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Efficient estimation of time-mean states of ocean models using 4D-Var and implicit time-stepping
Institute for Marine and Atmospheric research Utrecht, Department of Physics and Astronomy, Utrecht University, Princetonplein 5, 3584 CC, Utrecht, The Netherlands
Abstract. We propose an efficient method for estimating a time-mean state of an ocean model subject to given observations using implicit time-stepping. The new method uses (i) an implicit implementation of the 4D-Var method to fit the model trajectory to the observations, and (ii) a pre-processor which applies a multi-channel singular spectrum analysis to enhance the signal-to-noise ratio of the observational data and to filter out the high frequency variability. This approach enables one to estimate the time-mean model state using larger time-steps than is possible with an explicit model. The performance of the method is presented for two test cases within a barotropic quasi-geostrophic nonlinear model of the wind-driven double-gyre ocean circulation. The method turns out to be accurate and, in comparison with the time-mean state computed with an explicit version of the model, relatively cheap in computational cost.
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Citation: Terwisscha van Scheltinga, A. D. and Dijkstra, H. A.: Efficient estimation of time-mean states of ocean models using 4D-Var and implicit time-stepping, Nonlin. Processes Geophys., 14, 777-788, 2007. Bibtex EndNote Reference Manager
