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Data assimilation in the ocean circulation model of high spatial resolution using the methods of parallel programming |
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| Authors: | M.?N.?Kaurkin author-information" > author-information__contact u-icon-before" > mailto:kaurkinmn@gmail.com" title=" kaurkinmn@gmail.com" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author,R.?A.?Ibrayev |
| Affiliation: | 1.Institute of Numerical Mathematics,Russian Academy of Sciences,Moscow,Russia;2.Shirshov Institute of Oceanology,Russian Academy of Sciences,Moscow,Russia;3.Hydrometeorological Research Center of the Russian Federation,Moscow,Russia;4.Moscow Institute of Physics and Technology (State University),Dolgoprudny, Moscow oblast,Russia;5.Dorodnitsyn Computing Center,Russian Academy of Sciences,Moscow,Russia |
| Abstract: | The parallel implementation of the method of multivariate optimum interpolation (MVOI) for the INMIO ocean circulation model with the horizontal resolution of 1/10° and 49 vertical levels is proposed to correct the model computations with the measurement data. The data assimilation in the high-resolution model with the high degree of scalability is tested. The results of numerical experiments on assimilation of data from ARGO drifters located in the North Atlantic are presented. The model output data were also compared with independent data on sea surface temperature obtained from Aqua (NASA) satellite observations. The skill of the model solution was qualitatively evaluated. It is demonstrated experimentally that data assimilation substantially (to 30%) improves the model output data and reduces the error in the operational 24-hour forecast. |
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