+1 Recommend
1 collections
      • Record: found
      • Abstract: found
      • Article: found

      A New Multigrid 3D-VAR Optimization Method for Bottom Friction Using HF Radar Current Observation

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          This paper proposes a new method for data assimilation of the surface radial current observed by High Frequency ground wave radar and optimization of the bottom friction coefficient. In this method, the shallow water wave equation is introduced into the cost function of the multigrid three-dimensional variation data assimilation method as the weak constraint term, the surface current and the bottom friction coefficient are defined as the analytical variables, and the high spatiotemporal resolution surface radial flow observed by the high-frequency ground wave radar is used to optimize the surface current and bottom friction coefficient. This method can effectively consider the spatiotemporal correlation of radar data and extract multiscale information from surface radial flow data from long waves to short waves. Introducing the shallow water wave equation into the cost function as a weak constraint condition can adjust both the momentum and mass fields simultaneously to obtain more reasonable analysis information. The optimized bottom friction coefficient is introduced into the regional ocean numerical model to carry out numerical experiments. The test results show that the bottom friction coefficient obtained by this method can effectively improve the accuracy of the numerical simulation of sea surface height in the offshore area and reduce the simulation error.

          Related collections

          Author and article information

          Journal of Ocean University of China
          Science Press and Springer (China )
          12 November 2019
          01 December 2019
          : 18
          : 6
          : 1247-1255
          1Key Laboratory of Marine Environmental Information Technology, National Marine Data and Information Service, Ministry of Natural Resources, Tianjin 300171, China
          2School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
          3National Ocean Technology Center, Ministry of Natural Resources, Tianjin 300112, China
          4Marine Environment Institute, Tianjin 300200, China
          Author notes
          *Corresponding author: ZHANG Xiaoshuang
          Copyright © Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2019.

          The copyright to this article, including any graphic elements therein (e.g. illustrations, charts, moving images), is hereby assigned for good and valuable consideration to the editorial office of Journal of Ocean University of China, Science Press and Springer effective if and when the article is accepted for publication and to the extent assignable if assignability is restricted for by applicable law or regulations (e.g. for U.S. government or crown employees).

          Self URI (journal-page):


          Comment on this article