Presentations

Abstract

Together with on-site measurements, mesoscale models are commonly used to assess the wind resource at locations of planned wind farms, for instance by utilizing existing wind atlases like the New European Wind Atlas (NEWA; Dörenkämper et al., 2020), or by directly simulating the site of interesting, including the cluster wake effect from surrounding wind farms (e.g., Rosencrans et al., 2023). When generating these results, the emphasis often lies in ensuring an optimized model setup, particularly in terms of spatial resolution and the selection of boundary and surface layer schemes. However, many other model settings tend to be directly copied from previous studies, while their impact on the wind resource estimates is not well understood. One that is highlighted in the current work is the microphysics scheme. Microphysics schemes are historically well developed within numerical weather prediction models for their critical role in precipitation modeling - one of the earliest uses of weather forecasts. While in wind studies the accuracy of the precipitation estimates is typically ignored, the question arises whether this is sensible. Precipitation will upset the local energy balance, as the latent heat flux will increase at the expense of the sensible heat flux. This increased latent heat flux will bring more water vapor into the air, thereby lowering the air density. The decreased sensible heat flux will lower the turbulent kinetic energy due to smaller buoyancy-generated turbulence, thereby affecting the mixing in the boundary layer and with that the atmospheric stability and vertical wind profiles. This will surely affect wind estimates in the short time scale, but it is currently not well understood how this affects the long-term wind resource. The objective of this work is to investigate whether the choice of microphysics scheme in numerical weather prediction models is relevant for wind resource assessment. The Weather Research and Forecasting (WRF, Skamarock et al., 2019) model is utilized, using a model setup optimized for the wind resource in the German Bight (Cañadillas et al., 2022) as a basis. A series of sensitivity tests, involving various commonly used microphysics schemes, are carried out for multiple geographical locations exhibiting a range of geospatial characteristics. Simulation data is compared to measurement data with a focus on wind speed, wind direction and precipitation. Results from these sensitivity tests demonstrate that the errors in precipitation estimates are large, especially in complex terrain. During precipitation events the wind speed estimates vary, exhibiting significant differences when the precipitation rate is high, while they converge soon after the event is over. In terms of yearly averaged wind speed, the differences are within a few percent. More detailed analyses include studying the relation between precipitation and wind speed to investigate whether a more accurate precipitation estimate can help reduce wind speed biases. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.