A Multi-Point Meso–Micro Downscaling Method Including Atmospheric Stratification

In wind energy site assessment, one major challenge is to represent both the local characteristics as well general representation of climate on site. Micro-scale models (e.g., Reynolds-Averaged-Navier-Stokes (RANS)) excel in former, while meso-scale Weather Research and Forecasting (WRF)) latter. This paper presents a fast approach for meso–micro downscaling an industry-applicable computational fluid dynamics (CFD) modeling framework. The model independent postprocessing tool chain applied using New European Wind Atlas (NEWA) THETA micro-scale side. We adapt previously developed methodology extend it including stratification. compare single- multi-point critical flow situations proof concept long-term mast data at Rödeser Berg central Germany. longterm analysis, respect pure results, statistical bias can be reduced up 45% with single-point 107% (overcorrection 7%) downscaling. conclude that vital combine accuracy. further capable include shear or veer from into downscaled velocity field. adds both, accuracy robustness, by minimal cost. new introduction stratification provides marginal difference selected stability conditions, but gives prospect handling assessment future applications.