Recognizing earthquakes as foreshocks in real time would provide a valuable forecasting capability. In a recent study, Gulia and Wiemer (2019) proposed a traffic‐light system that relies on abrupt changes in b‐values relative to background values. The approach utilizes high‐resolution earthquake catalogs to monitor localized regions around the largest events and distinguish foreshock sequences (reduced b‐values) from aftershock sequences (increased b‐values). The recent well‐recorded earthquake foreshock sequences in Ridgecrest, California, and Maria Antonia, Puerto Rico, provide an opportunity to test the procedure. For Ridgecrest, our b‐value time series indicates an elevated risk of a larger impending earthquake during the Mw 6.4 foreshock sequence and provides an ambiguous identification of the onset of the Mw 7.1 aftershock sequence. However, the exact result depends strongly on expert judgment. Monte Carlo sampling across a range of reasonable decisions most often results in ambiguous warning levels. In the case of the Puerto Rico sequence, we record significant drops in b‐value prior to and following the largest event (Mw 6.4) in the sequence. The b‐value has still not returned to background levels (12 February 2020). The Ridgecrest sequence roughly conforms to expectations; the Puerto Rico sequence will only do so if a larger event occurs in the future with an ensuing b‐value increase. Any real‐time implementation of this approach will require dense instrumentation, consistent (versioned) low completeness catalogs, well‐calibrated maps of regionalized background b‐values, systematic real‐time catalog production, and robust decision making about the event source volumes to analyze.

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