WRF Downscaling Experiment over Honkajoki Wind Farm in Western Finland

SNIC 2017/1-28


SNAC Medium

Principal Investigator:

Javier Martin-Torres


Luleå tekniska universitet

Start Date:


End Date:


Primary Classification:

10508: Meteorologi och atmosfärforskning



This project is in collaboration with Novia University of Applied Sciences (Finland) and Umeå University (Sweden). The Weather Research and Forecasting (WRF) model is set up for the Honkajoki wind farm located in western Finland. A simple wind farm parameterization scheme that assumes wind turbines to act as a momentum sink on the mean flow and configured for this particular wind farm (the wind turbine parameters are provided by the manufacturer) is employed and is found to improve the simulation of the observed winds. The power produced by the wind turbines is one of the model outputs that will be used to better understand the patterns of energy generation by the wind farm. The model is set up with 60 levels in the vertical with about 20 levels in the lowest 200 m giving a good vertical resolution to allow a proper evaluation of the temperature and wind vertical profiles. These two fields in the lowest atmosphere (bottom 500 m) will be used to produce speed of sound profiles and subsequently refractive indices. Acoustic rays will then be placed in carefully chosen locations and ray tracing techniques will be applied to track sound waves and understand their propagation. The model output will be compared with observed data from a weather mast, a sodar and a microwave radiometer located near the wind farm. Preliminary results showed a good model performance. The results of this work will be useful for wind turbine manufacturers (e.g. information regarding the power generated by wind turbines for different seasons and atmospheric conditions can be provided), those performing laboratory experiments related to wind turbine activities as well as all researchers interested in producing model simulations of wind farms in particular in regions with a cold climate.