The INGV–CMCC Seasonal Prediction System: Improved Ocean Initial Conditions

Abstract

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 assimilation 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 presented 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, significant increases in the capability of the system to discriminate above-normal and below-normal temperature anomalies are shown in both the tropics and extratropics.