Ocean Climate Reanalysis of KIOST and its application to ENSO prediction system

A data assimilation system has been developed to apply to a fully coupled climate model, CM2.1, in the Korea Institute of Ocean Science and Technology (KIOST). The ocean observation data are assimilated into its ocean component model through the data assimilation system of the KIOST (DASK) while other component models are freely integrated. 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 El Niño and Southern Oscillation (ENSO), Pacific Decadal Oscillation and Indian Ocean Dipole. The heat content of the DASK shows a good correlation with real-world observations.

The ENSO is one of the most well-known and important climate phenomena. Although the ENSO appears in the tropical Pacific, it interacts with climate variability over the world, which impacts the human life by various ways. KIOST has been developed an ENSO prediction system by applying the DASK as its initial condition and wind bias correction to a fully coupled climate model, GFDL CM2.1. 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. To evaluate the ENSO prediction system, hindcast experiments have been conducted during 31 years from 1982 to 2012, 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 displayed in more detail in our study.