Multi-decadal variability in seasonal mean sea level along  the North Sea coast

Frederikse, Thomas; Gerkema, Theo

doi:10.5194/os-14-1491-2018

Cited by 18 publications

(28 citation statements)

References 29 publications

(36 reference statements)

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“…The variability is largest in the German Bight, and smaller at the British coast of the North Sea. This is in line with the twentieth century observations at TG stations around the North Sea (Dangendorf et al 2013;Frederikse and Gerkema 2018). The results are similar for RCP4.5 ( Supplementary Fig.…”

Section: Projected Changes In the Seasonal Sea-level Cyclesupporting

confidence: 90%

Improving sea-level projections on the Northwestern European shelf using dynamical downscaling

et al. 2020

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Changes in ocean properties and circulation lead to a spatially non-uniform pattern of ocean dynamic sea-level change (DSLC). The projections of ocean dynamic sea level presented in the IPCC AR5 were constructed with global climate models (GCMs) from the Coupled Model Intercomparison Project 5 (CMIP5). Since CMIP5 GCMs have a relatively coarse resolution and exclude tides and surges it is unclear whether they are suitable for providing DSLC projections in shallow coastal regions such as the Northwestern European Shelf (NWES). One approach to addressing these shortcomings is dynamical downscaling-i.e. using a high-resolution regional model forced with output from GCMs. Here we use the regional shelf seas model AMM7 to show that, depending on the driving CMIP5 GCM, dynamical downscaling can have a large impact on DSLC simulations in the NWES region. For a business-as-usual greenhouse gas concentration scenario, we find that downscaled simulations of twenty-first century DSLC can be up to 15.5 cm smaller than DSLC in the GCM simulations along the North Sea coastline owing to unresolved processes in the GCM. Furthermore, dynamical downscaling affects the simulated time of emergence of sea-level change (SLC) above sea-level variability, and can result in differences in the projected change of the amplitude of the seasonal cycle of sea level of over 0.3 mm/yr. We find that the difference between GCM and downscaled results is of similar magnitude to the uncertainty of CMIP5 ensembles used for previous DSLC projections. Our results support a role for dynamical downscaling in future regional sea-level projections to aid coastal decision makers.

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Section: Projected Changes In the Seasonal Sea-level Cyclesupporting

confidence: 90%

Improving sea-level projections on the Northwestern European shelf using dynamical downscaling

et al. 2020

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“…In our model, tides are prescribed by imposing water elevation at the open boundary, which is optimized by data assimilation and validation of the shallow-water tides using tidal gauge data (Egbert et al, 2010). It should be noted that this open boundary water elevation, despite producing a good fit with the observed Oosterschelde water level in our model (Jiang et al, 2019a), does not include the subtidal effects on coastal sea surface height, which is mostly driven by remote winds (Frederikse and Gerkema, 2018). If the impacts of remote wind forcing are considered, the variability of turnover times should be enhanced in winter and fall since these two seasons are found to exhibit the largest wind-driven sea level variability along the North Sea coast (Frederikse and Gerkema, 2018).…”

Section: Discussionmentioning

confidence: 99%

Decomposing the intra-annual variability of flushing characteristics in a tidal bay along the North Sea

Jiang

Soetaert

Gerkema

2019

Journal of Sea Research

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“…The magnitude of the interannual to multi-decadal variability of seasonal mean sea level and the extent to which that variability can be explained by atmospheric forcing are larger for autumn and winter than for spring and summer (Dangendorf et al, 2012;Dangendorf et al, 2013a;Frederikse & Gerkema, 2018). For example, a regression on local wind stress explains 80-90% of the observed interannual sea-level variability at Cuxhaven (Germany) in autumn and winter, compared to 50-60% in spring and summer (Dangendorf et al, 2013a).…”

Section: Introductionmentioning

confidence: 99%

“…For example, a regression on local wind stress explains 80-90% of the observed interannual sea-level variability at Cuxhaven (Germany) in autumn and winter, compared to 50-60% in spring and summer (Dangendorf et al, 2013a). This reflects the seasonality of atmospheric variability and introduces seasonal differences in sealevel trends computed over a few decades, especially in the southeastern North Sea (Dangendorf et al, 2012;Dangendorf et al, 2013b;Frederikse & Gerkema, 2018;Marcos & Tsimplis, 2007).…”

Section: Introductionmentioning

confidence: 99%

The Effect of Wind Stress on Seasonal Sea-Level Change on the Northwestern European Shelf

et al. 2022

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Projections of relative sea-level change (RSLC) are commonly reported at an annual mean basis. The seasonality of RSLC is often not considered, even though it may modulate the impacts of annual mean RSLC. Here, we study seasonal differences in 21st-century ocean dynamic sea-level change (DSLC, 2081-2100 minus 1995-2014) on the Northwestern European Shelf (NWES) and their drivers, using an ensemble of 33 CMIP6 models complemented with experiments performed with a regional ocean model. For the high-end emissions scenario SSP5-8.5, we find substantial seasonal differences in ensemble mean DSLC, especially in the southeastern North Sea. For example, at Esbjerg (Denmark), winter mean DSLC is on average 8.4 cm higher than summer mean DSLC. Along all coasts on the NWES, DSLC is higher in winter and spring than in summer and autumn. For the low-end emissions scenario SSP1-2.6, these seasonal differences are smaller. Our experiments indicate that the changes in winter and summer sea-level anomalies are mainly driven by regional changes in wind-stress anomalies, which are generally southwesterly and east-northeasterly over the NWES, respectively. In spring and autumn, regional wind-stress changes play a smaller role. We also show that CMIP6 models not resolving currents through the English Channel cannot accurately simulate the effect of seasonal wind-stress changes on he NWES. Our results imply that using projections of annual mean RSLC may underestimate the projected changes in extreme coastal sea levels in spring and winter. Additionally, changes in the seasonal sea-level cycle may affect groundwater dynamics and the inundation characteristics of intertidal ecosystems.

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Multi-decadal variability in seasonal mean sea level along the North Sea coast

Cited by 18 publications

References 29 publications

Improving sea-level projections on the Northwestern European shelf using dynamical downscaling

Improving sea-level projections on the Northwestern European shelf using dynamical downscaling

Decomposing the intra-annual variability of flushing characteristics in a tidal bay along the North Sea

The Effect of Wind Stress on Seasonal Sea-Level Change on the Northwestern European Shelf

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