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2002 LAPCOD Meeting
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A direct data assimilation method for Lagrangian observations
Kayo Ide(1), L. Kuznetsov(2) and C.K.R.T. Jones(2)
(1)University of California, Los Angeles, (2)University of North Carolina at Chapel Hill
kayo@atmos.ucla.edu(Abstract received 11/15/2002 for session D)
ABSTRACT
We present a new method for assimilating the Lagrangian observations directly into the model. The method is based on the extended Kalman filtering of the sequential approach. Most data assimilation systems in meteorology and oceanography use Eulerian models that compute the prognostic variables on a stationary grid. So far, in order to use Lagrangian observations given as trajectory data, they convert the data into Eulerian velocity by statistical interpolation. Doing so may lose precious time-integrated dynamical information hidden in the trajectories.
Our new method augments the trajectories to the prognostic variables of the model. This introduces the error correlation between the original model variables and the trajectories. Therefore, it provides a natural platform for direct assimilation of the Lagrangian observation in the framework of the extended Kalman filtering.
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2002 LAPCOD Meeting, Key Largo, Florida, December 12-16, 2000