Comparison of data-based and modeled-based analysis of aircraft departure noise using noise monitor network recordings

Abstract

A comparison of data-based regression analysis and modeled-based analysis of aircraft departure noise variations using airport noise monitor network recordings is presented. Accurate modeling of aircraft noise is useful for the assessment of departure procedures and provides insight into the noise reduction potential of noise abatement flight procedures. In addition, many airports employ monitor networks that continuously record noise data produced by aircraft on departure, which can be used for assessing potential factors leading to variation in departure noise and for comparison to results from modeling methods. In this paper, departure noise variations of Boeing 737-800 aircraft are correlated to departure climb procedure factors using both data-based approaches incorporating recorded noise collected at the Seattle International Airport monitor network, and a method to model departure noise from on altitude, ground track, and ground speed from recorded operational surveillance data. Examples using both approaches indicate altitude and velocity result in the highest correlating factors for noise at the three noise monitor locations studied. Limitations and areas of needed improvement for the different noise modeling methods are highlighted.