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Dynamical systems perspective of observing system design
Kayo Ide, Christopher K.R.T. Jones, Hayder Salman
University of California, Los Angeles
kayo@atmos.ucla.edu(Abstract received 05/01/2005 for session D)
ABSTRACT
We present the Lagrangian data assimilation (LaDA) method due to Ide and collaborators (Ide et al 2002, Kuznetsov et al 2003). We invoke an ensemble Kalman filter in order to estimate and forecast the (ocean) state using the shallow-water model (Salman et al, 2005). Based on the augmented state representation, the LaDA eliminates the need for any conventionally used approximation in assimilating the Lagrangian information. This augmentation also allows us to use dynamical systems theory for the design of a comprehensive observing system. We show how deploying drifters in the flow near the (Lagrangian) saddle point enhances the information content of the (Eulerian) flow dynamics extracted from the Lagrangian data using LaDA.
Ide, K., L. Kuznetsov and C.K.R.T. Jones, 2002: Lagrangian data assimilation for point-vortex system. J. Turbulence, 3, 053.
Kuznetsov, L., K. Ide and C.K.R.T. Jones, 2003: A method for assimilation of Lagrangian data. Mon. Wea. Rev., 131(10), 2247-2260.
Salman, H., L. Kuznetsov, C.K.R.T. Jones and K. Ide, 2005: A method for assimilating Lagrangian data into a shallow-water equation ocean model, Mon. Wea. Rev., Sub judice.
Poje, A.C., M. Toner, A.D. Kirwan Jr. and C.K.R.T. Jones, 2002: Drifter launch strategies based on dynamic Lagrangian templates, Journal of Physical Oceanography, 32, 1855-1869.
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2005 LAPCOD Meeting, Lerici, Italy, June 13-17, 2005