AGU Advances (Sep 2021)

Robust Earthquake Early Warning at a Fraction of the Cost: ASTUTI Costa Rica

  • Benjamin A. Brooks,
  • Marino Protti,
  • Todd Ericksen,
  • Julian Bunn,
  • Floribeth Vega,
  • Elizabeth S. Cochran,
  • Chris Duncan,
  • Jon Avery,
  • Sarah E. Minson,
  • Esteban Chaves,
  • Juan Carlos Baez,
  • James Foster,
  • Craig L. Glennie

DOI
https://doi.org/10.1029/2021AV000407
Journal volume & issue
Vol. 2, no. 3
pp. n/a – n/a

Abstract

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Abstract We show that a fixed smartphone network can provide robust Earthquake Early Warning for at least two orders of magnitude less cost than scientific‐grade networks. Our software and cloud‐based data architecture that we have constructed for the Alerta Sismica Temprana Utilizando Teléfonos Inteligentes (ASTUTI; Earthquake Early Warning Utilizing Smartphones) network in Costa Rica is easily scaled and exported. Implementation comprises provisioning and installing modern smartphones in judicious locations. Stand‐up time for regionally operational networks can be on the order of days. We evaluated a non‐parametric ground‐motion detection and alerting strategy that would alert the entire Costa Rican population of any event with a ground motion detection threshold of 0.55–0.65 %g at four neighboring stations. During a 6‐month evaluation period ASTUTI detected and alerted on five of 13 earthquakes with Mw 4.8–5.3 that caused felt Modified Mercalli Intensity shaking levels of 4.3–6. The system did not produce any false alerts and the undetected events did not produce wide‐spread or significant felt shaking. System latencies were less than or similar to scientific‐grade latencies. Alerts for all five detected events would have reached the capital city, San Jose, before strong S‐wave shaking. This would have afforded time for Drop Cover Hold On actions by most residents. Two of the five alerts were triggered by P‐waves suggesting that smartphone‐based networks could approach the fastest theoretical EEW performance, especially with future expected improvements in smartphone sensors and processing algorithms.

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