Abstract
A multi-decadal global wind-wave hindcast dataset—WHACS: the Wave Hindcast for ACS—spanning 1979 to near present was developed to offer insight into historical wave conditions both directly and as boundary forcing to localised simulations. Applications for WHACS include coastal management, climate research, and renewable energy projects, ultimately helping communities and industries make informed decisions to improve safety, efficiency, and resilience regarding wave conditions. This dataset features a near-global spherical multi-cell (SMC) grid that aligns with the Bureau operational wave forecast model and has been calibrated to better represent extreme wave conditions by improving the representation of extreme winds. Spanning from 1979 to near present, WHACS available output consists of multiple hourly bulk and spectral partition wave parameters for the native SMC grid, as well as regular global and regional regridded bulk wave parameters. For the Indo-Pacific, a gridded output of full spectral data is available across exclusive economic zones.
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Data availability
The WHACS dataset is available as bulk wave parameters across the native SMC grid, a global rectilinear grid with 1/8° resolution, a regional Australasian grid with 1/16° resolution, and full spectral data from a discrete set of selected global data points. The complete set of NetCDF data files from January 1979 to present is published by CSIRO and indexed within the Research Data Australia with Digital Object Identifier https://doi.org/10.25919/shdk-7p29:
For direct download from a browser via the Data Access Portal: https://doi.org/10.25919/yp77-v026
Remote access via THREDDS: https://data-cbr.csiro.au/thredds/catalog/catch_all/ACS_WP3_WHACS/ACS_hindcast_DRS/catalog.html
Bulk wave parameters are stored separately in NetCDF monthly files. The NetCDF files are identified by the filename suffix, with a prefix that denotes the month by start and end date stamps, i.e.,
< var > _WHACS_hindcast_WHACS_ERA5_1hr_ < yyyymmddhhmm > - < yyyymmddhhmm > .nc
Code availability
A notebook has been made available that forms a basic guide in using data produced from WHACS, with examples of a number of basic tasks that may be undertaken by researchers and data users, and tricks and tips to ensure smooth and efficient use of the data as supplied by the CSIRO Data Access Portal (requires GitHub login to access). https://github.com/AusClimateService/WHACS/tree/main/examples.
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Acknowledgements
This work was supported by the Australian Climate Service (ACS). Internal review for the Bureau of Meteorology was conducted by Isabela de Souza Cabral and Andy Taylor, with all comments greatly appreciated. Expert guidance and the dataset name “WHACS” were provided by Diana Greenslade. This work was undertaken with the assistance of resources and services from NCI, which is supported by the Australian Government. NCI provides a replication of the ERA5 used in this work. ASCAT data are produced by Remote Sensing Systems and sponsored by NASA Ocean Vector Winds Science Team. Data are available at www.remss.com.
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Grant Smith: Lead author, responsible for running wave model and post-processing wave hindcast data. Alberto Meucci: Lead author for sections on verification, undertaking analysis of wave hindcast dataset. Claire Spillman: co-lead and coordinator for the ACS Coastal Hazards Work Package 3. Ron Hoeke: co-lead and coordinator for the ACS Coastal Hazards Work Package 3 and expert advice on model development. Vanessa Hernaman: Lead modeller for coastal hazards, providing downscaling requirements and sensitivity testing for boundary conditions generated by the wave hindcast. Claire Trenham: Providing expert input and advice into model setup and development, and post processing techniques for data output correction and big data management and accessibility. Stefan Zieger: Lead wave modeler responsible for operational wave forecasts, SMC grid generation and expert advice on model setup and physics schemes. Bryan Hally: Generating output locations for spectral data based on geographical features and processing output for accessibility. Emilio Echevarria: Verification of model output and developing correction techniques for the dataset.
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Smith, G., Meucci, A., Spillman, C. et al. WHACS: An Improved Global Wave Hindcast for the Australian Climate Service. Sci Data (2026). https://doi.org/10.1038/s41597-026-06864-6
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DOI: https://doi.org/10.1038/s41597-026-06864-6
