EGU24-3679, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-3679
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Assessment of different CMIP6 regional wind wave climate downscaling approaches – From a global to a local perspective

Alberto Meucci1,2, Matteo Lorenzo3, Jin Liu1,4, Jozef Syktus5, Claire Trenham6, Vanessa Hernaman2, Ron Hoeke2, Miguel Onorato3, and Ian Young1
Alberto Meucci et al.
  • 1University of Melbourne, Melbourne School of Engineering, Department of Infrastructure Engineering, Australia (alberto.meucci@gmail.com)
  • 2Climate Science Centre, CSIRO Environment, Aspendale, Australia
  • 3Department of Physics and INFN, University of Turin, Turin, Italy
  • 4Department of Energy, Environment and Climate Action, Melbourne, Victoria, Australia
  • 5The University of Queensland, School of the Environment, Brisbane, Australia
  • 6Climate Science Centre, CSIRO Environment, Canberra, Australia

Wind waves play a crucial role in coastal dynamics and can significantly impact coastal sea levels, especially during extreme events. Ocean winds are changing as the Earth is warming, and hence the waves. The Australian Climate Service (https://www.acs.gov.au/), recognised wind waves as a crucial element to support future coastal climate mitigation and adaptation strategies. Wind wave climate future projections are, however, plagued by uncertainties. One of the primary sources of uncertainty originates from the resolution of the Coupled Model Intercomparison Project (CMIP) General Circulation Model (GCM) surface wind speed products. We hereby assess different approaches to regional wind wave climate modelling, to understand the impact of the CMIP6 GCM wind speed resolution. We evaluate the Southeast Australia wave climate results from an unstructured grid regional wave model nested in a global wave model. We compare 30 years (1985-2014) of historical wave climate simulations using wind vectors from the CMIP6 Meteorological Research Institute (MRI) CMIP, AMIP, and HighResMIP experiments (nominal resolutions of ~150 km for CMIP and AMIP, and 25 km for HighResMIP). We then compare these results with the wave model forced by the MRI CMIP surface winds dynamically downscaled with the Conformal Cubic Atmospheric Model (CCAM) (~12.5 km resolution). The findings indicate that the wind wave climate models yield divergent results, particularly at the extremes where the most interest lies for future coastal sea level projections. We discuss the reasons for the differences and propose the best way forward for developing regional wind wave climate projections.

How to cite: Meucci, A., Lorenzo, M., Liu, J., Syktus, J., Trenham, C., Hernaman, V., Hoeke, R., Onorato, M., and Young, I.: Assessment of different CMIP6 regional wind wave climate downscaling approaches – From a global to a local perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3679, https://doi.org/10.5194/egusphere-egu24-3679, 2024.