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

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

Zarifsanayei, Amin Reza (Griffith University)
Antolínez, José A. Á. (TU Delft Coastal Engineering)
Cartwright, Nick (Griffith University)
Etemad-Shahidi, Amir (Edith Cowan University; Griffith University)
Strauss, Darrell (Griffith University)
Lemos, Gil (University of Lisbon)
Semedo, Alvaro (IHE Delft Institute for Water Education)
Kumar, Rajesh (Centre for Climate Research Singapore)
Dobrynin, Mikhail (Deutscher Wetterdienst)
Akpınar, Adem (Bursa Uludağ University)

2023

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.

uncertainty in LST projections
climate change
CMIP6 CSIRO wave projections
ensemble modelling
coastal evolution

http://resolver.tudelft.nl/uuid:bd75bfa9-0186-45bb-a347-b5ff43e410f3

https://doi.org/10.3389/fmars.2023.1188136

2296-7745

Frontiers in Marine Science, 10

Institutional Repository

journal article

© 2023 Amin Reza Zarifsanayei, José A. Á. Antolínez, Nick Cartwright, Amir Etemad-Shahidi, Darrell Strauss, Gil Lemos, Alvaro Semedo, Rajesh Kumar, Mikhail Dobrynin, Adem Akpınar