We continue exploring methodologies to improve regional explosion discrimination using the western U.S. as a natural laboratory. The western U.S. has abundant natural seismicity, historic nuclear explosion data, and widespread mine blasts, making it a good testing ground to study the performance of regional explosion discrimination techniques. We have assembled and measured a large set of these events to systematically explore how to best optimize discrimination performance. Nuclear explosions can be discriminated from a background of earthquakes using regional phase (Pn, Pg, Sn, Lg) amplitude measures such as high frequency P/S ratios. The discrimination performance is improved if the amplitudes can be corrected for source size and path length effects. We show good results are achieved using earthquakes alone to calibrate for these effects with the MDAC technique (Walter and Taylor, 2001). We show significant further improvement is then possible by combining multiple MDAC amplitude ratios using an optimized weighting technique such as Linear Discriminant Analysis (LDA). However this requires data or models for both earthquakes and explosions. In many areas of the world regional distance nuclear explosion data is lacking, but mine blast data is available. Mine explosions are often designed to fracture and/or move rock, giving them different frequency and amplitude behavior than contained chemical shots, which seismically look like nuclear tests. Here we explore discrimination performance differences between explosion types, the possible disparity in the optimization parameters that would be chosen if only chemical explosions were available and the corresponding effect of that disparity on nuclear explosion discrimination. Even after correcting for average path and site effects, regional phase ratios contain a large amount of scatter. This scatter appears to be due to variations in source properties such as depth, focal mechanism, stress drop, in the near source material properties (including emplacement conditions in the case of explosions) and in variations from the average path and site correction. Here we look at several kinds of averaging as a means to try and reduce variance in earthquake and explosion populations and better understand the factors going into a minimum variance level as a function of epicenter (see Anderson ee et al. this volume). We focus on the performance of P/S ratios over the frequency range from 1 to 16 Hz finding some improvements in discrimination as frequency increases. We also explore averaging and optimally combining P/S ratios in multiple frequency bands as a means to reduce variance. Similarly we explore the effects of azimuthally averaging both regional amplitudes and amplitude ratios over multiple stations to reduce variance. Finally we look at optimal performance as a function of magnitude and path length, as these put limits the availability of good high frequency discrimination measures
