ALBERT

Description: A series of Observing System Simulation Experiments (OSSEs) is carried out with a global data assimilation system at 1/4° resolution using simulated data derived from a 1/12° resolution free run simulation. The objective is to quantify how well multiple altimeter missions and Argo profiling floats can constrain a global data assimilation system but also to better understand the sensitivity of results to data assimilation techniques used in Mercator Ocean operational systems. Impact of multiple altimeter data is clearly evidenced. Forecasts of sea level and ocean currents are significantly improved when moving from one altimeter to two altimeters. In high eddy energy regions, sea level and surface current forecast errors when assimilating one altimeter data set are respectively 20 % and 45 % of the error of the simulation without assimilation. Forecasts of sea level and ocean currents continue to be improved when moving from one altimeter to two altimeters with a relative error reduction of almost 30 %. The addition of a third altimeter still improves the forecasts even at this medium 1/4° resolution and brings an additional relative error reduction of about 10 %. The error level of the analysis with one altimeter is close to the forecast error level when two or three altimeter data sets are assimilated. Assimilating altimeter data also improves the representation of the 3D ocean fields. The addition of Argo has a major impact to improve temperature and demonstrates the essential role of Argo together with altimetry to constrain a global data assimilation system. Salinity fields are only marginally improved. Results derived from these OSSEs are consistent with those derived from experiments with real data (observing system evaluations/OSEs) but they allow a more detailed characterization of errors on analyses and forecasts. Both OSEs and OSSEs should be systematically used and intercompared to test data assimilation systems and quantify the impact of existing observing systems.

Description: A series of observing system simulation experiments (OSSEs) is carried out with a global data assimilation system at 1∕4° resolution using simulated data derived from a 1∕12° resolution free-run simulation. The objective is to not only quantify how well multiple altimeter missions and Argo profiling floats can constrain the global ocean analysis and 7-day forecast at 1∕4° resolution but also to better understand the sensitivity of results to data assimilation techniques used in Mercator Ocean operational systems. The impact of multiple altimeter data is clearly evidenced even at a 1∕4° resolution. Seven-day forecasts of sea level and ocean currents are significantly improved when moving from one altimeter to two altimeters not only on the sea level, but also on the 3-D thermohaline structure and currents. In high-eddy-energy regions, sea level and surface current 7-day forecast errors when assimilating one altimeter data set are respectively 20 and 45 % of the error of the simulation without assimilation. Seven-day forecasts of sea level and ocean currents continue to be improved when moving from one altimeter to two altimeters with a relative error reduction of almost 30 %. The addition of a third altimeter still improves the 7-day forecasts even at this medium 1∕4° resolution and brings an additional relative error reduction of about 10 %. The error level of the analysis with one altimeter is close to the 7-day forecast error level when two or three altimeter data sets are assimilated. Assimilating altimeter data also improves the representation of the 3-D ocean fields. The addition of Argo has a major impact on improving temperature and demonstrates the essential role of Argo together with altimetry in constraining a global data assimilation system. Salinity fields are only marginally improved. Results derived from these OSSEs are consistent with those derived from experiments with real data (observing system evaluations, OSEs) but they allow for more detailed characterisation of errors on analyses and 7-day forecasts. Both OSEs and OSSEs should be systematically used and intercompared to test data assimilation systems and quantify the impact of existing observing systems.