b-more-incomplete and b-more positive: Insights on A Robust Estimator of
Magnitude Distribution
Abstract
The $b$-value in earthquake magnitude-frequency distribution
quantifies the relative frequency of large versus small earthquakes.
Monitoring its evolution could provide fundamental insights into
temporal variations of stress on different fault patches. However,
genuine $b$-value changes are often difficult to distinguish from
artificial ones induced by temporal variations of the detection
threshold.
A highly innovative and effective solution to this issue has recently
been proposed by van der Elst (2021) through the b-positive method,
which is based on analyzing only the positive differences in magnitude
between successive earthquakes.
Here, we provide support to the robustness of the method, largely
unaffected by detection issues due to the properties of conditional
probability. However, we show that the b-positive method becomes less
efficient when earthquakes below the threshold are reported, leading to
the paradoxical behavior that it is more efficient when the catalog is
more incomplete. Thus, we propose the b-more-incomplete method, where
the b-method is applied only after artificially filtering the
instrumental catalog to be more incomplete. We also present other
modifications of the b-method, such as the b-more-positive method, and
demonstrate when these approaches can be efficient in managing
time-independent incompleteness present when the seismic network is
sparse.
We provide analytical and numerical results and apply the methods to
fore-mainshock sequences investigated by van der Elst (2021) for
validation. The results support the observed small changes in
$b$-value as genuine foreshock features.