Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/12189
Authors: Pistoia, Jenny* 
Clementi, Emanuela* 
Delrosso, Damiano* 
Mattia, Gelsomina* 
Fratianni, Claudia* 
Drudi, Massimiliano* 
Grandi, Alessandro* 
Padeletti, Davide* 
Di Pietro, Pierluigi* 
Storto, Andrea* 
Pinardi, Nadia* 
Title: Last improvements in the data assimilation scheme for the Mediterranean Analysis and Forecast system of the Copernicus Marine Service
Issue Date: 3-Oct-2017
URL: http://eurogoos.eu/download/publications/EuroGOOS-2017-Conference-Proceedings.pdf
Keywords: Data assimilation
EOFs
model error
observational error
Abstract: The Mediterranean Forecasting System (MFS) is a numerical ocean prediction system that produces analyses, reanalyses and short term forecasts for the entire Mediterranean Sea and its Atlantic Ocean adjacent areas. The system is now part of the Copernicus Marine Environment Monitoring Service (CMEMS) providing regular and systematic information about the physical state and dynamics of the Mediterranean Sea through the Med-MFC (Mediterranean Monitoring and Forecasting Center). MFS has been implemented in the Mediterranean Sea with 1/16o horizontal resolution and 72 vertical levels and is composed by the hydrodynamic model NEMO (Nucleus for European Modelling of the Ocean) 2-way online coupled with the third generation wave model WaveWatchIII (Clementi et al., 2017a) and forced by ECMWF atmospheric fields at 1/8° horizontal resolution. The model solutions are corrected by the data assimilation system (3D variational scheme, Dobricic and Pinardi, 2008) with a daily assimilation cycle of along track satellite Sea Level Anomaly (SLA) and vertical profiles of Temperature and Salinity from ARGO and gliders. In this study we present a new estimate of the background error covariance matrix with vertical Empirical Orthogonal Functions (EOFs) that are defined at each grid point of the model domain in order to better account for the error covariance between temperature and salinity in the shelf and open ocean areas. Moreover the Observational error covariance matrix is z-dependent and varies in each month. This new dataset has been tested and validated for more than 2 years against a background error correlation matrix varying only seasonally and in thirteen sub-regions of the Mediterranean Sea (Dobricic et al. 2005).
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