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

机译:Comparison and validation of global and regional ocean forecasting systems for the south China sea

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摘要

In this paper, the performance of two operational ocean forecasting systems, the global Mercator Ocean (MO) Operational System, developed and maintained by Mercator Ocean 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 science-based 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.
机译:本文介绍了两种海洋操作预报系统的性能,这两种方法分别是法国Mercator Ocean开发和维护的全球Mercator Ocean(MO)操作系统,以及国家海洋环境局(National Marine Environmental)的区域南海操作预报系统(SCSOFS)。已对中国的预报中心(NMEFC)进行了检查。两种系统都可以提供基于科学的温度,盐度,水位和海洋环流的临近预报/预报产品。根据2012年在南中国海获得的卫星观测资料和实地资料,对海洋环流,温度和盐分结构以及一些中尺度活动(如海锋,台风和中尺度涡流)进行了比较和验证。结果表明,MO在模拟海洋环流和海表温度(SST)方面表现更好,而SCSOFS在模拟温度和盐度结构方面表现更好。在中尺度活动方面,与以前的研究和卫星数据相比,在台风特宾期间,SSOFSFS在模拟海温上升和海温下降方面的表现优于MO。但是SCSOFS和MO的模型结果显示与卫星观测结果有些差异。总之,根据我们的比较和验证,已经为这两个预测系统提出了一些建议,以提高它们的预测性能。

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