Assimilating altimetry data into a HYCOM model of the Pacific: Ensemble Optimal Interpolation versus Ensemble Kalman Filter

TitleAssimilating altimetry data into a HYCOM model of the Pacific: Ensemble Optimal Interpolation versus Ensemble Kalman Filter
Publication TypeJournal Article
Year of Publication2010
AuthorsWan, L, Bertino, L, Zhu, J
JournalJournal of Atmospheric and Oceanic Technology
Volume27
Number of Pages753-765
Date Published04/2010
PublisherAmerican Meteorological Society
e-ISSN1520-0426
Abstract

The ensemble Kalman filter (EnKF) has proven its efficiency in strongly nonlinear dynamical systems but is demanding in its computing power requirements, which are typically about the same as those of the four- dimensional variational data assimilation (4DVAR) systems presently used in several weather forecasting centers. A simplified version of EnKF, the so-called ensemble optimal interpolation (EnOI), requires only a small fraction of the computing cost of the EnKF, but makes the crude assumption of no dynamical evolution of the errors. How do both these two methods compare in realistic settings of a Pacific Ocean forecasting system where the computational cost is a primary concern? In this paper the two methods are used to as- similate real altimetry data via a Hybrid Coordinate Ocean Model of the Pacific. The results are validated against the independent Argo temperature and salinity profiles and show that the EnKF has the advantage in terms of both temperature and salinity and in all parts of the domain, although not with a very striking difference.

URLhttp://journals.ametsoc.org/toc/atot/27/4
DOI10.1175/2009JTECHO626.1
Refereed DesignationRefereed
Author Address

NERSC

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