ZHOU Chaojie, DING Xiaohua, ZHANG Jie, YANG Jungang, MA Qiang. An evaluation of sea surface height assimilation using along-track and gridded products based on the Regional Ocean Modeling System (ROMS) and the four-dimensional variational data assimilation[J]. Acta Oceanologica Sinica, 2018, 37(9): 50-58. doi: 10.1007/s13131-018-1225-1
Citation: ZHOU Chaojie, DING Xiaohua, ZHANG Jie, YANG Jungang, MA Qiang. An evaluation of sea surface height assimilation using along-track and gridded products based on the Regional Ocean Modeling System (ROMS) and the four-dimensional variational data assimilation[J]. Acta Oceanologica Sinica, 2018, 37(9): 50-58. doi: 10.1007/s13131-018-1225-1

An evaluation of sea surface height assimilation using along-track and gridded products based on the Regional Ocean Modeling System (ROMS) and the four-dimensional variational data assimilation

doi: 10.1007/s13131-018-1225-1
  • Received Date: 2018-03-08
  • Remote sensing products are significant in the data assimilation of an ocean model. Considering the resolution and space coverage of different remote sensing data, two types of sea surface height (SSH) product are employed in the assimilation, including the gridded products from AVISO and the original along-track observations used in the generation. To explore their impact on the assimilation results, an experiment focus on the South China Sea (SCS) is conducted based on the Regional Ocean Modeling System (ROMS) and the four-dimensional variational data assimilation (4DVAR) technology. The comparison with EN4 data set and Argo profile indicates that, the along-track SSH assimilation result presents to be more accurate than the gridded SSH assimilation, because some noises may have been introduced in the merging process. Moreover, the mesoscale eddy detection capability of the assimilation results is analyzed by a vector geometry-based algorithm. It is verified that, the assimilation of the gridded SSH shows superiority in describing the eddy's characteristics, since the complete structure of the ocean surface has been reconstructed by the original data merging.
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