Improvements of ocean fronts forecasting in the South China Sea by using ensemble optimal interpolation assimilation

Abstract

Abstract Based on the operational ocean forecasting system in the South China Sea (SCS) runned by National Marine Environmental Forecasting Center (NMEFC), current Ensemble Optimal Assimilation (EnOI) system are updated by developing the dynamic coordination of multi-source data assimilation system, and has carried on the systematic evaluation. The diagnostic analysis of ocean fronts in the SCS is carried out using the daily average hindcast results in 2018, and the improvement effect of data assimilation on ocean mesoscale processes was evaluated. The statistical analysis results show that the occurrence frequency and diagnostic parameters of the ocean front after assimilation are closer to the observation. The comparison of the scores of the ocean front prediction skills before and after assimilation shows that the assimilated model has higher front prediction skills.