nerc.ac.uk

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

Holt, Jason; Hyder, Pat; Ashworth, Mike; Harle, James; Hewitt, Helene T.; Liu, Hedong; New, Adrian L.; Pickles, Stephen; Porter, Andrew; Popova, Ekaterina; Allen, J. Icarus; Siddorn, John; Wood, Richard. 2017 Prospects for improving the representation of coastal and shelf seas in global ocean models. Geoscientific Model Development, 10. 499-523. 10.5194/gmd-10-499-2017

Before downloading, please read NORA policies.
[img]
Preview
Text (Open Access paper)
gmd-10-499-2017.pdf - Published Version
Available under License Creative Commons Attribution.

Download (5MB) | Preview
[img]
Preview
Text
gmd-2016-145-manuscript-version3.pdf - Accepted Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview

Abstract/Summary

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 through 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 identify and quantify 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 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. We demonstrate this through basin scale northern North Atlantic simulations and analysis of global profile data, which particularly shows the need for increased vertical resolution in shallower water. In terms of finer scale processes, we find that a 1/12° global model resolves the 1st baroclinic Rossby Radius for only ~?20?% of regions <?500?m deep, but this increases to ~?90?% for a 1/72° model, so to resolve these scales globally requires substantially finer resolution than the current state-of-the-art. We consider a simple scale analysis and conceptual grid refining approach 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 2-way nesting approach). We put this analysis in the context of evolving computer systems, using the UK’s national research facility as an example. This doubles in peak performance every ~?1.2 years. Using a simple cost-model compared to a reference configuration (taken to be a 1/4° global model in 2011), 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 2024, the 2-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 today until 2027. Hence, we conclude that for computationally expensive models (e.g. for oceanographic research or operational oceanography), resolving scales to ~?1.5?km would be routinely practical in about a decade given substantial effort on numerical and computational development. For complex Earth System Models this extends to about two decades, suggesting the focus here needs to be on improved process parameterisation to meet these challenges.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.5194/gmd-10-499-2017
ISSN: 1991-9603
Date made live: 10 Jan 2017 11:04 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/515736

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...