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One of the major sources of uncertainty in predictions of wind farm noise(WFN) reflect parametric and model structure uncertainty. The model structureuncertainty is a systematic uncertainty, which relates to uncertainty about theappropriate mathematical structure of the models. Here we quantified the modelstructure uncertainty in predicting WFN arising from multi-input models,including nine ground impedance and four wind speed profile models. We used anumerical ray tracing sound propagation model for predicting the noise level atdifferent receivers. We found that variations between different groundimpedance models and wind speed profile models were significant sources ofuncertainty, and that these sources contributed to predicted noise leveldifferences in excess of 10 dBA at distances greater than 3.5 km. We also foundthat differences between atmospheric vertical wind speed profile models werethe main source of uncertainty in predicting WFN at long-range distances. Whenpredicting WFN, it is important to acknowledge variability associated withdifferent models as this contributes to the uncertainty of the predictedvalues.

Multi-input model uncertainty analysis for long-range wind farm noise predictions