While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of these physical relationships in the observational record across the contiguous United States. Here, we explore the joint relationships between a set of modes of natural climate variability (e.g., ocean variability indices and volcanic aerosols) as well as human-induced forcings (greenhouse gas emissions) and extreme daily precipitation based on in situ measurements from 1900 to present. These relationships are quantified using a spatial extreme value analysis, wherein aspects of the time-varying Generalized Extreme Value distribution change according to modes of climate variability. Furthermore, we are able to characterize the multivariate relationships at fine spatial scales; statistically significant relationships are identified using a robust resampling procedure that controls the rate of Type I errors. We find that there are important multivariate relationships between precipitation extremes and natural variability, and that these relationships vary both seasonally and spatially. Finally, we discuss how our improved quantification of these relationships can improve predictability of extremes and inform model development.