The International Monitoring System (IMS) infrasound network has been established to detect nuclear explosions and other signals of interest embedded in the station specific ambient noise. The ambient noise can be separated into coherent infrasound (e.g. real infrasonic signals) and incoherent noise (such as that caused by wind turbulence). Previous work statistically and systematically characterizing coherent infrasound recorded by the IMS. This paper expands on this analysis of the coherent ambient infrasound by including updated IMS datasets up to the end of 2020, for all 53 of the currently certified IMS infrasound stations using an updated configuration of the Progressive Multi-Channel Correlation (PMCC) method. This paper presents monthly station dependent reference curves for the back azimuth, apparent speed, and root-mean squared amplitude, which provide a means to determine the deviation from nominal monthly behaviour. In addition, a daily Ambient Noise Stationarity (ANS) factor based on deviations from the reference curves is determined for a quick reference to the data quality compared to the nominal situations. Newly presented histograms provide a higher resolution spectrum, including the observations of the microbarom peak, as well as additional peaks reflecting station dependent environmental noise. The aim of these reference curves is to identify periods of sub-optimal operation (e.g. non-operational sensor) or instances of strong abnormal signals of interest.