The Arctic Ocean is an optically complex environment and presents unique challenges for ocean color satellite remote sensing. Phytoplankton pigment packaging, high concentrations of chromophoric dissolved organic matter (CDOM), and the frequent presence of subsurface chlorophyll a (Chl a) maxima (SCM), complicate satellite measurement of surface Chl a. However, the impact of likely errors in surface Chl a on satellite-based estimates of depth-integrated daily net primary production (NPP) have yet to be quantified. Here we use a large in situ Chl a and primary production database (ARCSS-PP) to calculate the magnitude of the error that likely results from both omission of SCM and overestimated phytoplankton biomass when satellite-based Chl a is used as input to an NPP algorithm. Results show that errors in pan-Arctic NPP, due to omission of the SCM, increase from 0.2% in January to 16% in July and are largest in the Beaufort and Chukchi Sea. Over an annual cycle, the error is approximately 8%. Errors in regional NPP resulting from overestimates of surface Chl a by Sea-viewing Wide Field-of-view Sensor can be larger, particularly when surface Chl a and NPP are low, but are partially offset by underestimates in NPP due to omission of NPP at the SCM. As a result, the combined effect of underestimates in NPP due to omission of the SCM and overestimates in NPP due to high satellite Chl a yields a total error in annual pan-Arctic, depth-integrated NPP of <1%. The reasons for this surprisingly low error are discussed.