| This research explores the performance of a regional scale numerical climate model (MM5) with respect to the estimation of the wind resource over the Great Lakes region of North America. Three model domain resolutions (36 km, 12 km and 4 km) are evaluated for accuracy. Additionally, the ability of the model to accurately estimate the wind resource distribution at specific locations is investigated by employing various spatial aggregation schemes over the model domain.; The results of this evaluation of the MM5 model indicated that a coarser resolution domain provides the most reliable estimates of the wind resource over the region. Furthermore, only the nearest grid point appears to be a necessary estimator of the wind regime at a particular location. Using this information, the MM5 model estimates were compared with estimates produced by three statistical models, a joint probabilistic model, a measure-correlate-predict model, and a Krige model, all of which have been used with prior success in wind resource estimation. Of the three statistical models, the joint probabilistic and measure-correlate-predict models provided the best estimates over the region and were thus compared with the MM5 estimates.; It was determined that none of the three models significantly outperformed the others, even at relatively remote locations within the study area. However, it also was noted that the MM5 model contained a much higher systematic proportion of total estimative bias, and that it might be possible to improve the estimates. A multiple linear regression based upon Latitude was fit to the estimated Weibull parameters from the MM5 model and a significant improvement was noted. However, the improvement failed to cause the MM5 to significantly outperform the other models. Thus, this research concludes that in its present state and relative complexity of implementation relative to established statistical models, MM5 would not be a logical choice for estimating the wind resources of the Great Lakes region. |
