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.
  • loading
  • Amante C, Eakins B W. ETOPO1 1 Arc-Minute Global Relief Model:Procedures, Data Sources and Analysis. Psychologist 2009. ETOPO1 1 Arc-Minute Global Relief Model:Procedures, Data Sources and Analysis. Psychologist, 16(3):20-25
    Argo. 2000. Argo float data and metadata from Global Data Assembly Centre (Argo GDAC). SEANOE. http://doi.org/10.17882/42182[2000-09-12/2015-9-20]
    Atlas R, Hoffman R N, Ardizzone J, et al. 2011. A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications. Bulletin of the American Meteorological Society, 92(2):157-174
    Bouttier F, Courtier P. 1999. Data assimilation concepts and methods March 1999. Bracknell:ECMWF, 59
    Cheng Xuhua, Qi Yiquan. 2010. Variations of eddy kinetic energy in the South China Sea. Journal of Oceanography, 66(1):85-94
    Cooper M, Haines K. 1996. Altimetric assimilation with water property conservation. Journal of Geophysical Research, 101(C1):1059-1077
    Cox M D. 1985. An eddy resolving numerical model of the ventilated thermocline. Journal of Physical Oceanography, 15(10):1312-1324
    Gill A E. 1982. Atmosphere-Ocean Dynamics. London:Academic Press, 345-346
    Good S A, Martin M J, Rayner N A. 2013. EN4:quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates. Journal of Geophysical Research:Oceans, 118(12):6704-6716
    Kalnay E, Kanamitsu M, Kistler R, et al. 1996. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 77(3):437-471
    Kurapov A L, Foley D, Strub P T, et al. 2011. Variational assimilation of satellite observations in a coastal ocean model off Oregon. Journal of Geophysical Research:Oceans, 116(C5):C05006
    Large W G, Pond S. 1982. Sensible and latent heat flux measurements over the ocean. Journal of Physical Oceanography, 12(5):464-482
    Mellor G L, Yamada T. 1982. Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4):851-875
    Moore A M, Arango H G, Broquet G, et al. 2011a. The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems:Part I-System overview and formulation. Progress in Oceanography, 91(1):34-49
    Moore A M, Arango H G, Broquet G, et al. 2011b. The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems:Part Ⅱ-Performance and application to the California Current System. Progress in Oceanography, 91(1):50-73
    Moore A M, Arango H G, Broquet G, et al. 2011c. The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems:Part Ⅲ-Observation impact and observation sensitivity in the California Current System. Progress in Oceanography, 91(1):74-94
    Nencioli F, Dong Changming, Dickey T, et al. 2010. A vector geometry-based eddy detection algorithm and its application to a high-resolution numerical model product and high-frequency radar surface velocities in the Southern California Bight. Journal of Atmospheric and Oceanic Technology, 27(3):564-579
    O'Dea E J, Arnold A K, Edwards K P, et al. 2012. An operational ocean forecast system incorporating NEMO and SST data assimilation for the tidally driven European North-West shelf. Journal of Operational Oceanography, 5(1):3-17
    Penven P, Echevin V, Pasapera J, et al. 2005. Average circulation, seasonal cycle, and mesoscale dynamics of the Peru Current System:A modeling approach. Journal of Geophysical Research:Atmospheres, 110(C10):C10021
    Powell B S, Arango H G, Moore A M, et al. 2008. 4DVAR data assimilation in the Intra-Americas Sea with the Regional Ocean Modeling System (ROMS). Ocean Modelling, 23(3-4):130-145
    Ratheesh S, Sharma R, Basu S. 2012. Projection-based assimilation of satellite-derived surface data in an Indian Ocean circulation model. Marine Geodesy, 35(2):175-187
    Reynolds R W, Smith T M, Liu Chunying, et al. 2007. Daily high-resolution-blended analyses for sea surface temperature. Journal of Climate, 20(22):5473-5496
    Roemmich D, Gilson J. 2009. The 2004-2008 mean and annual cycle of temperature, salinity, and steric height in the global ocean from the Argo program. Progress in Oceanography, 82(2):81-100
    Shchepetkin A F, McWilliams J C. 2005. The Regional Oceanic Modeling System (ROMS):A split-explicit, free-surface, topography-following coordinates oceanic model. Ocean Modelling, 9(4):347-404
    Shu Yeqiang, Zhu Jiang, Wang Dongxiao, et al. 2009. Performance of four sea surface temperature assimilation schemes in the South China Sea. Continental Shelf Research, 29(11-12):1489-1501
    Shu Yeqiang, Zhu Jiang, Wang Dongxiao, et al. 2011. Assimilating remote sensing and in situ observations into a coastal model of northern South China Sea using ensemble Kalman filter. Continental Shelf Research, 31(6):S24-S36
    White W B, Tai C K, Holland W R. 1990. Continuous assimilation of Geosat altimetric sea level observations into a numerical synoptic ocean model of the California Current. Journal of Geophysical Research:Oceans, 95(C3):3127-3148
    Willis J K, Roemmich D, Cornuelle B. 2004. Interannual variability in upper ocean heat content, temperature, and thermosteric expansion on global scales. Journal of Geophysical Research:Oceans, 109(C12):C12036
    Xiao Xianjun, Wang Dongxiao, Xu Jianjun. 2006. The assimilation experiment in the southwestern South China Sea in summer 2000. Chinese Science Bulletin, 51(S2):31-37
    Zhang Zhengguang, Wang Wei, Qiu Bo. 2014. Oceanic mass transport by mesoscale eddies. Science, 345(6194):322-324
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (1096) PDF downloads(390) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return