Despite widespread community acceptance of renewable power generation to reduce CO2 emissions and natural resource impacts, large-scale expansion of wind farms has prompted significant community debate regarding adverse health impacts of wind farm noise (WFN). Our research has aimed to investigate this issue by identifying, quantifying, and characterising the components of WFN that are responsible for annoyance and sleep disturbance. In this study, we carried out 1-year-long acoustic and meteorological measurements at three residences located near different wind farms, allowing detailed characterisation of WFN and its relationship with meteorological conditions. At two of these residences, participants recorded their subjective annoyance, providing insight into the relationship between specific noise features and human response. To detect amplitude modulation (AM), which is a particularly annoying component of WFN, we used a novel detection algorithm which significantly outperformed previous methods. Application of this algorithm revealed that AM prevalence was 2 to 5 times higher during the nighttime compared to the daytime. Annoyance due to WFN was reported most often during the nighttime and early morning, consistent with the measured AM prevalence. Participants most often described the noise as a “swish” or “swoosh” and the presence of these signal components was confirmed via spectral analysis.