Publication Date:
2019-03-01
Description:
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 WW3 (WaveWatchIII) and forced by ECMWF
atmospheric fields at 1/8o horizontal resolution. The model solutions are corrected by the data
assimilation system (3D variational-3Dvar scheme adapted to the oceanic assimilation problem, Dobricic
and Pinardi, 2008) with a daily assimilation cycle of satellite Sea Level Anomaly (SLA) and vertical
profiles of Temperature and Salinity. In this study we present a new estimate the 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 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. Latest developments include the implementation of an upgraded 3Dvar (Storto et al.
2012) for a high-resolution model, 1/24o in the horizontal and 141 vertical levels
Description:
Published
Description:
Bergen, Norway
Description:
3SR. AMBIENTE - Servizi e ricerca per la Società
Keywords:
Data assimilation
;
EOFs
;
model error
;
observational error
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
Oral presentation
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