Downscaling Future Longshore Sediment Transport in South Eastern Australia

O’Grady, Julian; Babanin, Alexander V.; McInnes, Kathleen L.

doi:10.3390/jmse7090289

Cited by 8 publications

(6 citation statements)

References 61 publications

(81 reference statements)

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“…Downscaling is a process that brings global scale projections of the future climate to the local scale 23 , 24 . The application, or downscaling, of extreme wave conditions to coastal impact modelling can be resource intensive 5 , 25 .…”

Section: Introductionmentioning

confidence: 99%

Projected incremental changes to extreme wind-driven wave heights for the twenty-first century

O’Grady

Hemer

McInnes

et al. 2021

Sci Rep

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Global climate change will alter wind sea and swell waves, modifying the severity, frequency and impact of episodic coastal flooding and morphological change. Global-scale estimates of increases to coastal impacts have been typically attributed to sea level rise and not specifically to changes to waves on their own. This study provides a reduced complexity method for applying projected extreme wave changes to local scale impact studies. We use non-stationary extreme value analysis to distil an incremental change signal in extreme wave heights and associate this with a change in the frequency of events globally. Extreme wave heights are not projected to increase everywhere. We find that the largest increases will typically be experienced at higher latitudes, and that there is high ensemble model agreement on an increase (doubling of events) for the waters south of Australia, the Arabian Sea and the Gulf of Guinea by the end of the twenty-first century.

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Section: Introductionmentioning

confidence: 99%

Projected incremental changes to extreme wind-driven wave heights for the twenty-first century

O’Grady

Hemer

McInnes

et al. 2021

Sci Rep

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“…As illustrated in Figure 9, the use of some GCM-Ws (e.g., MIROC5 and GFDL-CM3) under different emission scenarios can even alter the sign (i.e., increase or decrease) of the projected changes in LST. Such interactions can challenge the reliability of any coastal sediment transport projections, conducted by arbitrarily choosing the GCM-Ws forcing datasets and emission scenarios (e.g., Dastgheib et al, 2016;O'Grady et al, 2019;Chowdhury et al, 2020). Apart from the aforementioned points, it seems that applying bias corrections could sometimes slightly manipulate the patterns of the LST projections under different emission scenarios, compared to those of the original forcing datasets (see Figure 9, the projections associated with BCC-CSM1.1 and ACCESS1.0 forcing conditions at site G).…”

Section: Resultsmentioning

confidence: 99%

“…In this way, the computational costs of sediment transport simulations are decreased. A few studies have tried to employ a more complex sediment transport model (i.e., process-based model; e.g., Bonaldo et al, 2015;O'Grady et al, 2019). To the knowledge of the authors, sampling and quantifying uncertainties from the common sources of uncertainty (namely of emission scenarios, GCM-Ws, LST models, and their non-linear interactions) in a systematic way, has been overlooked in the literature.…”

Section: Introductionmentioning

confidence: 99%

Uncertainties in the Projected Patterns of Wave-Driven Longshore Sediment Transport Along a Non-straight Coastline

et al. 2022

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This study quantifies the uncertainties in the projected changes in potential longshore sediment transport (LST) rates along a non-straight coastline. Four main sources of uncertainty, including the choice of emission scenarios, Global Circulation Model-driven offshore wave datasets (GCM-Ws), LST models, and their non-linear interactions were addressed through two ensemble modelling frameworks. The first ensemble consisted of the offshore wave forcing conditions without any bias correction (i.e., wave parameters extracted from eight datasets of GCM-Ws for baseline period 1979–2005, and future period 2081–2100 under two emission scenarios), a hybrid wave transformation method, and eight LST models (i.e., four bulk formulae, four process-based models). The differentiating factor of the second ensemble was the application of bias correction to the GCM-Ws, using a hindcast dataset as the reference. All ensemble members were weighted according to their performance to reproduce the reference LST patterns for the baseline period. Additionally, the total uncertainty of the LST projections was decomposed into the main sources and their interactions using the ANOVA method. Finally, the robustness of the LST projections was checked. Comparison of the projected changes in LST rates obtained from two ensembles indicated that the bias correction could relatively reduce the ranges of the uncertainty in the LST projections. On the annual scale, the contribution of emission scenarios, GCM-Ws, LST models and non-linear interactions to the total uncertainty was about 10–20, 35–50, 5–15, and 30–35%, respectively. Overall, the weighted means of the ensembles reported a decrease in net annual mean LST rates (less than 10% under RCP 4.5, a 10–20% under RCP 8.5). However, no robust projected changes in LST rates on annual and seasonal scales were found, questioning any ultimate decision being made using the means of the projected changes.

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“…Recently, the potential impact of climate change on wave-driven LST patterns has been studied in different regions (e.g., central coast of England, Zacharioudaki and Reeve, 2011; a stretch of coast in Italy, Bonaldo et al, 2015;West Africa coastline, Almar et al, 2015;Spanish coasts, Casas-Prat et al, 2016;Vietnam Coasts, Dastgheib et al, 2016; a short stretch of coast in southern Australia, O'Grady et al, 2019;Northwest of Portugal, Fernańdez-Fernańdez et al, 2020;Indian Coast, Chowdhury et al, 2020). A few studies (e.g., Zacharioudaki and Reeve, 2011) tried to manipulate the historical wave patterns to mimic climate change impacts on future wave and sediment transport patterns.…”

Section: Introductionmentioning

confidence: 99%

Uncertainties in wave-driven longshore sediment transport projections presented by a dynamic CMIP6-based ensemble

Zarifsanayei,

Antolínez,

Cartwright

et al. 2023

Front. Mar. Sci.

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In this study four experiments were conducted to investigate uncertainty in future longshore sediment transport (LST) projections due to: working with continuous time series of CSIRO CMIP6-driven waves (experiment #1) or sliced time series of waves from CSIRO-CMIP6-Ws and CSIRO-CMIP5-Ws (experiment #2); different wave-model-parametrization pairs to generate wave projections (experiment #3); and the inclusion/exclusion of sea level rise (SLR) for wave transformation (experiment #4). For each experiment, a weighted ensemble consisting of offshore wave forcing conditions, a surrogate model for nearshore wave transformation and eight LST models was used. The results of experiment # 1 indicated that the annual LST rates obtained from a continuous time series of waves were influenced by climate variability acting on timescales of 20-30 years. Uncertainty decomposition clearly reveals that for near-future coastal planning, a large part of the uncertainty arises from model selection and natural variability of the system (e.g., on average, 4% scenario, 57% model, and 39% internal variability). For the far future, the total uncertainty consists of 25% scenario, 54% model and 21% internal variability. Experiment #2 indicates that CMIP6 driven wave climatology yield similar outcomes to CMIP5 driven wave climatology in that LST rates decrease along the study area’s coast by less than 10%. The results of experiment #3 indicate that intra- and inter-annual variability of LST rates are influenced by the parameterization schemes of the wave simulations. This can increase the range of uncertainty in the LST projections and at the same time can limit the robustness of the projections. The inclusion of SLR (experiment #4) in wave transformation, under SSP1-2.6 and SSP5-8.5 scenarios, yields only meagre changes in the LST projections, compared to the case no SLR. However, it is noted that future research on SLR influence should include potential changes in nearshore profile shapes.

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Downscaling Future Longshore Sediment Transport in South Eastern Australia

Cited by 8 publications

References 61 publications

Projected incremental changes to extreme wind-driven wave heights for the twenty-first century

Projected incremental changes to extreme wind-driven wave heights for the twenty-first century

Uncertainties in the Projected Patterns of Wave-Driven Longshore Sediment Transport Along a Non-straight Coastline

Uncertainties in wave-driven longshore sediment transport projections presented by a dynamic CMIP6-based ensemble

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