  With all the improvement in wave and hydrodynamics numerical models, the
question rises in our mind that how the accuracy of the forcing functions and
their input can affect the results. In this paper, a commonly used numerical
third generation wave model, SWAN is applied to predict waves in Lake Michigan.
Wind data were analyzed to determine wind variation frequency over Lake
Michigan. Wave predictions uncertainty due to wind local effects were compared
during a period where wind had a fairly constant speed and direction over the
northern and southern basins. The study shows that despite model calibration in
Lake Michigan area, the model deficiency arises from ignoring wind effects in
small scales. Wave prediction also emphasizes that small scale turbulence in
meteorological forces can increase error in predictions up to 35%. Wave
frequency and coherence analysis showed that both models are able to reveal the
time scale of the wave variation with same accuracy. Insufficient number of
meteorological stations can result in neglecting local wind effects and
discrepancies in current predictions. The uncertainty of wave numerical models
due to input uncertainties and model principals should be taken into account
for design risk factors.
