Articles | Volume 28, issue 5
https://doi.org/10.5194/hess-28-1251-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-1251-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
15 Mar 2024
Review article |
| 15 Mar 2024
| 15 Mar 2024
A systematic review of climate change science relevant to Australian design flood estimation
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia
Seth Westra
School of Architectural and Civil Engineering, University of Adelaide, Adelaide, Australia
Rory Nathan
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia
Acacia Pepler
Australian Bureau of Meteorology, Sydney, Australia
National Environmental Science Program Climate System Hub, Sydney, Australia
Timothy H. Raupach
National Environmental Science Program Climate System Hub, Sydney, Australia
Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia
ARC Centre of Excellence for Climate Extremes, University of New South Wales, Kensington, New South Wales, Australia
Andrew Dowdy
Australian Bureau of Meteorology, Sydney, Australia
National Environmental Science Program Climate System Hub, Sydney, Australia
School of Geography, Earth and Atmospheric Sciences, University of Melbourne, Parkville, Victoria, Australia
Fiona Johnson
Water Research Centre, School of Civil and Environmental Engineering, University of New South Wales, Kensington, New South Wales, Australia
Australia Research Council Training Centre in Data Analytics for Resources and Environments, Kensington, New South Wales, Australia
Michelle Ho
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia
Kathleen L. McInnes
CSIRO Environment, Aspendale, Australia
Doerte Jakob
Australian Bureau of Meteorology, Melbourne, Australia
Jason Evans
National Environmental Science Program Climate System Hub, Sydney, Australia
Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia
ARC Centre of Excellence for Climate Extremes, University of New South Wales, Kensington, New South Wales, Australia
Gabriele Villarini
Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
High Meadows Environmental Institute, Princeton University, Princeton, New Jersey, USA
Hayley J. Fowler
School of Engineering, Newcastle University, Newcastle upon Tyne, UK
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Acacia S. Pepler and Irina Rudeva
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Keirnan Fowler, Murray Peel, Margarita Saft, Tim J. Peterson, Andrew Western, Lawrence Band, Cuan Petheram, Sandra Dharmadi, Kim Seong Tan, Lu Zhang, Patrick Lane, Anthony Kiem, Lucy Marshall, Anne Griebel, Belinda E. Medlyn, Dongryeol Ryu, Giancarlo Bonotto, Conrad Wasko, Anna Ukkola, Clare Stephens, Andrew Frost, Hansini Gardiya Weligamage, Patricia Saco, Hongxing Zheng, Francis Chiew, Edoardo Daly, Glen Walker, R. Willem Vervoort, Justin Hughes, Luca Trotter, Brad Neal, Ian Cartwright, and Rory Nathan
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Timothy H. Raupach, Andrey Martynov, Luca Nisi, Alessandro Hering, Yannick Barton, and Olivia Martius
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Chun-Hsu Su, Nathan Eizenberg, Dörte Jakob, Paul Fox-Hughes, Peter Steinle, Christopher J. White, and Charmaine Franklin
Geosci. Model Dev., 14, 4357–4378, https://doi.org/10.5194/gmd-14-4357-2021, https://doi.org/10.5194/gmd-14-4357-2021, 2021
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Sanaa Hobeichi, Gab Abramowitz, and Jason P. Evans
Hydrol. Earth Syst. Sci., 25, 3855–3874, https://doi.org/10.5194/hess-25-3855-2021, https://doi.org/10.5194/hess-25-3855-2021, 2021
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Evapotranspiration (ET) links the water, energy and carbon cycle on land. Reliable ET estimates are key to understand droughts and flooding. We develop a new ET dataset, DOLCE V3, by merging multiple global ET datasets, and we show that it matches ET observations better and hence is more reliable than its parent datasets. Next, we use DOLCE V3 to examine recent changes in ET and find that ET has increased over most of the land, decreased in some regions, and has not changed in some other regions
Max Kulinich, Yanan Fan, Spiridon Penev, Jason P. Evans, and Roman Olson
Geosci. Model Dev., 14, 3539–3551, https://doi.org/10.5194/gmd-14-3539-2021, https://doi.org/10.5194/gmd-14-3539-2021, 2021
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We present a novel stochastic approach based on Markov chains to estimate climate model weights of multi-model ensemble means. This approach showed improved performance (better correlation with observations) over existing alternatives during cross-validation and model-as-truth tests. The results of this comparative analysis should serve to motivate further studies in applications of Markov chain and other nonlinear methods to find optimal model weights for constructing ensemble means.
Wenyan Wu, Seth Westra, and Michael Leonard
Hydrol. Earth Syst. Sci., 25, 2821–2841, https://doi.org/10.5194/hess-25-2821-2021, https://doi.org/10.5194/hess-25-2821-2021, 2021
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Flood probability estimation is important for applications such as land use planning, reservoir operation, infrastructure design and safety assessments. However, it is a challenging task, especially in estuarine areas where floods are caused by both intense rainfall and storm surge. This study provides a review of approaches to flood probability estimation in these areas. Based on analysis of a real-world river system, guidance on method selection is provided.
Viswanathan Bringi, Kumar Vijay Mishra, Merhala Thurai, Patrick C. Kennedy, and Timothy H. Raupach
Atmos. Meas. Tech., 13, 4727–4750, https://doi.org/10.5194/amt-13-4727-2020, https://doi.org/10.5194/amt-13-4727-2020, 2020
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The raindrop size distribution and its moments are fundamental in many areas, such as radar measurement of rainfall using polarimetry and numerical modeling of the microphysical processes of rain formation and evolution. We develop a technique which uses advanced radar measurements and complete drop size distributions using two collocated instruments to retrieve the lower-order moments such as total drop concentration and rain water content. We demonstrate a proof-of-concept using a case study.
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Short summary
In response to flood risk, design flood estimation is a cornerstone of infrastructure design and emergency response planning, but design flood estimation guidance under climate change is still in its infancy. We perform the first published systematic review of the impact of climate change on design flood estimation and conduct a meta-analysis to provide quantitative estimates of possible future changes in extreme rainfall.
In response to flood risk, design flood estimation is a cornerstone of infrastructure design and...
