Browsing by Subject "tuulimallinnus"

Wind is often difficult to include in microclimatic research due to its high spatial and temporal variability. The development of wind speed and direction measurement methods together with the increase in available surface wind models and computational resources enable wind field simulation on a high temporal and spatial resolution. Winds were measured during summer 2018 in a topographically varying landscape of mostly low vegetation in Finnish Lapland. Six ultrasonic anemometers were placed to measure wind speed and direction in positions of varying topography and vegetation. Based on June 2018 data, topography has a clear effect on wind speeds but the effect of vegetation was not visible from the data. The highest average wind speeds measured on the study area varied between 6.3 m/s – 13.2 m/s, and highest gust wind speeds between 10.1 m/s – 17.1 m/s. The anemometers' data was used in modeling wind fields with WindNinja application to study areas of both topographic and vegetational variation and also to a larger area surrounding the study site. WindNinja is a diagnostic wind model, into which the data were applied as virtual weather stations. The modeling results were compared to measured wind speeds by leave-one-out validation. Spearman correlation coefficients between measured and simulated average wind speeds varied between 0.28 – 0.59, RMSE values between 1.1 – 2.6 m/s and MAE values between 0.8 – 2.0 m/s. The respective values for gust wind simulations were 0.42 – 0.63, 1.6 – 2.7 m/s and 1.2 – 2.1 m/s. Overall WindNinja underpredicted high wind speeds and overpredicted low speeds. In modeling results, topography had a clear effect on regional and local wind fields on all modeling areas Winds were strongest on top of ridges and weakest in depressions. Vegetation had very local effects to wind speed by increasing and lowering it. The results give a good overview of the small-scale windiness variability in the modeling areas. To further examine the micro- and mesoclimatic effects of windiness, the results of this thesis should be combined with other research conducted in the area. WindNinja has potential to further use in high resolution wind modeling, which is an important factor of microclimatic research in the changing climate. However, the software’s graphical user interface is not optimal for modeling longer periods of wind data.