Will high-resolution global ocean models benefit coupled predictions on short-range to climate timescales?

Hewitt, H. T., Bell, M. J., Chassignet, E. P., Czaja, A., Ferreira, D. ORCID: https://orcid.org/0000-0003-3243-9774, Griffies, S. M., Hyder, P., McClean, J. L., New, A. L. and Roberts, M. J. (2017) Will high-resolution global ocean models benefit coupled predictions on short-range to climate timescales? Ocean Modelling, 120. pp. 120-136. ISSN 1463-5003 doi: 10.1016/j.ocemod.2017.11.002

Abstract/Summary

As the importance of the ocean in the weather and climate system is increasingly recognised, operational systems are now moving towards coupled prediction not only for seasonal to climate timescales but also for short-range forecasts. A three-way tension exists between the allocation of computing resources to refine model resolution, the expansion of model complexity/capability, and the increase of ensemble size. Here we review evidence for the benefits of increased ocean resolution in global coupled models, where the ocean component explicitly represents transient mesoscale eddies and narrow boundary currents. We consider lessons learned from forced ocean/sea-ice simulations; from studies concerning the SST resolution required to impact atmospheric simulations; and from coupled predictions. Impacts of the mesoscale ocean in western boundary current regions on the large-scale atmospheric state have been identified. Understanding of air-sea feedback in western boundary currents is modifying our view of the dynamics in these key regions. It remains unclear whether variability associated with open ocean mesoscale eddies is equally important to the large-scale atmospheric state. We include a discussion of what processes can presently be parameterised in coupled models with coarse resolution non-eddying ocean models, and where parameterizations may fall short. We discuss the benefits of resolution and identify gaps in the current literature that leave important questions unanswered.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/73645
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Elsevier
Download/View statistics	View download statistics for this item