In this paper, a theoretical and numerical as-sessment of the validity of Eulerian truncation in stochasticrnmodeling is presented. Specifically, we analyze and compare theoretically various existing Eulerian-based first-order tech-niques with and without invoking Eulerian truncation and quantify the terms truncated and retained in the stochastic per-turbation equations using high resolution Monte Carlo simula-tions. We also analyze and compare numerically various exist-ing Eulerian-based first-order techniques and Monte Carlo simulation. The obtained results have demonstrated theoreti-cally and numerically that existing Eulerian-based stochasticrnperturbation techniques are equivalent. The terms truncated are indeed one order higher than those retained. Therefore,we conclude that Eulerian truncation is mathematically con-sistent and asymptotic.