Climate initialization applying ocean data assimilation for a ENSO prediction system

Abstract

El Ni&ntilde o and Southern Oscillation is one of the most well-known and important climatephenomena. Although the ENSO appears in the tropical Pacific, it interacts with climatevariability over the world, which impacts the human life by various ways. KIOST has beendeveloped an ENSO prediction system by applying the ocean data assimilation and wind biascorrection to a fully coupled climate model, GFDL CM2.1. The ocean observation data areassimilated into its ocean component model through the data assimilation system of theKIOST (DASK) while other component models are freely integrated. Even though atmospheric observation variables are not assimilated, the wind bias of the DASK has been corrected through applying a simple wind bias correction when calculating the air-sea fluxes.We evaluated the variability of the ocean climate in the climate reanalysis by the DASK from 1947 to 2012. The DASK represents global temperature and salinity well, not only at the surface but also at intermediate depths in the ocean. The DASK’s ocean climate variability also matches well with observations of the ENSO, Pacific Decadal Oscillation and Indian Ocean Dipole. The heat content of the DASK shows a good correlation with real-world observations. In this study, we use the reanalysis data from the DASK as an initial condition of our ENSO prediction system. To evaluate the ENSO prediction system, hindcast experiments have been conducted during 30 years from 1982 to 2011, which suggests that the ocean initialization and wind correction significantly improve the ENSO prediction skill. The sensitivity of the ENSO prediction skills to the ocean initialization and wind bias correction will be discussed in more detail in our study.