The use of information of net primary productivity (NPP) from remote ocean color sensors is increasingly common in marine sciences. The resulting information has been used to explain variations in productivity at different spatio-temporal scales and in the presence of climate phenomena, such as the El Niño Southern Oscillation, and global warming. Satellite remote sensing data were analyzed in Bahía de La Paz (BLP), Mexico, to determine the spatio-temporal variation in NPP. In addition, in situ hydrographic data were obtained to characterize the water properties in the bay. The satellite data agree with in situ measurements, validating the satellite observations over this region. The NPP generally presented seasonal variation with maximum values in winter-spring and minimum values in summer–autumn. The variance explained by NPP from the measured variables was ranked as Chl-a < DEN < SST < PAR < WSC. The highest NPP values generally occurred when subtropical subsurface (SsStW) water was relatively shallow. Due to divergence and mixing processes, this water provided nutrients to the euphotic zone, and consequently an increase in NPP and changes in plankton biomass were observed. The annual trends of the variation in hydrographic data with respect to that of remote sensing data were similar; however, it is necessary to increase the number of data validation studies. The remote sensing and in situ measurements allowed for the main biophysical variables that modulate NPP in different time scales to be identified. The satellite-derived NPP data classifies the BLP as a high productivity zone with 432 g C m${}^{-2}$ year${}^{-1}$. The use of satellite NPP data is satisfactory and should be incorporated into marine primary productivity studies.