Comparison and validation of global and regional ocean forecasting systems for the South China Sea

Abstract

Abstract. In this paper, the performance of two operational ocean forecasting systems, the global Mercator Océan (MO) Operational System, developed and maintained by Mercator Océan in France, and the regional South China Sea Operational Forecasting System (SCSOFS), by the National Marine Environmental Forecasting Center (NMEFC) in China, have been examined. Both systems can provide sciencebased nowcast/forecast products of temperature, salinity, water level, and ocean circulations. Comparison and validation of the ocean circulations, the structures of temperature and salinity, and some mesoscale activities, such as ocean fronts, typhoons, and mesoscale eddies, are conducted based on observed satellite and in situ data obtained in 2012 in the South China Sea. The results showed that MO performs better in simulating the ocean circulations and sea surface temperature (SST), and SCSOFS performs better in simulating the structures of temperature and salinity. For the mesoscale activities, the performance of SCSOFS is better than MO in simulating SST fronts and SST decrease during Typhoon Tembin compared with the previous studies and satellite data; but model results from both of SCSOFS and MO show some differences from satellite observations. In conclusion, some recommendations have been proposed for both forecast systems to improve their forecasting performance in the near future based on our comparison and validation.

The improvements to the regional South China Sea Operational Oceanography Forecasting System (SCSOFSv1)

“…As mentioned in the literature of Zhu et al (2016), the regional SCS Operational Oceanography 85Forecasting System (SCSOFS, here after named it as SCSOFSv1) has been developed and routinely operated in real time since the beginning of 2013. It has continued to be upgraded by modifying model settings in many aspects, such as mesh distributions, surface atmospheric field forcing, open boundary inputs, and so on, and improving data assimilation scheme according to the results of comparing and validating from Zhu et al (2016), in order to provide better services. The primary purpose of this paper 90 is to introducing updates applied to SCSOFS, but only show the highest impact on the system.…”

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

“…As mentioned in the literature of Zhu et al (2016), the regional SCS Operational Oceanography Forecasting System (SCSOFS, here after named it as SCSOFSv1) has been developed and routinely 85 operated in real time since the beginning of 2013. It has continued to be upgraded by modifying model settings in many aspects, such as mesh distributions, surface atmospheric field forcing, open boundary inputs, and so on, and improving data assimilation scheme according to the results of comparing and validating from Zhu et al (2016), in order to provide better services. The primary purpose of this paper is to introducing updates applied to SCSOFS, but only show the highest impact on the system.…”

“…As mentioned as Zhu et al (2016), the original SCSOFSv1 had employed the multivariate Ensemble Optimal Interpolation (EnOI, Evensen, 2003;Oke et al, 2008) four different variables to one array, respectively.…”

“…EnOI data assimilation scheme in recent couple years based on the recommendations ofZhu et al (2016), such as land-water grid mask redistribution, data sources for bathymetry, initial condition, sea surface forcing and open boundary condition changing to higher horizontal and temporal resolution, moving the eastern lateral boundary westward, increasing vertical layers of model, and so on.…”

Detection of Fronts as a Metric for Numerical Model Accuracy

“…For example, Ziegeler et al (2012) uses a method that determines the displacement of features relative to a mapped product. Zhu et al (2016) looks at distribution of SST fronts but does not define a quantitative metric for evaluation of their accuracy. However, these methods and metrics are not appropriate for application to altimetric measurements.…”