A large fraction of California's yearly precipitation comes from wintertime orographic clouds associated with atmospheric river (AR) events. The long-range transported dust and marine aerosols from Pacific Ocean may act as ice-nucleating particles (INPs) to affect cloud and precipitation properties over the region. The 2015 Atmospheric Radiation Measurement Cloud Aerosol Precipitation Experiment (ACAPEX), which intensively sampled clouds and aerosols during AR events, provides a unique opportunity to examine the INP-orographic cloud-AR interactions. In this study, we explore the effects of INPs from marine aerosols on the wintertime mixed-phase clouds during and after an AR event during the campaign and their relative importance compared with the dust impact. We carry out simulations at cloud-resolving scale (1 km) using WRF-Chem coupled with the spectral-bin microphysics (SBM) scheme. A recently developed immersion freezing ice nucleation parameterization for marine organics (McCluskey et al. 2018) is implemented into the model. By comparing against available airborne and ground-based observations, the new parameterization for marine INP improves the model performance particularly in simulating cloud phase, which is crucial to correctly simulating precipitation produced by mixed-phase clouds. It is found that marine INP enhances the formation of ice and snow, leading to a cloud regime shift from shallow warm cloud to mixed-phase and/or deep convective cloud. We also find that the responses of precipitation to marine INP are different during different cloud/AR periods, which can be attributed to the greatly altered thermodynamic condition and therefore cloud properties as the position and intensity of AR landfall evolve over time. The impact of marine INP is much more significant than dust INP over the studied AR period because dust is scarce. This study shows a potential large modification of orographic precipitation by marine aerosols from Pacific Ocean, suggesting a need to incorporate marine aerosols as INPs into current models.