Modelling the global coastal ocean

Holt, Jason; Harle, James; Proctor, Roger; Michel, Sylvain; Ashworth, Mike; Batstone, Crispian; Allen, Icarus; Holmes, Robert R.; Smyth, Tim; Haines, Keith; Bretherton, Daniel; Smith, G. C. Moore

doi:10.1098/rsta.2008.0210

Cited by 88 publications

(86 citation statements)

References 30 publications

(29 reference statements)

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“…The geographically varying projections in the AR5 were created using an ensemble of 21 general circulation models from the Coupled Model Intercomparison Project Phase 5 (CMIP5 19,13 ), together with state of the art modelling of glaciers and ice sheets. The sea level rise projections include thermal expansion, the effect of atmospheric loading, land-ice melt (including estimates of ice sheet rapid dynamic contributions derived from the literature), glacial isostatic adjustment and terrestrial water storage changes.…”

Section: Background Sea Level Risementioning

confidence: 99%

“…A 0.1° (approx. 11 km) resolution hydrodynamic model of the coastal region of the Bay of Bengal, based on the GCOMS model framework 13 , was run for three different climate scenarios for the 21 st century. These three climate scenarios are all for a medium Business-As-Usual greenhouse gas forcing scenario (the SRES A1B scenario) but differ in their atmospheric forcing conditions, with these being obtained from alternative atmospheric model projections.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the increased frequency of extreme sea levels in the Ganges–Brahmaputra–Meghna delta due to sea level rise and other effects of climate change

Kay

Caesar

Wolf

et al. 2015

Environ. Sci.: Processes Impacts

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Coastal flooding due to storm surge and high tides is a serious risk for inhabitants of the Ganges-Brahmaputra-Meghna (GBM) delta, as much of the land is close to sea level. Climate change could lead to large areas of land being subject to increased flooding, salinization and ultimate abandonment in both West Bengal, India, and Bangladesh. IPCC 5 th assessment modelling of sea level rise and estimates of subsidence rates from the EU IMPACT2C project suggest that sea level in the GBM delta region may rise by 0.63 to 0.88 m by 2090, with some studies suggesting this could be up to 0.5 m higher if potential substantial melting of the West Antarctic ice sheet is included. These sea level rise scenarios lead to increased frequency of high water coastal events. Any effect of climate change on the frequency and severity of storms can also have an effect on extreme sea levels. A shelf-sea model of the Bay of Bengal has been used to investigate how the combined effect of sea level rise and changes in other environmental conditions under climate change may alter the frequency of extreme sea level events for the period 1971 to 2099. The model was forced using atmospheric and oceanic boundary conditions derived from climate model projections and the future scenario increase in sea level was applied at its ocean boundary. The model results show an increased likelihood of extreme sea level events through the 21st century, with the frequency of events increasing greatly in the second half of the century: water levels that occurred at decadal time intervals under present-day model conditions occurred in most years by the middle of the 21 st century and 3-15 times per year by 2100. The heights of the most extreme events tend to increase more in the first half of the century than the second. The modelled scenarios provide a case study of how sea level rise and other effects of climate change may combine to produce a greatly increased threat to life and property in the GBM delta by the end of this century.

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Section: Background Sea Level Risementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling the increased frequency of extreme sea levels in the Ganges–Brahmaputra–Meghna delta due to sea level rise and other effects of climate change

Kay

Caesar

Wolf

et al. 2015

Environ. Sci.: Processes Impacts

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“…The nesting procedure is similar in principle to other nested models (Holt et al, 2009;Korres and Lascaratos, 2003;Nittis et al, 2006), but the uniqueness of MSN_Flood is a novel approach to boundary formulation through an incorporation of ghost cells (GCs) in a manner that the nested boundary operates as an internal boundary. GCs are specified adjacent to nested boundaries so that the boundary configuration consist of two rows/columns of CG cells: internal boundary cells and the adjacent exterior ghost cells.…”

Section: Nesting Structure and Proceduresmentioning

confidence: 99%

Development of high-resolution multi-scale modelling system for simulation of coastal-fluvial urban flooding

Comer

Olbert

Hartnett

2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Urban developments in coastal zones are often exposed to natural hazards such as flooding. In this research, a state-of-the-art, multi-scale nested flood (MSN_Flood) model is applied to simulate complex coastal-fluvial urban flooding due to combined effects of tides, surges and river discharges. Cork city on Ireland's southwest coast is a study case. The flood modelling system comprises a cascade of four dynamically linked models that resolve the hydrodynamics of Cork Harbour and/or its sub-region at four scales: 90, 30, 6 and 2 m.Results demonstrate that the internalization of the nested boundary through the use of ghost cells combined with a tailored adaptive interpolation technique creates a highly dynamic moving boundary that permits flooding and drying of the nested boundary. This novel feature of MSN_Flood provides a high degree of choice regarding the location of the boundaries to the nested domain and therefore flexibility in model application. The nested MSN_Flood model through dynamic downscaling facilitates significant improvements in accuracy of model output without incurring the computational expense of high spatial resolution over the entire model domain. The urban flood model provides full characteristics of water levels and flow regimes necessary for flood hazard identification and flood risk assessment.

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“…Large, irregularly shaped nests (e.g. Holt et al, 2009) would be good option, not overrefining in the open ocean and limiting the number of grids and connections between them. This would require substantial development to AGRIF or an alternative approach.…”

Section: Options For Multiscale Modellingmentioning

confidence: 99%

Prospects for improving the representation of coastal and shelf seas in global ocean models

et al. 2017

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Abstract. Accurately representing coastal and shelf seas in global ocean models represents one of the grand challenges of Earth system science. They are regions of immense societal importance through the goods and services they provide, hazards they pose and their role in global-scale processes and cycles, e.g. carbon fluxes and dense water formation. However, they are poorly represented in the current generation of global ocean models. In this contribution, we aim to briefly characterise the problem, and then to identify the important physical processes, and their scales, needed to address this issue in the context of the options available to resolve these scales globally and the evolving computational landscape.We find barotropic and topographic scales are well resolved by the current state-of-the-art model resolutions, e.g. nominal 1/12 • , and still reasonably well resolved at 1/4 • ; here, the focus is on process representation. We identify tides, vertical coordinates, river inflows and mixing schemes as four areas where modelling approaches can readily be transferred from regional to global modelling with substantial benefit. In terms of finer-scale processes, we find that a 1/12 • global model resolves the first baroclinic Rossby radius for only ∼ 8 % of regions < 500 m deep, but this increases to ∼ 70 % for a 1/72 • model, so resolving scales globally requires substantially finer resolution than the current state of the art.We quantify the benefit of improved resolution and process representation using 1/12 • global-and basin-scale northern North Atlantic nucleus for a European model of the ocean (NEMO) simulations; the latter includes tides and a k-ε vertical mixing scheme. These are compared with global stratification observations and 19 models from CMIP5. In terms of correlation and basin-wide rms error, the high-resolution models outperform all these CMIP5 models. The model with tides shows improved seasonal cycles compared to the highresolution model without tides. The benefits of resolution are particularly apparent in eastern boundary upwelling zones.To explore the balance between the size of a globally refined model and that of multiscale modelling options (e.g. finite element, finite volume or a two-way nesting approach), we consider a simple scale analysis and a conceptual grid refining approach. We put this analysis in the context of evolving computer systems, discussing model turnaround time, scalability and resource costs. Using a simple cost model compared to a reference configuration (taken to be a 1/4 • global model in 2011) and the increasing performance of the UK Research Councils' computer facility, we estimate an unstructured mesh multiscale approach, resolving process scales down to 1.5 km, would use a comparable share of the computer resource by 2021, the two-way nested multiscale approach by 2022, and a 1/72 • global model by 2026. However, we also note that a 1/12 • global model would not have a comparable computational cost to a 1 • global model in 2017 until 2027. Hence, we conc...

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Modelling the global coastal ocean

Cited by 88 publications

References 30 publications

Modelling the increased frequency of extreme sea levels in the Ganges–Brahmaputra–Meghna delta due to sea level rise and other effects of climate change

Modelling the increased frequency of extreme sea levels in the Ganges–Brahmaputra–Meghna delta due to sea level rise and other effects of climate change

Development of high-resolution multi-scale modelling system for simulation of coastal-fluvial urban flooding

Prospects for improving the representation of coastal and shelf seas in global ocean models

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