Abstract
Three- and four-dimensional variational assimilation (3DVAR and 4DVAR) systems have been developed for the Océan Parallélisé (OPA) ocean general circulation model of the Laboratoire d'Océanographie Dynamique et de Climatologie. They have been applied to a tropical Pacific version of OPA and cycled over the period 1993–98 using in situ temperature observations from the Global Temperature and Salinity Pilot Programme. The assimilation system is described in detail in Part I of this paper. In this paper, an evaluation of the physical properties of the analyses is undertaken. Experiments performed with a univariate optimal interpolation (OI) scheme give similar results to those obtained with the univariate 3DVAR and are thus not discussed in detail. For the 3DVAR and 4DVAR, it is shown that both the mean state and interannual variability of the thermal field are improved by the assimilation. The fit to the assimilated data in 4DVAR is also very good at timescales comparable to or shorter than the 30-day assimilation window (e.g., at the timescale of tropical instability waves), which demonstrates the effectiveness of the linearized ocean dynamics in carrying information through time. Comparisons with data that are not assimilated are also presented. The intensity of the North Equatorial Counter Current is increased (and improved) in both assimilation experiments. A large eastward bias in the surface currents appears in the eastern Pacific in the 3DVAR analyses, but not in those of 4DVAR. The large current bias is related to a spurious vertical circulation cell that develops along the equatorial strip in 3DVAR. In 4DVAR, the surface current variability is moderately improved. The salinity displays a drift in both experiments but is less accentuated in 4DVAR than in 3DVAR. The better performance of 4DVAR is attributed to multivariate aspects of the 4DVAR analysis coming from the use of the linearized ocean dynamics as a constraint. Even in 4DVAR, however, additional constraints seem necessary to provide better control of the analysis of currents and salinity when observations of those variables are not directly assimilated. Improvements to the analysis can be expected in the future with the inclusion of a multivariate background-error covariance matrix. This and other possible ways of improving the analysis system are discussed.
Corresponding author address: Dr. Jérôme Vialard, LODYC, Case 100, 4 Place Jussieu, 75252 Paris Cedex 05, France. Email: jv@lodyc.jussieu.fr