PREDICTING ENVIRONMENTAL EXTREMES IN A PERIOD OF CLIMATE CHANGE
Grant number: DP160100738 | Funding period: 2016 - 2020
This project has the potential to reduce the uncertainty in the predictions of extreme winds and waves used to design and operate coastal and offshore facilities. Predictions are typically achieved by extrapolating recorded data to predict probable extremes. The uncertainties associated with this approach are very large. This project aims to develop a new approach called ‘large ensemble aggregate’ analysis, which brings together data from alternative model predictions or alternative measurement locations to expand the effective data and avoid the necessity for statistical extrapolation. This approach may significantly reduce the uncertainty in estimating extreme values. This would reduce the..View full description
Related publications (10)
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Robustness and uncertainties in global multivariate wind-wave climate projections
Joao Morim, Mark Hemer, Xiaolan L Wang, Nick Cartwright, Claire Trenham, Alvaro Semedos, Ian Young, Lucy Bricheno, Paula Camus, Merce Casas-Prat, Li Erikson, Lorenzo Mentaschi, Nobuhito Mori, Tomoya Shimura, Ben Timmermans, Ole Aarnes, Oyvind Breivik, Arno Behrens, Mikhail Dobrynin, Melisa Menendez
Understanding climate-driven impacts on the multivariate global wind-wave climate is paramount to effective offshore/coastal clima..