There are basically three ways that have been demonstrated to reliably measure seismic velocity changes in the crust of the Earth—repeating events, controlled sources, and ambient noise. Each has its complementary benefits. Repeating events and controlled sources provide measurements at discrete points in time and space with high signal‐to‐noise ratios. But to achieve a sufficient signal‐to‐noise ratio for ambient noise it has been necessary to average over long periods of time and/or numbers of station pairs. Often 30 days has been the average, but researchers have experimented with one‐day averages to capture short‐term velocity variations at the expense of reduced measurement precision. Coseismic and postseismic velocity changes have been established for many earthquakes. But measuring a clear preseismic signal has continued to elude us. One of the main reasons is due to insufficient temporal sampling for repeating events and controlled sources making the findings inconclusive as to the existence of a preseismic signal because of a lack of data. The benefit of ambient noise monitoring is that it provides continuous measurements in the preseismic period and offers hope to alleviate this problem. This paper improves the measurement precision for one‐day ambient noise monitoring by averaging over the three station components to construct the full nine‐element Green’s tensor. Doing so, I am able to measure a 95% confidence limit for an upper bound on preseismic velocity changes to be 0.0265%. I also compare my results constructing the Green’s function by the correlation of the coda of the correlation of ambient noise.

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