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