  Explosions near ground generate multiple geophysical waveforms in the
radiation-dominated range of their signature fields. Multi-phenomological
explosion monitoring (MultiPEM) at these ranges requires the predictive
capability to forecast trigger rates of digital detectors that process such
waveform data, and thereby accurately anticipate the probability that
hypothetical explosions can be identified in operations. To confront this
challenge, we derive and compare the predicted and observed performance of
three digital detectors that process radio, acoustic and seismic waveform data
that record a small, aboveground explosion. We measure this comparison with the
peak range in magnitude (magnitude discrepancy) over which different
performance curves report the same probability of detection, within an interval
of moderate detection probability, and thereby quantify solutions to three
topical monitoring questions. In particular, our solutions (1) demonstrate how
empirically parameterized detectors that operate in a variable noisy
environments provide fair-to-very good forecasting capability to detect small
explosions, (2) show that the observed performance of a particular waveform
detector can better forecast performance curves constructed from different
observations, when compared to theoretical performance curves, and (3) provide
an upper bound on detection uncertainty, in terms of a physical source
attribute (magnitude)
