Extreme precipitation can have profound consequences for communities,; resulting in natural hazards such as rainfall-triggered landslides that; cause casualties and extensive property damage. A key challenge to; understanding and predicting rainfall-triggered landslides comes from; observational uncertainties in the depth and intensity of precipitation; preceding the event. Practitioners and researchers must select among a; wide range of precipitation products, often with little guidance. Here; we evaluate the degree of precipitation uncertainty across multiple; precipitation products for a large set of landslide-triggering storm; events and investigate the impact of these uncertainties on predicted; landslide probability using published intensity-duration thresholds. The; average intensity, peak intensity, duration, and NOAA-Atlas return; periods are compared ahead of 228 reported landslides across the; continental US and Canada. Precipitation data are taken from four; products that cover disparate measurement methods: near real-time and; post-processed satellite (IMERG), radar (MRMS), and gauge-based; (NLDAS-2). Landslide-triggering precipitation was found to vary widely; across precipitation products with the depth of individual storm events; diverging by as much as 296 mm with an average range of 51 mm. Peak; intensity measurements, which are typically influential in triggering; landslides, were also highly variable with an average range of 7.8 mm/hr; and as much as 57 mm/hr. The two products more reliant upon ground-based; observations (MRMS and NLDAS-2) performed better at identifying; landslides according to published intensity-duration storm thresholds,; but all products exhibited hit-ratios of greater than 0.56. A greater; proportion of landslides were predicted when including only; manually-verified landslide locations. We recommend practitioners; consider low-latency products like MRMS for investigating landslides,; given their near-real time data availability and good performance in; detecting landslides. Practitioners would be well-served considering; more than one product as a way to confirm intense storm signals and; minimize the influence of noise and false alarms.
