Extreme weather events (EWEs) are increasing in both intensity and frequency globally. For long-lived, slow-reproducing marine predators, repeated or sequential EWE-driven breeding failures can have population-level consequences. We quantified effects of EWEs on reproductive output and identified temporal windows of vulnerability during breeding in three sentinel species across 14 colonies with varying population trajectories in Tasmania, Australia. Using long-term breeding datasets and daily weather records, we found that Australian fur seals ( Arctocephalus pusillus doriferus ), short-tailed shearwaters ( Ardenna tenuirostris ), and shy albatross ( Thalassarche cauta ) exhibited species- and colony-specific vulnerabilities. Storm surges reduced pup production in a low-lying fur seal colony, extreme rainfall lowered shearwater breeding success, and albatross productivity declined with exposure to extreme heat, rainfall, and wave events. These results highlight the importance of identifying critical extreme weather thresholds and periods of vulnerability to inform ecological forecasting. Proactive, climate-informed management strategies tailored to specific colonies are needed to enhance the resilience of vulnerable populations under accelerating climate change.

The nadir and off-nadir ocean wind and wave products of the Surface Waves Investigation and Monitoring (SWIM) instrument onboard the China France Oceanography Satellite (CFOSAT) are validated against multiple wave buoy datasets. These include a moored buoy in the Southern Ocean, the Northern Hemisphere focused wave buoys of the National Data Buoy Centre (NDBC), and a globally distributed Sofar drifting spotter buoy archive. SWIM nadir comparisons of significant wave height and wind speed data against NDBC buoy measurements showed that SWIM can capture these parameters with high accuracy and temporal stability. The off-nadir comparisons of SWIM bulk statistics of significant wave height and peak wave direction indicate high correlation and low errors against all buoy datasets. The performance of wave period (both mean and peak) is relatively poorer and varies by buoy dataset considered, with best results obtained against the Sofar archive. The accuracy of SWIM mean wave period against all buoy datasets is significantly improved by using a recently published neural networks-based inversion approach. Finally, quantitative evaluation of SWIM omni-directional spectra indicated an overall best performance for SWIM 10° beam product amongst the four SWIM products and against all exploited wave buoy datasets. This calibration and validation work is comprehensive and valuable because it describes the performance of CFOSAT wind/wave products in global oceanic conditions and against both moored and drifting wave buoy networks, with satellite-buoy collocations varying from 1605 to 7233 respectively for nadir wave and wind comparisons and over 3000 for off-nadir comparisons across all platforms. It is the intention that this work will enable the uptake of SWIM data with better-informed quantification of errors and accuracies.

Changes in wave climate can impact coastal zones by altering the sediment supplied to coastal compartments via longshore sediment transport (LST). Estimating these changes is challenging, and biases and uncertainty in wave climate projections contribute to uncertainty in LST and morphological change projections. This paper compares wave climate, LST projections, and morphological changes derived from two iterations of the Coupled Model Intercomparison Project (CMIP), and the implications of applying wave climate bias correction in these projections for the late 21st century under high emission scenarios. LST and morphological changes were simulated in a process-based model calibrated with data from a sand bypassing system. Bias correction improved representation of wave climate, including extremes, and reduced variance between climate models. Although bias correction did not change projected mean LST, it reduced the spread of model ensembles by 20% and 10% for CMIP5 and CMIP6, respectively. Both CMIP5 and CMIP6 suggest a future reduction of LST in the study area. However, CMIP6-derived projections show: (a) 50% less variance in wave forcing; (b) greater consistency between ensemble members; and (c) double the reduction in LST. This reduction is attributed to changes in the frequency, intensity and direction of modal and extreme waves. Morphological changes suggest steepening of the beach profiles in line with the historical record. This contribution highlights the value of a bias-corrected model ensemble and improvements in CMIP iterations in providing coherent projections of future wave climate change and its impacts on regional coastal processes.

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.

Terrestrially breeding marine predators have experienced shifts in species distribution, prey availability, breeding phenology, and population dynamics due to climate change worldwide. These central-place foragers are restricted within proximity of their breeding colonies during the breeding season, making them highly susceptible to any changes in both marine and terrestrial environments. While ecologists have developed risk assessments to evaluate climate risk in various contexts, these often overlook critical breeding biology data. To address this knowledge gap, we developed a trait-based risk assessment framework, focusing on the breeding season and applying it to marine predators breeding in parts of Australian territory and Antarctica. Our objectives were to quantify climate change risk, identify specific threats, and establish an adaptable assessment framework. The assessment considered 25 criteria related to three risk components: vulnerability, exposure, and hazard, while accounting for uncertainty. We employed a scoring system that integrated a systematic literature review and expert elicitation for the hazard criteria. Monte Carlo sensitivity analysis was conducted to identify key factors contributing to overall risk. We identified shy albatross ( Thalassarche cauta ), southern rockhopper penguins ( Eudyptes chrysocome ), Australian fur seals ( Arctocephalus pusillus doriferus ), and Australian sea lions ( Neophoca cinerea ) with high climate urgency. Species breeding in lower latitudes, as well as certain eared seal, albatross, and penguin species, were particularly at risk. Hazard and exposure explained the most variation in relative risk, outweighing vulnerability. Key climate hazards affecting most species include extreme weather events, changes in habitat suitability, and prey availability. We emphasise the need for further research, focusing on at-risk species, and filling knowledge gaps (less-studied hazards, and/or species) to provide a more accurate and robust climate change risk assessment. Our findings offer valuable insights for conservation efforts, given that monitoring and implementing climate adaptation strategies for land-dependent marine predators is more feasible during their breeding season.

AbstractThe ocean is a dominant feature of our planet, covering 70% of its surface and driving its climate and biosphere. The ocean sustains life on earth and yet is in peril from climate change.

In this article, a regional ocean surface waves dataset from Sentinel-1 A and B Synthetic Aperture Radar (SAR) satellites has been described. The ocean wave data have been extracted from the Sentinel-1 level-2 OCN (ocean) product as provided by the European Space Agency and downloadable for this region from the Copernicus Australasia regional data hub. The source OCN data have been produced by evolving versions of Sentinel-1 Instrument Processing Facility (IPF). The structure of the source OCN NetCDF files changes over time and presents a challenge in performing long duration, time series analyses, including the examination of potential inconsistencies in OCN wave data, due to employment of different IPF versions over the duration of the satellite missions. Here, the input OCN wave data have been homogenized to a single, easily usable standard format after applying a quality assurance and control procedure that removes various inconsistencies in variables, coordinates, dimensions and land flag, and through the addition of new auxiliary variables. The new format has the desirable properties of being compact in size, consistent in structure, and scalable in temporal and spatial coverage. It is also convenient to use and offers opportunities to perform fast, multi-year regional processing and analysis for calibration and validation studies and scientific applications. No re-processing of Sentinel-1 level-1 data has been carried out in this work.

Coastal flood damage is primarily the result of extreme sea levels. Climate change is expected to drive an increase in these extremes. While proper estimation of changes in storm surges is essential to estimate changes in extreme sea levels, there remains low confidence in future trends of surge contribution to extreme sea levels. Alerting local populations of imminent extreme sea levels is also critical to protecting coastal populations. Both predicting and projecting extreme sea levels require reliable numerical prediction systems. The SurgeMIP (surge model intercomparison) community has been established to tackle such challenges. Efforts to intercompare storm surge prediction systems and coordinate the community 's prediction and projection efforts are introduced. An overview of past and recent advances in storm surge science such as physical processes to consider and the recent development of global forecasting systems are briefly introduced. Selected historical events and drivers behind fast increasing service and knowledge requirements for emergency response to adaptation considerations are also discussed. The community 's initial plans and recent progress are introduced. These include the establishment of an intercomparison project, the identification of research and development gaps, and the introduction of efforts to coordinate projections that span multiple climate scenarios.

We present a global wind wave climate model ensemble composed of eight spectral wave model simulations forced by 3-hourly surface wind speed and daily sea ice concentration from eight different CMIP6 GCMs. The spectral wave model uses ST6 physics parametrizations and a global three-grid structure for efficient Arctic and Antarctic wave modeling. The ensemble performance is evaluated against a reference global multi-mission satellite altimeter database and the recent ECMWF IFS Cy46r1 ERA5 wave hindcast, ERA5H. For each ensemble member three 30-year slices, one historical, and two future emission scenarios (SSP1-2.6 and SSP5-8.5) are available, and cover two distinct periods: 1985–2014 and 2071–2100. Two models extend to 140 years (1961–2100) of continuous wind wave climate simulations. The present ensemble outperforms a previous CMIP5-forced wind wave climate ensemble, showing improved performance across all ocean regions. This dataset is a valuable resource for future wind wave climate research and can find practical applications in offshore and coastal engineering projects, providing crucial insights into the uncertainties connected to wind wave climate future projections.

HEMER, M.A.; CHURCH, J.A. and HUNTER, J.R., 2007. Waves and climate change on the Australian coast, SI 50 (Proceedings of the 9th International Coastal Symposium), 432 - 437. Gold Coast, Australia, ISSN 0749.0208.There is a need to plan for the impacts of coastal erosion in response to climate change Australia-wide. A deep-water wave climatology of the Australian region is determined, which is required as boundary conditions for coastal wave models. Available wave data for the Australian region has been analysed to determine the mean climatology and interannual variability of mean significant wave height. Available data includes global wave model output from the ECMWF 45-yr re-analysis, ERA-40; corrected ERA-40 wave heights and the NOAA WaveWatch III operational wave model; satellite altimetry measurements; and data from a network of 30 wave-rider buoys surrounding the Australian coast located on the inner-mid continental shelf and some short-term deep-water wave-rider buoy deployments. These data have been analysed to determine the long-term mean, annual cycle and interannual variability of the mean Australian wave climate. Correlation with a number of climate indices in the Australian region indicate that southern ocean wind anomalies are a dominant mechanism responsible for variability of wave climate in the region. Correlation between monthly mean significant wave heights and the Southern Oscillation Index is significant along Australia's eastern margin.

This work revisits and extends an analysis of the Australian wave observing network. The method is based on calculating correlations between modelled wave variables at observation sites and the Australian coastal domain and identifying areas of low correlation. This gives an indication of the areas where variability of the wave fields is poorly captured by existing observation locations, i.e. the network gaps. It is found that the gaps in the network that had been identified in previous work are to a large part reduced by the recent deployment of new infrastructure, but not eliminated. It is also found that the network does less well at observing the synoptic scale wave field than it does at observing the monthly wave climate. Lagged correlations are also considered but found to have only a modest impact on the ability of the network to observe the wave field variability.

Over the last two decades, a large body of academic scholarship has been generated on wave and tidal energy related topics. It is therefore important to assess and analyse the research direction and development through horizon scanning processes. To synthesise such large-scale literature, this review adopts a bibliometric method and scrutinises over 8000 wave/tidal energy related documents published during 2003–2021. Overall, 98 countries contributed to the literature, with the top ten mainly developed countries plus China produced nearly two-thirds of the research. A thorough analysis on documents marked the emergence of four broad research themes (dominated by wave energy subjects): (A) resource assessment, site selection, and environmental impacts/benefits; (B) wave energy converters, hybrid systems, and hydrodynamic performance; (C) vibration energy harvesting and piezoelectric nanogenerators; and (D) flow dynamics, tidal turbines, and turbine design. Further, nineteen research sub-clusters, corresponding to broader themes, were identified, highlighting the trending research topics. An interesting observation was a recent shift in research focus from solely evaluating energy resources and ideal sites to integrating wave/tidal energy schemes into wider coastal/estuarine management plans by developing multicriteria decision-making frameworks and promoting novel designs and cost-sharing practices. The method and results presented may provide insights into the evolution of wave/tidal energy science and its multiple research topics, thus helping to inform future management decisions.

The amount of wave and tidal energy entering an estuary from the ocean is highly influenced by the entrance morphology, therefore, the ability to accurately detect and measure bathymetric changes in morphology is highly desirable for coastal managers.As in-situ bathymetric data collection is often costly and/or logistically challenging, bathymetry derived from multispectral and hyperspectral imagery has become widely used.This paper details an ongoing investigation into the suitability of using UAV captured multispectral imagery to develop a repeatable methodology to detect and measure inlet morphological variability.Specifically, this study utilises multispectral imagery to derive bathymetric models using the empirical algorithm first proposed by Stumpf et al (2003) to determine inlet variability through time.This paper and presentation documents an ongoing field campaign of UAV multispectral imagery capture, the development of bathymetric models from this imagery and the validation of these bathymetric models using contemporaneous single beam sonar surveys.The study inlet, Moonee Creek, is on the south-east Australian coast and is a small, microtidal, wave dominated inlet.

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.

We present four 140-yr wind-wave climate simulations (1961-2100) forced with surface wind speed and sea ice concentration from two CMIP6 GCMs under two different climate scenarios: SSP1-2.6 and SSP5-8.5. A global three -grid system is implemented in WAVEWATCH III to simulate the wave-ice interactions in the Arctic and Antarctic regions. The models perform well in comparison with global satellite altimeter and in situ buoys climatology. The compari-son with traditional trend analyses demonstrates the present GCM-forced wave models' ability to reproduce the main his-torical climate signals. The long-term datasets allow a comprehensive description of the twentieth-and twenty -first-century wave climate and yield statistically robust trends. Analysis of the latest IPCC ocean climatic regions highlights four regions where changes in wave climate are projected to be most significant: the Arctic, the North Pacific, the North Atlantic, and the Southern Ocean. The main driver of offshore wave climate change is the wind, except for the Arctic where the signifi-cant sea ice retreat causes a sharp increase in the projected wave heights. Distinct changes in the wave period and the wave direction are found in the Southern Hemisphere, where the poleward shift of the Southern Ocean westerlies causes an in-crease in the wave period of up to 5% and a counterclockwise change in wave direction of up to 58. The new CMIP6 forced wave models improve in performance compared to previous CMIP5 forced wave models, and will ultimately contribute to a new CMIP6 wind-wave climate model ensemble, crucial for coastal adaptation strategies and the design of future marine offshore structures and operations.

There are numerous global ocean wave reanalysis and hindcast products currently being distributed and used across different scientific fields. However, there is not a consistent dataset that can sample across all existing products based on a standardized framework. Here, we present and describe the first coordinated multi-product ensemble of present-day global wave fields available to date. This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, includes general and extreme statistics of significant wave height (Hs), mean wave period (Tm) and mean wave direction (θm) computed across 1980–2014, at different frequency resolutions (monthly, seasonally, and annually). This coordinated global ensemble has been derived from fourteen state-of-the-science global wave products obtained from different atmospheric reanalysis forcing and downscaling methods. This data set has been processed, under a specific framework for consistency and quality, following standard Data Reference Syntax, Directory Structures and Metadata specifications. This new comprehensive dataset provides support to future broad-scale analysis of historical wave climatology and variability as well as coastal risk and vulnerability assessments across offshore and coastal engineering applications.