Subfootprint variability (SFV), variability within the footprint of a satellite measurement, is a source of error associated with the validation process, especially for a satellite measurement with a large footprint such as those measuring sea surface salinity (SSS). This type of error has not been adequately quantified in the past. In this study, I have examined SFV using in situ ocean data from the SPURS-1 (Salinity Processes in the Upper ocean Regional Studies-1) and SPURS-2 field campaigns in the subtropical North Atlantic and eastern tropical North Pacific respectively. I computed SFV from these data over two one-year periods of intense sampling. The results show that SFV is highly seasonal. I have computed SFV errors in several different forms, a median value of the weekly snapshot error, a total snapshot error, an absolute error of the Aquarius and SMAP (Soil Moisture Active Passive) measurement, a part of that error associated with SFV and a bias due to the skewness of the distribution of SSS. These results are characteristic only of the particular regions studied. However, comparison of the results with high resolution models, and in situ data from moorings gives the possibility of getting global estimates of SFV from these other more common sources of SSS data.