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Ann. Geophys., 21, 189-204, 2003
www.ann-geophys.net/21/189/2003/
© European Geosciences Union 2003
Assimilation scheme of the Mediterranean Forecasting System: operational implementation
E. Demirov1, N. Pinardi2, C. Fratianni1, M. Tonani1, L. Giacomelli2, and P. De Mey3
1Instituto Nazionale di Geofisica e Vulcanologia, Rome, Italy
2Bologna University, Corso di Scienze Ambientali, Ravenna, Italy
3LEGOS, Toulouse, France
Abstract. This paper describes the
operational implementation of the data assimilation scheme for the
Mediterranean Forecasting System Pilot Project (MFSPP). The assimilation
scheme, System for Ocean Forecast and Analysis (SOFA), is a reduced order
Optimal Interpolation (OI) scheme. The order reduction is achieved by
projection of the state vector into vertical Empirical Orthogonal Functions (EOF).
The data assimilated are Sea Level Anomaly (SLA) and temperature profiles from
Expandable Bathy Termographs (XBT). The data collection, quality control,
assimilation and forecast procedures are all done in Near Real Time (NRT). The
OI is used intermittently with an assimilation cycle of one week so that an
analysis is produced once a week. The forecast is then done for ten days
following the analysis day. The root mean square (RMS) between the model
forecast and the analysis (the forecast RMS) is below 0.7°C in the surface
layers and below 0.2°C in the layers deeper than 200 m for all the ten
forecast days. The RMS between forecast and initial condition (persistence RMS)
is higher than forecast RMS after the first day. This means that the model
improves forecast with respect to persistence. The calculation of the misfit
between the forecast and the satellite data suggests that the model solution
represents well the main space and time variability of the SLA except for a
relatively short period of three – four weeks during the summer when the data
show a fast transition between the cyclonic winter and anti-cyclonic summer
regimes. This occurs in the surface layers that are not corrected by our
assimilation scheme hypothesis. On the basis of the forecast skill scores
analysis, conclusions are drawn about future improvements.
Key words. Oceanography; general
(marginal and semi-enclosed seas; numerical modeling; ocean prediction)
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