The improvements to the regional South China Sea Operational Oceanography Forecasting System

Abstract

Abstract. South China Sea Operational Oceanography Forecasting System (SCSOFS) had been built up and operated in National Marine Environmental Forecasting Center of China to provide daily updated hydrodynamic forecasting in SCS for the future 5 days since 2013. This paper presents comprehensive updates had been conducted to the configurations of the physical model and data assimilation scheme in order to improve SCSOFS forecasting skills in recent years. It highlights three of the most sensitive updates, sea surface atmospheric forcing method, tracers advection discrete scheme, and modification of data assimilation scheme. Scientific inter-comparison and accuracy assessment among five versions during the whole upgrading processes are performed by employing Global Ocean Data Assimilation Experiment OceanView Inter-comparison and Validation Task Team Class4 metrics. The results indicate that remarkable improvements have been achieved in SCSOFSv2 with respect to the original version SCSOFSv1. Domain averaged monthly mean root mean square errors decrease from 1.21 °C to 0.52 °C for sea surface temperature, from 21.6 cm to 8.5 cm for sea level anomaly, respectively.

Inversion of Initial Field Based on a Temperature Transport Adjoint

“…Peng et al [28] evaluated the role of a 4D-Var algorithm based on POM (Princeton Ocean Model) and its adjoint for storm surge simulation, by adjusting both the initial conditions and the upper boundary conditions, the storm surge simulation was improved. South China Sea Operational Oceanography Forecasting System (SCSOFS) was built to provide daily updated hydrodynamic forecasting in SCS for the future 5 days since 2013, and it also had been improved through comprehensive updates of the configurations of the physical model and data assimilation scheme [29].…”