Class Generation for Numerical Wind Atlases

摘要

A new optimised clustering method is presented for generating wind classes for mesoscale modelling to produce numerical wind atlases. It is compared with the existing method of dividing the data in 12 to 16 sectors, 3 to 7 wind-speed bins and dividing again according to the stability of the atmosphere. Wind atlases are typically produced using many years of on-site wind observations at many locations. Numerical wind atlases are the result of mesoscale model integrations based on synoptic scale wind climates and can be produced in a number of hours of computation. 40 years of twice daily NCEP/NCAR Reanalysis geostrophic wind data (approximately 200 km resolution) are represented in typically around 150 classes, each with a frequency of occurrence.