Assessment of the FOAM global data assimilation system for real-time operational ocean forecasting

An operational system to forecast the state of the global ocean a few days ahead has been implemented at the UK Met. Office (UKMO). The system, known as the Forecasting Ocean Assimilation Model (FOAM), consists of a 1 degrees x 1 degrees resolution numerical ocean model driven by surface fluxes from the UKMO numerical weather prediction (NWP) suite and a modified successiv e correction data assimilation scheme for thermal observations. The assimil ation scheme is assessed here in a series of I-year integrations by compari son with 'independent' thermal profile observations and climatology. Assimi lating temperature observations significantly reduces model errors in the u pper ocean and results in temperature analyses that on average are closer t o independent observations than climatology. The specific results depend on location and depth. The extent to which the data assimilation scheme is ab le to compensate for uncertainties in the surface forcing fluxes is also as sessed by comparing integrations forced with climatological and NWP fluxes. Assimilating data is able to compensate for uncertainties in the surface h eat forcing fluxes and significantly reduces the impact from uncertainties in the surface wind stress. Crown Copyright (C) 2000 Published by Elsevier Science B.V. All rights reserved.