Ocean Science www.ocean-sci.net 1812-0784 1812-0792 6 1 2010 10.5194/os-6-269-2010 http://www.ocean-sci.net/6/269/2010/ http://www.ocean-sci.net/6/269/2010/os-6-269-2010.html http://www.ocean-sci.net/6/269/2010/os-6-269-2010.pdf 269 284 2010-02-25 Impact of global ocean model resolution on sea-level variability with emphasis on interannual time scales T. Penduff thierry.penduff@legi.grenoble-inp.fr M. Juza L. Brodeau G. C. Smith B. Barnier J.-M. Molines A.-M. Treguier G. Madec Laboratoire des Écoulements Géophysiques et Industriels, UMR 5519, CNRS and Université de Grenoble, BP 53, 38041, Grenoble, France Department of Oceanography, The Florida State University, Tallahassee, USA National Oceanography Centre, Southampton, UK Laboratoire de Physique des Océans, UMR 6523, CNRS, IFREMER and UBO, 29280 Plouzané, France Laboratoire d'Océanographie et du Climat: Expérimentations et Approches Numériques, UMR 7159, CNRS, IPSL, and UPMC, 75252 Paris, France now at: Northwest Atlantic Fisheries Centre, Fisheries and Ocean Canada, St John's, Canada Four global ocean/sea-ice simulations driven by the same realistic 47-year daily atmospheric forcing were performed by the DRAKKAR group at 2°, 1°, &frac12°, and ¼° resolutions. Simulated mean sea-surface heights (MSSH) and sea-level anomalies (SLA) are collocated over the period 1993–2004 onto the AVISO dataset. MSSH fields are compared with an inverse estimate. SLA datasets are filtered and compared over various time and space scales with AVISO regarding three characteristics: SLA standard deviations, spatial correlations between SLA variability maps, and temporal correlations between observed and simulated band-passed filtered local SLA timeseries. Beyond the 2°−1° transition whose benefits are moderate, further increases in resolution and associated changes in subgrid scale parameterizations simultaneously induce (i) strong increases in SLA standard deviations, (ii) strong improvements in the spatial distribution of SLA variability, and (iii) slight decreases in temporal correlations between observed and simulation SLA timeseries. These 3 effects are not only clear on mesoscale (14–180 days) and quasi-annual (5–18 months) fluctuations, but also on the slower (interannual), large-scale variability ultimately involved in ocean-atmosphere coupled processes. 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