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Shallow Slow Slip Events Identified Offshore the Osa Peninsula in Southern Costa Rica from GNSS Time Series

Authors: Cyril, Muller; Marino, Protti Quesada; Lujia, Feng; Emma, Hill; Mason, Perry;

Shallow Slow Slip Events Identified Offshore the Osa Peninsula in Southern Costa Rica from GNSS Time Series

Abstract

Using new continuous GNSS time series from the region, we identify 5 distinct shallow SSEs that occurred immediately offshore and beneath the Osa peninsula: an event detected by one site in 2013, and two events occurring in close succession in both 2018 and 2022 detected by multiple stations, indicating a preliminary recurrence interval of ~4-5 years. While SSEs have been observed to the north at Nicoya, this is their first documentation in southern Costa Rica. Modeled slip distributions of the 2018 and 2022 events indicate that they ruptured the same or overlapping patches of the plate interface, nearly at the trench, updip of historic earthquakes including the 1983 Mw 7.4 Osa event. Immediately offshore, the estimated cumulative slip from the 2018 and 2022 events is sufficient to close the slip deficit from tectonic loading over the recurrence interval, likely influencing the magnitude and spatial slip distribution of future large ruptures.

This is contains seismic catalog used in the article. The GNSS data are available with the following DOI: 10.5281/zenodo.7779495

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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