Integration of Arrival-Time Datasets for Consistent Quality Control: A Case Study of Amphibious Experiments along the Middle America Trench

Abstract

We have integrated waveform and arrival‐onset data collected in Costa Rica as part of the National Science Foundation (NSF)‐sponsored Costa Rica Seismogenic Zone Experiment (CRSEIZE) and along central Costa Rica and Nicaragua as part of the German SFB 574 program. The five arrays, composed of different sensor types (one‐ and three‐component land and ocean bottom seismometers and hydrophones), were archived using different software packages (Antelope and SEISAN) and were automatically and manually picked using various quality criteria resulting in a disparate set of pick weights. We evaluate pick quality using automated arrival detection and picking algorithm based on the wavelet transform and Akaike information criterion picker. The consistency of the arrival information over various scales provides a basis for assigning a quality to the analyst pick. Approximately 31% of P arrival times and 26% of S times have been classified as high‐quality picks (quality 0–1). An additional 21% of P times and 27% of S arrivals are good quality (quality 2–3). The revised quality picks are mapped directly into new pick weights for inversion studies. We explore the effect of new weighting and removal of poor data by relocating hypocenters through a minimum 1D velocity model and conducting double‐difference local earthquake tomography (LET). Analysis of the hypocenter relocation and seismic velocity tomography results suggest that using the improved quality determinations have a greater effect on improving sharpness in the velocity images than on the magnitude of hypocentral movement. Online Material: Figures of waveforms, event statistics, and tomography; and tables of station and event parameters, station qualities, velocity model, and hypocentral parameters.