High temporal precipitation variability, characterized by less frequent but larger-magnitude precipitation events, is increasing. However, how precipitation variability affects N2O emissions and the underlying mechanisms remain unclear, especially at multiple-year scales. We conducted a 3-year manipulative experiment in which the same long-term mean growing season precipitation total was repackaged into events of inversely varying magnitude and frequency to simulate four levels of precipitation variability (extra-extreme, extreme, medium, and normal) in a semiarid grassland. Cumulative N2O emissions was the smallest under the extra-extreme precipitation variability scenario (6 very large rainfall events), 26% less than emission under the other three treatments (10, 16, and 24 rainfall events) over the three growing seasons. However, this difference was almost entirely due to three sampling events in the third year. Plant community (biomass and biodiversity), soil abiotic properties (water, dissolved organic carbon and pH), soil microbial biomass (carbon, nitrogen and the ratio), and soil functional genes (archaeal and bacterial amoA, nirS, nirK, narG, and nosZ) explained 61% of the variation in N2O emissions in response to the precipitation variability. Structural equation modelling indicated that the precipitation variability had direct positive effects, and indirect negative effects via soil abiotic properties, on soil functional genes that ultimately had positive effects on N2O emissions. The reduction in N2O emission in the extra-extreme precipitation variability scenario in the third year was due to low levels of soil water content, soil pH, aboveground biomass, and microbial biomass carbon simultaneously. Our results suggest that at the multi-year timescale, semiarid grasslands may have negative feedbacks to future precipitation regimes with higher variability.