To assess infrasound detector performance, automated detections by the progressive multichannel correlation method (Cansi, 1995) and the adaptive F‐detector (AFD; Arrowsmith et al., 2009) are compared with signals identified by five independent analysts. Each detector was applied to a 4‐hr time sequence recorded by the Korean seismoacoustic array, CHNAR, composed of small (<100  m) and large (1000  m) aperture subarrays. Detector effectiveness was estimated for a selection of array elements and detection thresholds under low‐ and high‐noise conditions. Estimated receiver operating characteristic based on events identified by analysts evaluates the change in detection probability (Pd) and false‐alarm probability (Pf) for various detector parameters. This empirical study documents that the use of smaller aperture subarrays by both detectors increases Pd with smaller p‐values recommended for AFD to minimize Pf. Pd is impacted most by noise level, as shown by an increase in detections for average root mean square amplitudes from 1.2 to 3.2 MPa. Critical to this assessment is the identification of the source of the noise, constrained by signal characteristics, complementary seismic observations, and realistic atmospheric modeling. Based on signal characteristics (correlation value, phase velocity, and detection azimuth) and raytracing using global and local weather datasets, we conclude that during low‐noise conditions some detections from local distances (10–50 km) are affected by surface wind direction, and a second set is affected by tropospheric winds. This illustrates the role that surface and higher‐atmosphere winds play in array performance when assessing signals from regional infrasound sources in which local detections may be considered as noise or clutter.

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