The INGV-CMCC seasonal prediction system: Improved ocean initial conditions

The development of the Istituto Nazionale di Geofisica e Vulcanologia (INGV)-Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC) Seasonal Prediction System (SPS) is documented. In this SPS the ocean initial-conditions estimation includes a reduced-order optimal interpolation procedure for th...

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Detalles Bibliográficos
Autores principales: Alessandri, A., Borrelli, A., Masina, S., Cherchi, A., Gualdi, S., Navarra, A., Di Pietro, P., Carril, A.F.
Formato: JOUR
Materias:
Boreal winters
Control simulation
Data assimilation
Ensemble forecasts
Extratropics
Global scale
Initial conditions
Optimal interpolation
Reduced order
Sea surface temperatures
Seasonal prediction
Subsurface profile
Surface climate
Temperature anomaly
Atmospheric temperature
Climatology
Data processing
Nickel compounds
Oceanography
Tropics
Forecasting
accuracy assessment
data assimilation
El Nino
ensemble forecasting
extratropical environment
global perspective
marine atmosphere
prediction
salinity
sea surface temperature
seasonal variation
temperature anomaly
tropical meteorology
weather forecasting
winter
Pacific Ocean
Pacific Ocean (Tropical)
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_00270644_v138_n7_p2930_Alessandri
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
Descripción
Sumario:The development of the Istituto Nazionale di Geofisica e Vulcanologia (INGV)-Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC) 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 as-similation of subsurface profiles during ocean initialization), it is shown that the improved ocean initialization increases the skill in the prediction of tropical Pacific sea surface temperatures of the system for boreal winter forecasts. Considering the forecast of the 1997/98 El Niño, the data assimilation in the ocean initial conditions leads to a considerable improvement in the representation of its onset and development. The results pre-sented in this paper indicate a better prediction of global-scale surface climate anomalies for the forecasts started in November, probably because of the improvement in the tropical Pacific. For boreal winter, sig-nificant increases in the capability of the system to discriminate above-normal and below-normal temperature anomalies are shown in both the tropics and extratropics. © 2010 American Meteorological Society.

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