Spatial Analysis of Analog Ensemble Forecasts for Wind Forecasting
This research presents an application of an analog-based method for short-term wind speed prediction. The long-term goal is to use this methodology operationally in the management of wind farms. Further investigation of the application of analog models to improve the short-term prediction of wind speed and direction is needed. Utilizing past weather observations and forecast model output, Monache et al. (2013) worked to discover the best analog members for a specific site. The current research investigates how the addition of spatial analytics impacts the selection of ensemble members. Supervised machine learning and spatial analytics will be used to categorize regional subsets of stations to determine the impact on the analog ensemble output when spatial relationships are integrated into the effort. The hypothesis is that observations from neighbor stations will improve the short-term forecast predictions.
Supplementary URL: http://geoinf.psu.edu