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Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/5852

Authors: Alessandri, A.*
Borrelli, A.*
Masina, S.*
Cherchi, A.*
Gualdi, S.*
Navarra, A.*
Di Pietro, P.*
Title: The INGV-CMCC Seasonal Prediction System: improved ocean initial conditions
Title of journal: Monthly Weather Review
Series/Report no.: /138 (2010)
Publisher: American Meteorological Society
Issue Date: 2010
Keywords: ocean modelling
global climate models
seasonal forecast
coupled models
Abstract: The development of the INGV (Istituto Nazionale di Geofisica e Vulcanologia)-CMCC (Centro Euro-Mediterraneo per i Cambiamenti Climatici) Seasonal Prediction System (SPS) is documented. In this SPS the ocean initial conditions estimation includes a Reduced Order Optimal Interpolation procedure for the assimilation of temperature and salinity profiles at the global scale. Nine member ensemble forecasts have been produced for the period 1991-2003 for two starting dates per year in order to assess the impact of the subsurface assimilation in the ocean for initialization. Comparing the results with control simulations (i.e.: without assimilation of subsurface profiles during ocean initialization), we showed that the improved ocean initialization increases the skill in the prediction of tropical Pacific SSTs in our system for boreal winter forecasts. Considering the forecast of the El Ni˜no 1997-1998, the data assimilation in the ocean initial conditions leads to a considerable improvement in the representation of its onset and development. Our results indicate a better prediction of global scale surface climate anomalies for the forecasts started in November, probably due to the improvement in the tropical Pacific. For boreal winter, in both tropics and extra tropics, we show significant increases in the capability of the system to discriminate above normal and below normal temperature anomalies.
Appears in Collections:03.01.03. Global climate models
Papers Published / Papers in press

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