The current investigation focuses on a fully compressible, axisymmetric jet operating at high subsonic conditions. The test bed of interest includes 10 kHz time-resolved particle image velocimetry coupled with simultaneously sampled near and far-field pressure measurements. The experimental results to be presented have been conducted in the Syracuse University anechoic chamber at the Skytop campus. This study focuses on identifying possible noise-producing events in the flow field by implementing reduced-order modeling techniques to extract "loud" modes in the flow. These concepts are coupled with wavelet-based diagnostic tracking techniques to examine the spatial and temporal nature of the "loud" modes. For this work, Mach 0.6 and Mach 0.85 will be the focus, in an effort to understand the noise-producing structures in a subsonic jet. The overall goal of this work is to effciently link near-field velocity with far-field acoustics to identify the interactions of the flow field responsible for far-field noise generation. Low-dimensional "loud" modes can then be implemented into closed-loop control algorithms in real-time for far-field noise suppression. This paper will focus on these "loud" modes, primarily linking the flow physics directly to the acoustics.