An operational real-time eddy-resolving 1/16° global ocean nowcast/forecast system

O.M Smedstad,E.J Metzger,H.E Hurlburt,A.B Kara,J.F Shriver,C.P Murray,R.C Rhodes,A.J Wallcraft

doi:10.1109/oceans.2002.1192067

O.M Smedstad, E.J Metzger + Show 6 more

https://doi.org/10.1109/oceans.2002.1192067

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Publication Date: Oct 29, 2002

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A real-time eddy-resolving global ocean nowcast/forecast system has been running at the Naval Oceanographic Office (NAVOCEANO) since 18 October 2000 and it became an operational product on 27 September 2001. The system, which was developed at the Naval Research Laboratory (NRL), uses the NRL Layered Ocean Model (NLOM) with 1/16/spl deg/ resolution and seven layers in the vertical. Real-time satellite altimeter sea surface height (SSH) from TOPEX/Poseidon, ERS-2 and Geosat-Follow-On provided by NAVOCEANO's Altimeter Data Fusion Center, are assimilated into the model. The large size of the model grid (4906/spl times/2304/spl times/7) and operational requirements makes it necessary to use a computationally efficient ocean model and assimilation scheme. The assimilation consists of an optimum interpolation (OI) deviation analysis of SSH with the model as a first guess, a statistical inference technique for vertical mass field updates, geostrophic balance for the velocity updates outside the equatorial region and an incremental updating of the model fields to further reduce gravity wave generation. A spatially varying mesoscale covariance function determined from TOPEX/Poseidon and ERS-2 data is used in the OI analysis. The sea surface temperature (SST) assimilation consists of relaxing the NLOM SST to the Modular Ocean Data Assimilation System (MODAS) SST analysis which is performed daily at NAVOCEANO. Real-time and archived results from the model can be viewed at the NRL Website http://www.ocean.nrlssc.navy.mil/global/spl I.bar/nlom. This includes many zoom regions, nowcasts and forecasts of SSH, upper ocean currents and SST, forecast verification statistics, subsurface temperature cross-sections, the amount of altimeter data used for each nowcast from each satellite and nowcast comparisons with unassimilated data. The results show that the model has predictive skill of the mesoscale variability for at least one month.

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