The questions concerning how much precipitation is extreme and how extreme precipitation responds to warming are important to improving climate resiliency and achieving sustainable development of typical loess hills and gullies in China. The spatial-temporal variation of extreme precipitation is investigated on the Loess Plateau in northern Shaanxi province from 1970 to 2017. To understand the influence of El Ni?o on extreme climate variation, this study analyzes whether extreme precipitation events are linked to the SST in nine different sea regions (NINO 1+2, NINO 3, NINO 3.4, NINO 4, NINO W, NINO A, NINO B, NINO C, NINO Z). The result showed that from 1970 to 2017, an obvious warming-wetting trend occurred on the Loess Plateau in northern Shaanxi. The warming process can be divided into three periods: a rapid increase period (1970-1998), followed by a short hiatus (1999-2012), and finally, a warming rebound period (2013-2017). In addition, precipitation was dominated by interannual oscillation. However, after 2004, precipitation increased in northern Shaanxi, which was associated with semi-arid boundaries moving to the northwest. The result also showed that 16 extreme climate indices were quantified as precipitation changes that were more intense on the Loess Plateau in northern Shaanxi. Spatially, regarding the number of precipitation days when daily precipitation was above 1, 5, 10, or 20 mm, there was a clear increasing trend from south to north. Even so, the region showed a consistent and significant change in the number of decreasing rainy days and increasing SDII. Finally, in the past 48 years, the influence of SST on the central and western equatorial Pacific, for the decadal variation of extreme precipitation, was more obvious than that in the eastern equatorial Pacific. Additionally, while the influence of SST on the northern side of the equatorial Pacific was more obvious than that on the southern side, the effect by the SST periodic variation on the 14~16a time scale was more significant than that on the 4~8a time scale. It is worth mentioning that changes in nearly all indices had a strong correlation to NINO W, especially the intensity indices (Rx1day, Rx5day, and SDII) and the indices defined on a percentile-based threshold (R95, R99, R95P, and P99P). The anomaly of SST in the Nino W region served as a typical signal that there was an increase in occurrence of extreme precipitation in northern Shaanxi.