Symposium on Observations, Data Assimilation, and Probabilistic Prediction

P1.2

Multivariate assimilation of SST, sea level and currents for tropical Pacific Ocean

Eric Hackert, University of Maryland, College Park, MD; and J. Ballabrera and A. Busalacchi

Over the past number of years great strides have been made in the field of ocean data assimilation. New data types such as those provided by the extended altimetry missions (ie. TOPEX/Poseidon) now provide ocean modelers with enough high-quality data to allow data assimilation on basin-wide scales. In the current study the Singular Evolutive Extended Kalman (SEEK) filter approach, first described by Pham et al. (1998), is used to assimilate various data types into a general circulation model of the tropical Pacific Ocean. The ocean model is a high-resolution, reduced gravity, primitive equation, sigma-coordinate model with variable depth oceanic mixed layer (Gent and Cane, 1989). The data include sea surface height (SSH) from the TOPEX/Poseidon altimeter, sea surface temperature (SST) analyses from satellite and in situ observations, and surface currents derived from SSH and wind stress fields by combining the geostrophic approximation and Ekman dynamics (Lagerloef et al., 1999).

The impact of each data type is studied separately and together using a multivariate approach. Also shown is the impact of the formulation of the reduced basis defining the assimilation filter. For example, the SST results are improved when the mixed layer is decoupled from the assimilation procedure while assimilating only sea level information.

Poster Session 1, Effective Assimilation of the Vast Observational Datasets Becoming Available
Monday, 14 January 2002, 3:30 PM-5:30 PM

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