The burgeoning transmission and collection of real-time and climatological ocean data has focused attention on the requirement for efficient techniques of objective quality control and analysis, amenable to both real-time and delayed mode applications. This paper discusses the application of such techniques to analysis of Pacific ocean temperature, using statistics and maps drawn from 12 bimonthly analyses of the 150 m temperature during 1987--1988 as a means of evaluation. It is demonsrated that for observational data of varying quality, objective standardization is an integral element of the interpolation and mapping process and provides an effective method for screening large oceanic data sets. Prechecking and cross-validation are the center pieces of the quality control scheme, the efficacy of which depends both on the judicious choice of error tolerance levels and on the suitability of first-guess field and statistical prescriptions. The data rejection rate is near 5%, reflecting the conservative tolerances adopted for the study. Unreasonably low rates are obtained whenever inflated signal or noise levels are used. Persistent offsets in the first-guess field adversely affect the quality control measures and, in turn, can modify the analysis product. Using a parameter which relates to the system performance, it is shown that the analysis system is extracting close to maximum information from the available data. Degradation in system performance is chiefly linked to lack of effective quality control and poor statistical prescriptions. ¿1991 American Geophysical Union