ПРИВЕДЕННЯ ДАНИХ ВИМІРЮВАНЬ ШВИДКОСТІ ВІТРУ ДО УМОВ ВІДКРИТОЇ МІСЦЕВОСТІ

Abstract

Wind speed spatial distribution over the territory of Ukraine built based on weather stations measurements has been analyzed. Interpolated field of wind speed averaged over 1981-2010 indicated fairly heterogeneous structure with a number of artificial spots of larger/smaller values compared to surrounding areas. The main reason of such heterogeneity might be associated with representativeness of observation site regarding the landscape zone. It is well known that surrounding obstacles have a great impact on wind flow in horizontal direction. In order to solve this problem we have corrected sub-daily wind speed data measured at 207 meteorological stations of Ukraine for the period of 1981-2010 according to the open terrain conditions and the standard height (10 m). Generally, aerodynamic characteristics (e.g. surface roughness length) of measurement sites are needed in order to perform such adjustment. However, the only usable parameter available at a climatological reference book is horizon closure degree. The research revealed significant relationship between this characteristic and wind speed records (Pearson correlation coefficient equals -0.58). Given that horizon closure degree could not be used in correction procedure directly, surface roughness length has been calculated for 10 stations and statistical relationship has been determined between these two parameters. Based on the obtained relation and additional information we have found roughness length for all 207 stations at eight directions. Supplementary materials for analysis included observation sites description and Google Earth snapshots as well. In the final step, there has been applied a correction formula derived from the neutral logarithmic profile of wind speed in the atmospheric surface layer. The output of the research is new database of corrected wind speed measurements for the multiyear period. These results have been compared with observations. Mean 30-yr corrected speeds are featured by more homogeneous distribution over Ukraine and mostly higher values (with positive mean spatial bias ~0.35 m/s). The applied method allowed us to remove uncertainties related to differences in vertical level of measurements and considerably eliminate influence of the micro-scale terrain inhomogeneity. Obtained datasets may facilitate to perform spatial interpolation and further development of Ukrainian Wind Atlas.