Abstract The U.S. Geological Survey’s ShakeAlert earthquake early warning (EEW) system provides EEW alerts to the U.S. West Coast. ShakeAlert EEW alerts are distributed by alert delivery partners, such as the MyShake smartphone app, supported by earthquake warning in California and CalOES. MyShake has been delivering alerts since 2019 and currently serves over 2 million active EEW users. As alerts reach an ever-increasing number of users, there is a growing need to rapidly assess system performance and provide answers to commonly asked questions by EEW recipients about their EEW experience. MyShake harvests detailed alert delivery data from EEW recipients, including alert delivery latencies. We first present a retrospective analysis of MyShake delivery latencies across a large number of events. Latency is not a single number, but rather a distribution. We find the median of the 20th and 50th percentile delivery latencies across the events was 2.03 and 2.90 s, respectively. We find latencies have remained constant even with an increasing number of users while confirming they need to be considered for realistic warning time calculations. We leverage delivery latency data to develop a near-real-time, fully automated workflow that can produce data-driven warning time estimates for MyShake users. We develop user-friendly graphical products to present our results, including a joint map of median warning time contours and shaking distribution, and discuss how useful insights can be created for the general public and expert users alike. Our products can be rapidly disseminated via social media to satisfy the public's desire for information. Our results can also complement other efforts to assess ShakeAlert alerting performance, such as the Did-You-Feel-It supplemental EEW questionnaire. In addition, our workflow produces technical diagnostics that enable rapid detection of failures along the ShakeAlert–MyShake alerting pipeline.
Thompson et al. (Fri,) studied this question.