DYNAMICAL STATISTICAL DOWNSCALING PROCEDURE FOR WIND CLIMATE ASSESSMENT AND ITS VERIFICATION BY OBSERVATION

Abstract

A hybrid approach of computational fluid dynamics and mesoscale modeling, Dynamical statistical downscaling procedure was proposed for wind climate assessment without onsite measurement and verified at Tappi Cape. The atmospheric stratification at Tsugaru Strait during summer causes flow convergence, which results in high wind speed at the cape throughout the year. Idealizing and realizing approach with computational fluid dynamics can take the effect of local terrain into account and the prediction error of annual mean wind speed at Tappi Wind Park was 7.6 percent. Compared to the spatial conditional nesting and temporal conditional nesting, proposed method reduce the prediction error of annual and monthly mean wind speed at Tappi Lighthouse from 29.8 percent to 4.6 percent and from 19.3 percent to 5.9 percent respectively.