During a prolonged clearing with paricularly dry atmospheric conditions over the Southern California Bight, four NOAA 6 satellite overpasses at 12-hour intervals were recorded while a research vessel measured ocean temperatures within the field of view of the satellite. This data set is used to evaluate two versions of an equation for estimating sea surface temperature from satellite data and for examining short-term changes in surface temperature caused by diurnal variation and surface layer movement. Surface temperatures calculated from data taken during a daytime overpass, using two slightly differing versions of a multiwindow atmospheric correction equation, match the ocean temperatures within the expected range of scatter: ¿0.6¿C. One version has a mean daytime bias of +0.5¿C, the other has -0.4¿C, and thus the two versions differ by 0.9¿C. The satellite-derived sea surface temperatures show a diurnal variation in the range of 0.25¿ to 1.0¿C. Hence the basis of calculated satellite temperatures for the nighttime overpasses differ from those for the daytime; the bias in one version is +1.2¿C and in the other is +0.4¿C. It is suggested that these biases are caused by inherent problems in the selection and matching of satellite and ocean data sets used to determine the equation coefficients as well as poorly understood diurnal variation of the surface temperature as measured by satellite. Advection, evidenced by an image-to-image shift of thermal gradients over 12- and 24-hour periods can produce local temperature changes that add to the problem. Noise in one of the satellite data channels, another part of the problem, is shown to be amenable to filtering techniques. Diurnal differences in satellite-observed surface temperatures are found to vary regionally; larger variations is found in waters that are turbid and have a shallow thermocline. Near surface in situ temperature measurements suggest a diurnal layer variation of 0.2¿C, much less than the variations observed by satellite. An estimation of diurnal sea surface temperature variation based on heat budget calculations supports the in situ observations.