Pseudo-spectral acceleration (PSA) is the most commonly used intensity measure in earthquake engineering, as it serves as a simple approximate predictor of structural response for many types of systems. Therefore, most ground motion models (GMMs, aka GMPEs) provide median and standard deviation PSA using a suite of input parameters characterizing the source, path and site effects. Unfortunately, PSA is a complex metric: the PSA for a single oscillator frequency depends on the Fourier amplitudes across a range of frequencies. The Fourier Amplitude Spectrum (FAS) is an appealing alternative because its simple linear superposition allows effects to be modeled as transfer functions. For this reason, most seismological models (e.g., the source spectrum) are developed for the FAS. Using FAS in conjunction with random vibration theory (RVT) allows GMM developers to superimpose seismological models directly, computing PSA only at the end of the process. The FAS-RVT-PSA approach was used for the development of GMMs for the Next Generation Attenuation Relationships for Central & Eastern North-America (NGA-East) project [PEER, 2018]. As part of the project, the team above developed a systematic processing algorithm for FAS that minimizes computational requirements and bias that results from the RVT approximation. We introduce the down-sampled orientation-independent FAS referred to as the effective amplitude spectrum (EAS) and recommended it as a new approach for characterizing the frequency content of ground motion records. This algorithm down-samples the EAS with a Konno and Ohmachi [1998] smoothing window with a width (b_w) of 1/30 and 100 frequency points per decade. This smoothing window was identified as having the least impact on a suite of RVT calibration properties. We applied this smoothing to the FAS delivered through the PEER ground motion portal for NGA-East and NGA-West2 databases.