Data Assimilation Method for the Ocean Circulation Model NEMO and Its Application for the Calculation of Ocean Characteristics in the Arctic Zone of Russia

摘要

Based on the GKF (Generalized Kalman Filter) data assimilation method, which we have proposed earlier, jointly with the NEMO (Nucleus for European Modelling of the Ocean) model of ocean circulation, the spatial-temporal variability of several model characteristics, in particular, the ocean level field and the water temperature field in the Arctic Zone of Russia, is studied in numerical experiments. The ocean level data taken from the AVISO (Archiving, Validating and Interpolation Satellite Observation) archive are assimilated into the NEMO model. The ocean level and temperature are calculated both with and without data assimilation (the control run). The results of calculations are analyzed and it is shown that the main spatial variability of the characteristics after data assimilation is in a good agreement with the localization of currents in the Northern Atlantics and the Arctic Zone of Russia. The authors have performed the installation and adaptation of the NEMO software package on the K-60 high-performance computer (HPC) in the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences (Moscow, Russia). The qualitative estimate of this variability is presented and it is shown at what time interval the dependence of the calculated characteristics on the observation data manifests itself.