparative results indicate that the swell wave dominated sites in Western and Southern Australia present merits for combining wind and wave power, while wind–wave dominated regions, such as Eastern Australia, are not preferable for this diversified system. It can be found that power variability and downtime can be significantly reduced for the specific wind–wave capacity mix if a lower correlation or longer lag time exists between the two renewables. The results also illustrate that the combinations with different WEC systems present varying benefits in the different locations in Australia. • Wind and wave energy resources are assessed in Australian region. • A wave identification system is designed for hybrid exploration. • A matrix to assess the potential of combined energy farm is proposed. • Sensitivity of WEC selection to the combined energy farm is investigated. [ABSTRACT FROM AUTHOR]