Received: 23 May 2019 – Discussion started: 20 Jun 2019
Abstract. An original hybrid data assimilation scheme recently developed is presented and tested. The scheme is based on the application of the theory of diffusion random processes. It is applied here in conjunction with the Hybrid-Coordinate Ocean Model (HYCOM) to assimilate altimetry data from the Archiving, Validating and Interpolating Satellite Oceanography Data (AVISO) in the Atlantic. Several numerical experiments were conducted and their results were analyzed. It is shown that the method is able to assimilate data and to produce analyses closer to observations. It also conserves the model balance. This method allows calculating the confidence range of the analyses by estimating their errors The presented method is compared with the Ensemble Optimal Interpolation scheme (EnOI) and it is shown that it has several advantages, in particular, it provides a better forecast and requires less computational cost.
How to cite. Belyaev, K., Kuleshov, A., Smirnov, I., and Tanajura, C. A. S.: A hybrid data assimilation method and its comparison with an Ensemble Optimal Interpolation scheme in conjunction with the numerical ocean model using altimetry data, Ocean Sci. Discuss. [preprint], https://doi.org/10.5194/os-2019-56, 2019.
The authors data assimilation method recently developed is presented and tested together with the ocean circulation model. It is shown that the method is able to assimilate data. It produces analyses closer to observations and also has several advantages in comparison with the traditional data assimilation schemes, for instance, with the Ensemble Optimal Interpolation scheme (EnOI). It provides a better forecast and requires less computational consumptions.
The authors data assimilation method recently developed is presented and tested together with...