Abstract
The investigation of the consequences of trying to blend tropical Pacific observations from the Tropical Atmosphere–Ocean (TAO) array into the dynamical framework of an intermediate coupled ocean–atmosphere model is continued. In a previous study it was found that the model dynamics, the prior estimates of uncertainty in the observations, and the estimates of the errors in the dynamical equations of the model could not be reconciled with data from the 1994–95 period. The error estimates and the data forced the rejection of the model physics as being unacceptably in error. In this work, data from two periods (1995–96 and 1997–98) were used when the tropical Pacific was in states very different from the previous study. The consequences of increasing the prior error estimates were explored in an effort to find out if it is possible at least to use the intermediate model physics to assist in mapping the observations into fields in a statistically consistent way.
It was found that such a result is possible for the new data periods, with larger prior error assumptions. However, examination of the behavior of the mapped fields indicates that they have no dynamical utility. The model dynamical residuals, that is, the size of the quantity that is left after evaluating all of the terms in each intermediate model equation, dominate the terms themselves. Evidently the intermediate model is not able to add insight into the processes that caused the tropical Pacific to behave as it was observed to, during these time intervals.
The inverse techniques described here together with the relatively dense TAO dataset have made it possible for the unambiguous rejection of the nonlinear intermediate model dynamical system. This is the first time that data have been able to provide such a clear-cut appraisal of simplified dynamics.
Corresponding author address: Dr. Andrew F. Bennett, College of Oceanic and Atmospheric Sciences, Oregon State University, 104 Ocean Admin. Bldg., Corvallis, OR 97331-5503.
Email: bennett@oce.orst.edu
