Abstract

El Nino–Southern Oscillation (ENSO) is one of the most influential fluctuations of the coupled atmosphere-ocean climate system in the Seasonal-to-Interannual (SI) time scale for global and local communities. Ocean data assimilation systems are generally adopted for monitoring ENSO because the variation of the heat content in the ocean interior of the equatorial Pacific is considered a good precursor of El Ninos, and essential for understanding the ENSO process. They are also utilized for the initialization of Coupled Atmosphere-OceanGeneral Circulation Models (CGCMs), along with atmosphere data assimilation systems in the SI forecasting systems of various operational centers. In this paper, we discuss the capacity of current operational ocean data assimilation systems adopted for ENSO monitoring and SI forecasting based on studies using the system of the Japan Meteorological Agency (JMA). It then demonstrates the benefits of assimilating ocean observation data through those systems in SI forecasts using the JMA seasonal and ENSO forecasting system. It also introduces the recent effort of JMA/Meteorological Research Institute (MRI) to resolve “coupled shock, which is one of the most crucial issues concerning the initialization with uncoupled ocean and atmosphere data assimilation systems in SI forecasting. This chapter is organized as follows. Section 2 summarizes the process of developing ocean data assimilation systems for up-to-date ENSOmonitoring and SI forecasting. In particular, it describes efforts to improve the Temperature-Salinity (T-S) balance in the assimilation results over the past decade. We then introduce the ocean data assimilation system used in the JMA seasonal and ENSO forecasting system as a state-of-the-art system in Section 3. Section 4 demonstrates the importance of assimilating ocean observation data through the ocean data assimilation system for ENSO and seasonal forecasting. Section 5 introduces the recent effort to resolve the coupled shock at JMA/MRI. This chapter is summarized in Section 6. Assimilating Ocean Observation Data for ENSO Monitoring and Forecasting

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